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Atomizer/studies/bracket_stiffness_optimization_atomizerfield/2_results/study.db

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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
SQLite format 3@ ><3E>a><3E>.<2E><><0F><0F> <0C> <0A>  E f
feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
<EFBFBD>K<07>d<07><04>a<04><01>(<01><01>Qe?indexsqlite_autoindex_trial_intermediate_values_1trial_intermediate_values<16>E%%<01>Mtabletrial_valuestrial_valuesCREATE TABLE trial_values (
trial_value_id INTEGER NOT NULL,
trial_id INTEGER NOT NULL,
objective INTEGER NOT NULL,
value FLOAT,
value_type VARCHAR(7) NOT NULL,
PRIMARY KEY (trial_value_id),
UNIQUE (trial_id, objective),
FOREIGN KEY(trial_id) REFERENCES trials (trial_id)
)7K%indexsqlite_autoindex_trial_values_1trial_values<14>,%%<01>tabletrial_paramstrial_paramsCREATE TABLE trial_params (
param_id INTEGER NOT NULL,
trial_id INTEGER,
param_name VARCHAR(512),
param_value FLOAT,
distribution_json TEXT,
PRIMARY KEY (param_id),
UNIQUE (trial_id, param_name),
FOREIGN KEY(trial_id) REFERENCES trials (trial_id)
)7K%indexsqlite_autoindex_trial_params_1trial_params<12>I;;<01>)tabletrial_system_attributestrial_system_attributesCREATE TABLE trial_system_attributes (
trial_system_attribute_id INTEGER NOT NULL,
trial_id INTEGER,
"key" VARCHAR(512),
value_json TEXT,
PRIMARY KEY (trial_system_attribute_id),
UNIQUE (trial_id, "key"),
FOREIGN KEY(trial_id) REFERENCES trials (trial_id)
)Ma;indexsqlite_autoindex_trial_system_attributes_1trial_system_attributes<10>? 77<01>tabletrial_user_attributestrial_user_attributes CREATE TABLE trial_user_attributes (
trial_user_attribute_id INTEGER NOT NULL,
trial_id INTEGER,
"key" VARCHAR(512),
value_json TEXT,
PRIMARY KEY (trial_user_attribute_id),
UNIQUE (trial_id, "key"),
FOREIGN KEY(trial_id) REFERENCES trials (trial_id)
)I ]7indexsqlite_autoindex_trial_user_attributes_1trial_user_attributesX 1uindexix_trials_study_idtrials CREATE INDEX ix_trials_study_id ON trials (study_id)<29>
<01> tabletrialstrials CREATE TABLE trials (
trial_id INTEGER NOT NULL,
number INTEGER,
study_id INTEGER,
state VARCHAR(8) NOT NULL,
datetime_start DATETIME,
datetime_complete DATETIME,
PRIMARY KEY (trial_id),
FOREIGN KEY(study_id) REFERENCES studies (study_id)
)<29>J;;<01>+tablestudy_system_attributesstudy_system_attributes CREATE TABLE study_system_attributes (
study_system_attribute_id INTEGER NOT NULL,
study_id INTEGER,
"key" VARCHAR(512),
value_json TEXT,
PRIMARY KEY (study_system_attribute_id),
UNIQUE (study_id, "key"),
FOREIGN KEY(study_id) REFERENCES studies (study_id)
)M a;indexsqlite_autoindex_study_system_attributes_1study_system_attributes
<EFBFBD>@77<01>tablestudy_user_attributesstudy_user_attributesCREATE TABLE study_user_attributes (
study_user_attribute_id INTEGER NOT NULL,
study_id INTEGER,
"key" VARCHAR(512),
value_json TEXT,
PRIMARY KEY (study_user_attribute_id),
UNIQUE (study_id, "key"),
FOREIGN KEY(study_id) REFERENCES studies (study_id)
)I]7indexsqlite_autoindex_study_user_attributes_1study_user_attributes<08>J--<01>Gtablestudy_directionsstudy_directionsCREATE TABLE study_directions (
study_direction_id INTEGER NOT NULL,
direction VARCHAR(8) NOT NULL,
study_id INTEGER NOT NULL,
objective INTEGER NOT NULL,
PRIMARY KEY (study_direction_id),
UNIQUE (study_id, objective),
FOREIGN KEY(study_id) REFERENCES studies (study_id)
)?S-indexsqlite_autoindex_study_directions_1study_directions<00>\%%<01>{tableversion_infoversion_infoCREATE TABLE version_info (
version_info_id INTEGER NOT NULL,
schema_version INTEGER,
library_version VARCHAR(256),
PRIMARY KEY (version_info_id),
CHECK (version_info_id=1)
)j7<01>indexix_studies_study_namestudiesCREATE UNIQUE INDEX ix_studies_study_name ON studies (study_name)<29> <01>otablestudiesstudiesCREATE TABLE studies (
study_id INTEGER NOT NULL,
study_name VARCHAR(512) NOT NULL,
PRIMARY KEY (study_ <0F><0F>/ebracket_stiffness_
<0F><0F>/e bracket_stiffness_optimization_atomizerfield
 4.6.0 <0F><0F><0F>  MINIMIZE 
<0F><0F><0F>  
feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00

feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
<EFBFBD>
feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
<EFBFBD>
feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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 9NSGAIISampler:parent:9  9NSGAIISampler:parent:8 9NSGAIISampler:parent:7 9NSGAIISampler:parent:6 9NSGAIISampler:parent:5 9NSGAIISampler:parent:4 9NSGAIISampler:parent:3 9NSGAIISampler:parent:2 9 NSGAIISampler:parent:1f^<0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>~xrlf<07><07>B<06><06>p*<05><05>X<04><04>@<03><03>n(<02><02>V<01><01>><00><00><00>)9 A8RUNNING2025-11-26 10:10:32.839448D8 AA7COMPLETE2025-11-26 10:10:23.8373122025-11-26 10:10:32.825555D7 AA6COMPLETE2025-11-26 10:10:14.9541872025-11-26 10:10:23.827735D6 AA5COMPLETE2025-11-26 10:10:05.4369492025-11-26 10:10:14.935533D5 AA4COMPLETE2025-11-26 10:09:58.5129502025-11-26 10:10:05.374400D4 AA3COMPLETE2025-11-26 10:09:50.9286782025-11-26 10:09:58.498530D3 AA2COMPLETE2025-11-26 10:09:43.8627072025-11-26 10:09:50.913567D2 AA1COMPLETE2025-11-26 09:57:17.3820342025-11-26 09:57:23.221697D1 AA0COMPLETE2025-11-26 09:57:11.0572152025-11-26 09:57:17.360461D0 AA/COMPLETE2025-11-26 09:57:04.6176732025-11-26 09:57:11.036550D/ AA.COMPLETE2025-11-26 09:56:58.7679292025-11-26 09:57:04.610111D. AA-COMPLETE2025-11-26 09:56:53.0200252025-11-26 09:56:58.757188D- AA,COMPLETE2025-11-26 09:56:47.2702162025-11-26 09:56:53.002123D, AA+COMPLETE2025-11-26 09:56:41.3473222025-11-26 09:56:47.247643D+ AA*COMPLETE2025-11-26 09:56:35.1957752025-11-26 09:56:41.328939D* AA)COMPLETE2025-11-26 09:56:29.5055992025-11-26 09:56:35.167371D) AA(COMPLETE2025-11-26 09:56:23.2641072025-11-26 09:56:29.494334D( AA'COMPLETE2025-11-26 09:56:17.4213352025-11-26 09:56:23.258564D' AA&COMPLETE2025-11-26 09:56:11.4373682025-11-26 09:56:17.397182D& AA%COMPLETE2025-11-26 09:56:05.7039172025-11-26 09:56:11.415465D% AA$COMPLETE2025-11-26 09:55:59.8427662025-11-26 09:56:05.611222D$ AA#COMPLETE2025-11-26 09:55:53.7106622025-11-26 09:55:59.838763D# AA"COMPLETE2025-11-26 09:55:47.7262522025-11-26 09:55:53.683303D" AA!COMPLETE2025-11-26 09:55:42.0921032025-11-26 09:55:47.715457D! AA COMPLETE2025-11-26 09:55:35.9414132025-11-26 09:55:42.079760D  AACOMPLETE2025-11-26 09:55:29.7593912025-11-26 09:55:35.930470D AACOMPLETE2025-11-26 09:55:23.8146452025-11-26 09:55:29.755969D AACOMPLETE2025-11-26 09:55:18.0609212025-11-26 09:55:23.792547D AACOMPLETE2025-11-26 09:55:11.9630892025-11-26 09:55:18.036240D AACOMPLETE2025-11-26 09:55:05.8470112025-11-26 09:55:11.952320D AACOMPLETE2025-11-26 09:55:00.0172652025-11-26 09:55:05.836727D AACOMPLETE2025-11-26 09:54:54.1073612025-11-26 09:55:00.005702D AACOMPLETE2025-11-26 09:54:48.3563892025-11-26 09:54:54.100156D AACOMPLETE2025-11-26 09:54:42.2304842025-11-26 09:54:48.333043D AACOMPLETE2025-11-26 09:54:36.4285252025-11-26 09:54:42.201980D AACOMPLETE2025-11-26 09:54:30.6621242025-11-26 09:54:36.417029D AACOMPLETE2025-11-26 09:54:24.7789212025-11-26 09:54:30.651604D AACOMPLETE2025-11-26 09:54:18.8004612025-11-26 09:54:24.770437D AACOMPLETE2025-11-26 09:54:12.9151432025-11-26 09:54:18.785268D AACOMPLETE2025-11-26 09:54:06.9720402025-11-26 09:54:12.909595D AACOMPLETE2025-11-26 09:54:00.8944282025-11-26 09:54:06.967077D AACOMPLETE2025-11-26 09:53:54.4963112025-11-26 09:54:00.867620D AACOMPLETE2025-11-26 09:53:47.4324022025-11-26 09:53:54.469904D AA COMPLETE2025-11-26 09:53:41.2930332025-11-26 09:53:47.414597D  AA COMPLETE2025-11-26 09:53:28.6517992025-11-26 09:53:41.280545D  AA COMPLETE2025-11-26 09:53:21.9109332025-11-26 09:53:28.631334D  AA
COMPLETE2025-11-26 09:53:14.3793422025-11-26 09:53:21.887921D
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00

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feasibletrue)-3
max_displacement0.090150550007820133
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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COMPLETE2025-11-26 10:41:44.7075122025-11-26 10:41:54.052654E<EFBFBD>
 AA COMPLETE2025-11-26 10:41:35.5275882025-11-26 10:41:44.687662E<EFBFBD>  AACOMPLETE2025-11-26 10:41:26.1507342025-11-26 10:41:35.511648E<EFBFBD> AACOMPLETE2025-11-26 10:41:16.7012082025-11-26 10:41:26.132176<0F><03> AA<00>COMPLETE2025-11-26 10:38:11.3391112025-11-26 10:38:11.525720` AA<00>COMPLETE2025-11-26 10:38:11.0911112025-11-26 10:38:11.327590 AA<00>COMPLETE2025-11-26 10:38:10.8727182025-11-26 10:38:11.075415<02> AA<00>COMPLETE2025-11-26 10:38:10.6603252025-11-26 10:38:10.858741<02> AA<00>COMPLETE2025-11-26 10:38:10.4455422025-11-26 10:38:10.648359@ AA<00>COMPLETE2025-11-26 10:38:10.1744922025-11-26 10:38:10.422399<01> AA<00>COMPLETE2025-11-26 10:38:09.9457012025-11-26 10:38:10.159287<01> AA<00>COMPLETE2025-11-26 10:38:09.7231942025-11-26 10:38:09.936714h AA<00>COMPLETE2025-11-26 10:38:09.4814282025-11-26 10:38:09.710399  AA<00>COMPLETE2025-11-26 10:38:09.2516022025-11-26 10:38:09.467603<00> AA<00>COMPLETE2025-11-26 10:38:09.0374252025-11-26 10:38:09.241302<00> AA<00>COMPLETE2025-11-26 10:38:08.7888992025-11-26 10:38:09.008117H AA<00>COMPLETE2025-11-26 10:38:08.5712592025-11-26 10:38:08.774947E<EFBFBD> AACOMPLETE2025-11-26 10:41:07.3976292025-11-26 10:41:16.685868E<EFBFBD> AACOMPLETE2025-11-26 10:40:58.0886022025-11-26 10:41:07.377655E<EFBFBD> AACOMPLETE2025-11-26 10:40:50.4290512025-11-26 10:40:58.073727E<EFBFBD> AACOMPLETE2025-11-26 10:40:40.8851652025-11-26 10:40:50.416044E<EFBFBD> AACOMPLETE2025-11-26 10:40:32.1089222025-11-26 10:40:40.868671E<EFBFBD> AACOMPLETE2025-11-26 10:40:23.1703662025-11-26 10:40:32.092561E<EFBFBD> AACOMPLETE2025-11-26 10:40:14.6789992025-11-26 10:40:23.150705E<EFBFBD> AA<00>COMPLETE2025-11-26 10:40:06.2895232025-11-26 10:40:14.663482E<EFBFBD> AA<00>COMPLETE2025-11-26 10:39:56.7670542025-11-26 10:40:06.268315E<EFBFBD>~ AA<00>COMPLETE2025-11-26 10:39:47.6708972025-11-26 10:39:56.749215E<EFBFBD>} AA<00>COMPLETE2025-11-26 10:39:40.3445252025-11-26 10:39:47.651020E<EFBFBD>| AA<00>COMPLETE2025-11-26 10:39:34.1039712025-11-26 10:39:40.332926E<EFBFBD>{ AA<00>COMPLETE2025-11-26 10:39:27.9976692025-11-26 10:39:34.092683H AA<00>COMPLETE2025-11-26 10:38:11.5378552025-11-26 10:38:11.737042
<0B><00>d<07><07><07><07><07>~hR<&<06><06><06><06><06><06>v`J4 <0B> <0B> r \ F 0  
<EFBFBD>
<EFBFBD>
<EFBFBD>
feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
<EFBFBD>
feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
<EFBFBD>
feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
<EFBFBD>
<EFBFBD>
feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
^
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<EFBFBD>
<EFBFBD>
`
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NSGAIISampler:generation26!<21> = NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=NSGAIISampler:generation25!<21>=<01>NSGAIISampler:generation25!<21>~=<01>NSGAIISampler:generation25!<21>}=<01>NSGAIISampler:generation25!<21>|=<01>NSGAIISampler:generation25!<21>{=<01>NSGAIISampler:generation25!<21>z=<01>NSGAIISampler:generation25!<21>y=<01>NSGAIISampler:generation25!<21>x=<01>NSGAIISampler:generation25!<21>w=<01>NSGAIISampler:generation25!<21>v=<01>NSGAIISampler:generation25!<21>u=<01>NSGAIISampler:generation24!<21>t=<01>NSGAIISampler:generation24!<21>s=<01>NSGAIISampler:generation24!<21>r=<01>NSGAIISampler:generation24!<21>q=<01>NSGAIISampler:generation24!<21>p=<01>NSGAIISampler:generation24!<21>o=<01>NSGAIISampler:generation24!<21>n=<01>NSGAIISampler:generation24!<21>m=<01>NSGAIISampler:generation24!<21>l=<01>NSGAIISampler:generation24!<21>k=<01>NSGAIISampler:generation24!<21>j=<01>NSGAIISampler:generation24!<21>i=<01>NSGAIISampler:generation24!<21>h=<01>NSGAIISampler:generation24!<21>g=<01>NSGAIISampler:generation24!<21>f=<01>NSGAIISampler:generation24!<21>e=<01>NSGAIISampler:generation24!<21>d=<01>NSGAIISampler:generation24!<21>c=<01>NSGAIISampler:generation24!<21>b=<01>NSGAIISampler:generation24!<21>a=<01>NSGAIISampler:generation23!<21>`=<01>NSGAIISampler:generation23!<21>_=<01>NSGAIISampler:generation23!<21>^=<01>NSGAIISampler:generation23!<21>]=<01>NSGAIISampler:generation23!<21>\=<01>NSGAIISampler:generation23!<21>[=<01>NSGAIISampler:generation23!<21>Z=<01>NSGAIISampler:generation23!<21>Y=<01>NSGAIISampler:generation23!<21>X=<01>NSGAIISampler:generation23!<21>W=<01>NSGAIISampler:generation23!<21>V=<01>NSGAIISampler:generation23!<21>U=<01>NSGAIISampler:generation23!<21>T=<01>NSGAIISampler:generation23!<21>S=<01>NSGAIISampler:generation23!<21>R=<01>NSGAIISampler:generation23!<21>Q=<01>NSGAIISampler:generation23!<21>P=<01>NSGAIISampler:generation23!<21>O=<01>NSGAIISampler:generation23!<21>N=<01>NSGAIISampler:generation23!<21>M=<01>NSGAIISampler:generation22!<21>L=<01>NSGAIISampler:generation22!<21>K=<01>NSGAIISampler:generation22!<21>J=<01>NSGAIISampler:generation22!<21>I=<01>NSGAIISampler:generation22!<21>H=<01>NSGAIISampler:generation22!<21>G=<01>NSGAIISampler:generation22!<21>F=<01>NSGAIISampler:generation22!<21>E=<01>NSGAIISampler:generation22!<21>D=<01>NSGAIISampler:generation22!<21>C=<01>NSGAIISampler:generation22!<21>B=<01>NSGAIISampler:generation22!<21>A=<01>NSGAIISampler:generation22!<21>@=<01>NSGAIISampler:generation22!<21>?=<01>NSGAIISampler:generation22!<21>>=<01>NSGAIISampler:generation22!<21>==<01>NSGAIISampler:generation22!<21><=<01>NSGAIISampler:generation22!<21>;=<01>NSGAIISampler:generation22!<21>:=<01>NSGAIISampler:generation22!<21>9=<01>NSGAIISampler:generation21 Lz<0E>n <0A> b <0C> V <0B> J
feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
<EFBFBD>
feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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feat: Add AtomizerField training data export and intelligent model discovery Major additions: - Training data export system for AtomizerField neural network training - Bracket stiffness optimization study with 50+ training samples - Intelligent NX model discovery (auto-detect solutions, expressions, mesh) - Result extractors module for displacement, stress, frequency, mass - User-generated NX journals for advanced workflows - Archive structure for legacy scripts and test outputs - Protocol documentation and dashboard launcher 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00
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feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements ## Protocol 13: Adaptive Multi-Objective Optimization - Iterative FEA + Neural Network surrogate workflow - Initial FEA sampling, NN training, NN-accelerated search - FEA validation of top NN predictions, retraining loop - adaptive_state.json tracks iteration history and best values - M1 mirror study (V11) with 103 FEA, 3000 NN trials ## Dashboard Visualization Enhancements - Added Plotly.js interactive charts (parallel coords, Pareto, convergence) - Lazy loading with React.lazy() for performance - Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB) - Chart library toggle (Recharts default, Plotly on-demand) - ExpandableChart component for full-screen modal views - ConsoleOutput component for real-time log viewing ## Documentation - Protocol 13 detailed documentation - Dashboard visualization guide - Plotly components README - Updated run-optimization skill with Mode 5 (adaptive) ## Bug Fixes - Fixed TypeScript errors in dashboard components - Fixed Card component to accept ReactNode title - Removed unused imports across components 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
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Efeasibletrue*<2A> -3Emax_displacement0.07015468138338893<1E>3Emass0.12074094461175466!<21>/Estiffness14254.21625871396)<29>//Dinference_time_ms21.69632911682129<1B>-Dneural_predictedtrue<13>Dfeasibletrue*<2A>-3Dmax_displacement0.09945153265970588<1C>/Dmass0.112125398447712"<22>1Dstiffness10055.149209431574*<2A>/1Cinference_time_ms11.544227600097656<1B>-Cneural_predictedtrue<13>~Cfeasibletrue*<2A>}-3Cmax_displacement0.09945153265970588<1C>|/Cmass0.112125398447712"<22>{1Cstiffness10055.149209431574)<29>z//Binference_time_ms8.040666580200195<1B>y-Bneural_predictedtrue<13>xBfeasibletrue*<2A>w-3Bmax_displacement0.07801229603868466<1E>v3Bmass0.11602756188125603"<22>u1Bstiffness12818.492093914541)<29>t//Ainference_time_ms8.027315139770508<1B>s-Aneural_predictedtrue<13>rAfeasibletrue*<2A>q-3Amax_displacement0.06480094966300026<1E>p3Amass0.12404644574633664"<22>o1Astiffness15431.872606814206<1B>n/@inference_time_ms0.0<1B>m-@neural_predictedtrue<13>l@feasibletrue*<2A>k-3@max_displacement0.07713634080978933<1E>j3@mass0.11648041379067464"<22>i1@stiffness12964.058049705807)<29>h//?inference_time_ms4.670381546020508<1B>g-?neural_predictedtrue<13>f?feasibletrue*<2A>e-3?max_displacement0.07801229603868466<1E>d3?mass0.11602756188125603"<22>c1?stiffness12818.492093914541)<29>b//>inference_time_ms2.609729766845703<1B>a->neural_predictedtrue<13>`>feasibletrue*<2A>_-3>max_displacement0.05267580537137354<1E>^3>mass0.14494405045796968"<22>]1>stiffness18984.047665713453)<29>\//=inference_time_ms8.022546768188477<1B>[-=neural_predictedtrue<13>Z=feasibletrue*<2A>Y-3=max_displacement0.07897821702799904<1E>X3=mass0.11551474602471279"<22>W1=stiffness12661.719112315286*<2A>V/1<inference_time_ms1.7435550689697266<1B>U-<neural_predictedtrue<13>T<feasibletrue*<2A>S-3<max_displacement0.16098268375065064<1E>R3<mass0.09661780412312546!<21>Q/<stiffness6211.848235484261)<29>P//;inference_time_ms8.031845092773438<1B>O-;neural_predictedtrue<13>N;feasibletrue*<2A>M-3;max_displacement0.10159614152606589<1D>L1;mass0.1115625854111662!<21>K/;stiffness9842.893489645336)<29>J//:inference_time_ms9.773969650268555<1B>I-:neural_predictedtrue<13>H:feasibletrue*<2A>G-3:max_displacement0.10798431236267682<1E>F3:mass0.10733292916349454!<21>E/:stiffness9260.604416698914(<28>D/-9inference_time_ms21.3472843170166<1B>C-9neural_predictedtrue<13>B9feasibletrue*<2A>A-39max_displacement0.07015468138338893<1E>@39mass0.12074094461175466!<21>?/9stiffness14254.21625871396*<2A>>/18inference_time_ms10.540485382080078<1B>=-8neural_predictedtrue<13><8feasibletrue*<2A>;-38max_displacement0.06762608962339779<1E>:38mass0.12122753624351572!<21>9/8stiffness14787.19242187282 Lz<0E>n <0A> b <0C> V <0B> J
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m-max_displacement
k mass
j/inference_time_ms
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l<01>stiffness
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d/<01>inference_time_ms
h<01>feasible
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b<01>feasible
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9/<01>inference_time_ms
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4<01>stiffness
3/<01>inference_time_ms
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<01>stiffness <09>-<01>max_displacement <09> <01>mass <09><01>feasible
<01>stiffness <09>-<01>neural_predicted <09>-<01>max_displacement <09> <01>mass <09>/<01>inference_time_ms <09><01>feasible <09><01>stiffness <09>-<01>neural_predicted <09>-<01>max_displacement <09> <01>mass <09>/<01>inference_time_ms <09><01>feasible <09><01>stiffness <09>-<01>neural_predicted <09>-<01>max_displacement <09> <01>mass <09>/<01>inference_time_ms <09><01>feasible <09>-<01>neural_predicted
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X/<01>inference_time_ms
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T<01>stiffness
K-<01>neural_predicted
O-<01>max_displacement
M <01>mass
L/<01>inference_time_ms
P<01>feasible
N<01>stiffness
E-<01>neural_predicted
I-<01>max_displacement
G <01>mass
F/<01>inference_time_ms
J<01>feasible
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1<01>mass0.1345568514254711!<21> /<01>stiffness15507.91207916077*<2A>/1<01>inference_time_ms11.012077331542969<1B>-<01>neural_predictedtrue<13><01>feasibletrue*<2A>-3<01>max_displacement0.06730507765854574<1E>3<01>mass0.12133407707151092"<22>1<01>stiffness14857.720023342545 Lz<0E>n <0A> b <0C> V <0B> J
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{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>n'<07>U<01>tip_thickness@><3E><16>6'<27>{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02>m'<07>U<01>support_angle@;<3B> <09><>U{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>l'<07>U<01>tip_thickness@A<><41><08>=Y{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02>k'<07>U<01>support_angle@Gp<><05>.{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>j'<07>U<01>tip_thickness@><3E><16>6'<27>{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02>i'<07>U<01>support_angle@P<>I(<28>_<EFBFBD>{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>h'<07>U<01>tip_thickness@MB<4D>1 x{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02>g'<07>U<01>support_angle@C]<0E><><{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>f'<07>U<01>tip_thickness@A<><41><08>=Y{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02>e'<07>U<01>support_angle@P<>I(<28>_<EFBFBD>{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>d'<07>U<01>tip_thickness@><3E><16>6'<27>{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02>c'<07>U<01>support_angle@D<>r<EFBFBD><72>s/{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>b'<07>U<01>tip_thickness@><3E><16>6'<27>{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02>a'<07>U<01>support_angle@5{EZB-{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>`'<07>U<01>tip_thickness@HH<19><>y{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02>_'<07>U<01>support_angle@;<3B> <09><>U{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}} 7<00><0F>p(<0E><0E>P <0A> x 0 <0C> <0C> X  <0B> <0B> 8
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{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>'<07>Utip_thickness@?<1A>fn{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02> '<07>Usupport_angle@Q<05><>P<EFBFBD>{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02> '<07>Utip_thickness@I<><49>S@n{"name": "FloatDistribution", "attributes": {"step": null, "low": 30.0, "high": 60.0, "log": false}}<7D><02> '<07>Usupport_angle@P<>I(<28>_<EFBFBD>{"name": "FloatDistribution", "attributes": {"step": null, "low": 20.0, "high": 70.0, "log": false}}<7D><02>
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<06><06><06><06>[7<05><05><05><05>eE<04><04><04>rE/<03><03><03>q[=<02><02><02><02>i=<01><01><01><01>iF%<00>*<2A>]-3max_displacement0.07894396187264156<1E>\3mass0.11551863428345494 <20>[-stiffness12667.2132520189*<2A>Z/1inference_time_ms12.529134750366211<1B>Y-neural_predictedtrue<13>Xfeasibletrue*<2A>W-3max_displacement0.06449288315281165<1E>V3mass0.12448544066396403"<22>U1stiffness15505.586835536033)<29>T//inference_time_ms12.51077651977539<1B>S-neural_predictedtrue<13>Rfeasibletrue*<2A>Q-3max_displacement0.04791887400771355<1E>P3mass0.15677539161002368"<22>O1stiffness20868.603879110953*<2A>N/1inference_time_ms13.017416000366211<1B>M-neural_predictedtrue<13>Lfeasibletrue*<2A>K-3max_displacement0.09292984929298069<1E>J3mass0.11375262976475145"<22>I1stiffness10760.805140738923*<2A>H/1inference_time_ms14.000654220581055<1B>G-neural_predictedtrue<13>Ffeasibletrue*<2A>E-3max_displacement0.05377366599691086<1E>D3mass0.14308838973413981"<22>C1stiffness18596.463184366992*<2A>B/1inference_time_ms10.000228881835938<1B>A-neural_predictedtrue<13>@feasibletrue)<29>?-1max_displacement0.0647919711561574<1D>>1mass0.1240418409244414"<22>=1stiffness15434.011068900265)<29><// inference_time_ms9.787559509277344<1B>;- neural_predictedtrue<13>: feasibletrue)<29>9-1 max_displacement0.1496304524366605<1E>83 mass0.09847589514662897!<21>7/ stiffness6683.131566572694)<29>6// inference_time_ms10.51783561706543<1B>5- neural_predictedtrue<13>4 feasibletrue+<2B>3-5 max_displacement0.050511304753679584<1E>23 mass0.15008243901780483"<22>11 stiffness19797.548387960684*<2A>0/1 inference_time_ms11.972665786743164<1B>/- neural_predictedtrue<13>. feasibletrue+<2B>--5 max_displacement0.050511304753679584<1E>,3 mass0.15008243901780483"<22>+1 stiffness19797.548387960684*<2A>*/1
inference_time_ms10.279417037963867<1B>)-
neural_predictedtrue<13>(
feasibletrue*<2A>'-3
max_displacement0.04697719379145715<1E>&3
mass0.16025502228143998"<22>%1
stiffness21286.924979794152*<2A>$/1 inference_time_ms12.087821960449219<1B>#- neural_predictedtrue<13>" feasibletrue*<2A>!-3 max_displacement0.04702884687281492<1E> 3 mass0.16096016015650255"<22>1 stiffness21263.544962188967*<2A>/1inference_time_ms15.485525131225586<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.09359577054302812<1E>3mass0.11358305179733316"<22>1stiffness10684.243467393402*<2A>/1inference_time_ms13.806343078613281<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.06730507765854574<1E>3mass0.12133407707151092"<22>1stiffness14857.720023342545)<29>//inference_time_ms13.91458511352539<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.05266834596462331<1E>3mass0.14494384517380104"<22> 1stiffness18986.736372387466*<2A> /1inference_time_ms13.000965118408203<1B> -neural_predictedtrue<13>
feasibletrue*<2A> -3max_displacement0.05564687641318733<1E>3mass0.13816670179152568"<22>1stiffness17970.460598270303*<2A>/1inference_time_ms11.826515197753906<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.05011701919816116<1D>1mass0.1531333877833006!<21>/stiffness19953.30161289183)<29>//inference_time_ms11.00778579711914<1B>-neural_predictedtrue<13>~feasibletrue*<2A>}-3max_displacement0.16110955251673992<1E>|3mass0.09645714829129376!<21>{/stiffness6206.956598033478*<2A>z/1inference_time_ms12.000799179077148<1B>y-neural_predictedtrue<13>xfeasibletrue*<2A>w-3max_displacement0.11535112021501308<1E>v3mass0.10538341825689987!<21>u/stiffness8669.183256616947*<2A>t/1inference_time_ms12.568235397338867<1B>s-neural_predictedtrue<13>rfeasibletrue*<2A>q-3max_displacement0.06833929792136484
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feasible stiffness
<EFBFBD>-neural_predicted -max_displacement  mass /inference_time_ms feasible stiffness
<EFBFBD>-neural_predicted
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<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
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<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD> stiffness
<EFBFBD>- neural_predicted
<EFBFBD>- max_displacement
<EFBFBD>  mass
<EFBFBD>/ inference_time_ms
<EFBFBD> feasible
<EFBFBD> stiffness
<EFBFBD>- neural_predicted
<EFBFBD>- max_displacement
<EFBFBD>  mass
<EFBFBD>/ inference_time_ms
<EFBFBD> feasible
<EFBFBD> stiffness
<EFBFBD>- neural_predicted
<EFBFBD>- max_displacement
<EFBFBD>  mass
<EFBFBD>/ inference_time_ms
<EFBFBD> feasible
<EFBFBD>
stiffness
<EFBFBD>-
neural_predicted
<EFBFBD>-
max_displacement
<EFBFBD> 
mass
<EFBFBD>/
inference_time_ms
<EFBFBD>
feasible
<EFBFBD> stiffness
<EFBFBD>- neural_predicted
<EFBFBD>- max_displacement
<EFBFBD>  mass
<EFBFBD>/ inference_time_ms
<EFBFBD> feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
<EFBFBD>-neural_predicted
<EFBFBD>-max_displacement
<EFBFBD> mass
<EFBFBD>/inference_time_ms
<EFBFBD>feasible
<EFBFBD>stiffness
{-neural_predicted
-max_displacement
} mass
|/inference_time_ms
<EFBFBD>feasible
~stiffness
u-neural_predicted
y-max_displacement
w mass
v/inference_time_ms
zfeasible
xstiffness
o-neural_predicted
s-max_displacement
q mass
p/inference_time_ms
tfeasible
rstiffness
i-neural_predicted
m-max_displacement
k mass
j/inference_time_ms
nfeasible
l<01>stiffness
c-<01>neural_predicted
g-<01>max_displacement
e <01>mass
d/<01>inference_time_ms
h<01>feasible
f<01>stiffness
]-<01>neural_predicted
a-<01>max_displacement
_ <01>mass
^/<01>inference_time_ms
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Dstiffness -Dneural_predicted -Dmax_displacement  Dmass /Dinference_time_ms Dfeasible Cstiffness <0B>-Cneural_predicted <0B>-Cmax_displacement <0B> Cmass <0B>/Cinference_time_ms Cfeasible <0B>Bstiffness <0B>-Bneural_predicted <0B>-Bmax_displacement <0B> Bmass <0B>/Binference_time_ms <0B>Bfeasible <0B>Astiffness <0B>-Aneural_predicted <0B>-Amax_displacement <0B> Amass <0B>/Ainference_time_ms <0B>Afeasible <0B>@stiffness <0B>-@neural_predicted <0B>-@max_displacement <0B> @mass <0B>/@inference_time_ms <0B>@feasible <0B>?stiffness <0B>-?neural_predicted <0B>-?max_displacement <0B> ?mass <0B>/?inference_time_ms <0B>?feasible <0B>>stiffness <0B>->neural_predicted <0B>->max_displacement <0B> >mass <0B>/>inference_time_ms <0B>>feasible <0B>=stiffness <0B>-=neural_predicted <0B>-=max_displacement <0B> =mass <0B>/=inference_time_ms <0B>=feasible <0B><stiffness <0B>-<neural_predicted <0B>-<max_displacement <0B> <mass <0B>/<inference_time_ms <0B><feasible <0B>;stiffness <0B>-;neural_predicted <0B>-;max_displacement <0B> ;mass <0B>/;inference_time_ms <0B>;feasible <0B>:stiffness <0B>-:neural_predicted <0B>-:max_displacement <0B> :mass <0B>/:inference_time_ms <0B>:feasible <0B>9stiffness <0B>-9neural_predicted <0B>-9max_displacement <0B> 9mass <0B>/9inference_time_ms <0B>9feasible <0B>8stiffness <0B>-8neural_predicted <0B>-8max_displacement <0B> 8mass <0B>/8inference_time_ms <0B>8feasible <0B>7stiffness <0B>-7neural_predicted <0B>-7max_displacement <0B> 7mass <0B>/7inference_time_ms <0B>7feasible <0B>6stiffness <0B>-6neural_predicted <0B>-6max_displacement <0B> 6mass <0B>/6inference_time_ms <0B>6feasible <0B>5stiffness <0B>-5neural_predicted <0B>-5max_displacement <0B> 5mass <0B>/5inference_time_ms <0B>5feasible <0B>4stiffness <0B>-4neural_predicted <0B>-4max_displacement <0B> 4mass <0B>/4inference_time_ms <0B>4feasible <0B>3stiffness <0B>-3neural_predicted <0B>-3max_displacement <0B> 3mass <0B>/3inference_time_ms <0B> Lz<0E>n <0A> b <0C> V <0B> J
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3pmass0.14278178568784738!<21> /pstiffness18480.73112585557*<2A>/1oinference_time_ms10.233402252197266<1B>-oneural_predictedtrue<13>ofeasibletrue)<29>-1omax_displacement0.0785706149785391<1E>3omass0.11746244745069215"<22>1ostiffness12727.404517237668*<2A>/1ninference_time_ms15.304327011108398
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/pinference_time_ms pfeasible ostiffness -oneural_predicted -omax_displacement  omass /oinference_time_ms ofeasible nstiffness <0C>-nneural_predicted -nmax_displacement <0C> nmass <0C>/ninference_time_ms nfeasible mstiffness <0C>-mneural_predicted <0C>-mmax_displacement <0C> mmass <0C>/minference_time_ms <0C>mfeasible <0C>lstiffness <0C>-lneural_predicted <0C>-lmax_displacement <0C> lmass <0C>/linference_time_ms <0C>lfeasible <0C>kstiffness <0C>-kneural_predicted <0C>-kmax_displacement <0C> kmass <0C>/kinference_time_ms <0C>kfeasible <0C>jstiffness <0C>-jneural_predicted <0C>-jmax_displacement <0C> jmass <0C>/jinference_time_ms <0C>jfeasible <0C>istiffness <0C>-ineural_predicted <0C>-imax_displacement <0C> imass <0C>/iinference_time_ms <0C>ifeasible <0C>hstiffness <0C>-hneural_predicted <0C>-hmax_displacement <0C> hmass <0C>/hinference_time_ms <0C>
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 ;<3B>KNSGAIISampler:parent:10[188, 7, 15, 58, 82, 103, 110, 123, 127, 130, 132, 138, 146, 149, 199, 144, 147, 180, 183, 165]{  9<>KNSGAIISampler:parent:9[180, 7, 15, 58, 82, 103, 110, 123, 127, 130, 132, 138, 146, 149, 165, 144, 169, 147, 164, 179]{ 9<>KNSGAIISampler:parent:8[146, 149, 159, 7, 15, 58, 82, 103, 110, 123, 127, 130, 132, 138, 144, 155, 147, 151, 160, 154]v 9<>ANSGAIISampler:parent:7[119, 96, 82, 130, 18, 7, 94, 127, 90, 15, 110, 103, 122, 58, 17, 138, 123, 125, 132, 109]s 9<>;NSGAIISampler:parent:6[96, 119, 82, 80, 58, 104, 18, 7, 90, 103, 15, 110, 109, 51, 108, 88, 94, 118, 17, 107]i 9<>'NSGAIISampler:parent:5[96, 80, 82, 58, 17, 18, 7, 90, 22, 51, 2, 94, 74, 88, 92, 15, 19, 5, 99, 64]i 9<>'NSGAIISampler:parent:4[39, 67, 45, 80, 58, 5, 17, 18, 73, 7, 2, 74, 51, 15, 72, 19, 22, 64, 77, 60]h 9<>%NSGAIISampler:parent:3[39, 6, 45, 58, 18, 23, 17, 57, 7, 22, 2, 5, 15, 60, 28, 19, 41, 46, 51, 59]g 9<>#NSGAIISampler:parent:2[6, 39, 19, 18, 26, 17, 22, 7, 33, 37, 2, 15, 21, 30, 23, 28, 20, 5, 36, 9]c 9<>NSGAIISampler:parent:1[1, 2, 3, 5, 6, 7, 9, 10, 11, 12, 13, 15, 16, 17, 18, 19, 20, 14, 8, 4] [|<0E>t <0A> l <0C> d <0B> \
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T <09> L<08>D<07><<06>,<05> x<03>M<02> <01><00>[<00>= ;<3B>{NSGAIISampler:parent:61[1184, 1142, 1188, 1204, 1212, 923, 1208, 1106, 1213, 1219, 1115, 1181, 1164, 1203, 1152, 1165, 1185, 1103, 1220, 1215]<5D>< ;<3B>{NSGAIISampler:parent:60[1142, 1184, 1169, 1188, 1153, 1152, 1115, 923, 1181, 1106, 1162, 1183, 1148, 1194, 1151, 1165, 1147, 1164, 1103, 1185]<5D>; ;<3B>{NSGAIISampler:parent:59[1142, 1124, 1146, 1169, 923, 1153, 1181, 1103, 1132, 1159, 1151, 1164, 1165, 1115, 1162, 1148, 1147, 1152, 1126, 1106]<5D>: ;<3B>{NSGAIISampler:parent:58[1124, 1142, 1137, 1146, 1148, 1132, 1106, 1151, 1098, 1161, 1152, 1153, 1115, 1159, 1126, 1125, 1147, 1140, 1103, 923]<5D>9 ;<3B>yNSGAIISampler:parent:57[1120, 1124, 1113, 1137, 1098, 1074, 1119, 1132, 1106, 986, 1115, 923, 1134, 1133, 1125, 1103, 1123, 1140, 1122, 1126]<5D>8 ;<3B>yNSGAIISampler:parent:56[1082, 1120, 1113, 1115, 1098, 1097, 1107, 1069, 1119, 986, 1074, 1089, 1111, 1106, 1088, 923, 1114, 1044, 1103, 1117]<5D>7 ;<3B>wNSGAIISampler:parent:55[1068, 1082, 1064, 1087, 1008, 1069, 984, 1088, 1097, 923, 1099, 1060, 1098, 1044, 1074, 986, 1089, 1091, 1083, 1095]<5D>6 ;<3B>wNSGAIISampler:parent:54[1045, 1068, 1052, 1064, 1060, 923, 1008, 984, 1043, 1014, 986, 1062, 1066, 1044, 1079, 1069, 1063, 1039, 1074, 1081]<5D>5 ;<3B>oNSGAIISampler:parent:53[1045, 1023, 1052, 1010, 923, 1008, 984, 1043, 1014, 1049, 1060, 992, 1039, 986, 1044, 996, 1057, 1040, 982, 976]<5D> 4 ;<3B>iNSGAIISampler:parent:52[482, 1009, 1023, 1010, 1041, 1014, 984, 986, 992, 990, 1040, 1038, 923, 926, 1039, 996, 1012, 982, 1008, 976]<5D> 3 ;<3B>eNSGAIISampler:parent:51[482, 974, 1009, 982, 984, 1008, 1020, 986, 992, 926, 1005, 923, 996, 976, 1014, 990, 1004, 995, 1012, 1010]<5D>2 ;<3B>UNSGAIISampler:parent:50[482, 974, 942, 982, 900, 995, 977, 988, 984, 993, 926, 923, 957, 964, 992, 990, 998, 996, 986, 976]<5D>1 ;<3B>UNSGAIISampler:parent:49[482, 942, 974, 902, 946, 916, 923, 969, 900, 977, 976, 961, 957, 964, 963, 968, 767, 926, 915, 973]<5D>0 ;<3B>UNSGAIISampler:parent:48[482, 922, 942, 916, 902, 946, 900, 923, 955, 937, 929, 904, 961, 957, 926, 767, 915, 889, 954, 882]<5D>/ ;<3B>UNSGAIISampler:parent:47[482, 894, 922, 767, 902, 926, 882, 900, 928, 923, 896, 929, 915, 875, 937, 889, 916, 904, 927, 890]<5D>. ;<3B>UNSGAIISampler:parent:46[482, 894, 864, 896, 890, 900, 902, 916, 767, 823, 912, 882, 921, 904, 889, 915, 910, 875, 845, 887]<5D>- ;<3B>UNSGAIISampler:parent:45[482, 864, 894, 900, 875, 868, 890, 887, 767, 859, 882, 896, 867, 823, 845, 884, 889, 895, 849, 858]<5D>, ;<3B>UNSGAIISampler:parent:44[482, 832, 864, 779, 845, 858, 818, 868, 826, 877, 863, 855, 851, 859, 867, 876, 849, 767, 875, 823]<5D>+ ;<3B>UNSGAIISampler:parent:43[482, 832, 802, 818, 855, 767, 773, 849, 859, 845, 851, 779, 856, 823, 858, 826, 742, 821, 825, 830]<5D>* ;<3B>UNSGAIISampler:parent:42[482, 802, 832, 821, 818, 575, 767, 823, 772, 773, 742, 779, 781, 812, 825, 820, 831, 838, 830, 826]<5D>) ;<3B>UNSGAIISampler:parent:41[482, 791, 802, 817, 767, 779, 772, 773, 798, 760, 575, 818, 820, 729, 812, 781, 784, 742, 814, 821]<5D>( ;<3B>UNSGAIISampler:parent:40[482, 776, 791, 798, 790, 784, 729, 742, 772, 773, 760, 779, 665, 575, 781, 719, 794, 648, 759, 767]<5D>' ;<3B>UNSGAIISampler:parent:39[482, 709, 776, 742, 757, 575, 708, 648, 773, 760, 665, 779, 767, 651, 725, 759, 719, 729, 781, 772]<5D>& ;<3B>UNSGAIISampler:parent:38[482, 709, 683, 708, 575, 722, 759, 760, 735, 638, 742, 277, 749, 648, 729, 651, 719, 725, 665, 757]<5D>% ;<3B>UNSGAIISampler:parent:37[482, 709, 683, 428, 708, 665, 638, 722, 648, 277, 735, 575, 719, 651, 728, 725, 707, 724, 711, 729]<5D>$ ;<3B>UNSGAIISampler:parent:36[482, 683, 709, 665, 575, 638, 707, 702, 428, 610, 277, 704, 711, 718, 719, 651, 673, 648, 708, 713]<5D># ;<3B>UNSGAIISampler:parent:35[482, 677, 683, 660, 673, 638, 610, 575, 651, 428, 699, 277, 687, 655, 665, 648, 697, 659, 684, 688]<5D>" ;<3B>UNSGAIISampler:parent:34[482, 654, 677, 660, 673, 655, 638, 565, 277, 428, 679, 663, 665, 575, 610, 651, 637, 659, 622, 648]<5D>! ;<3B>UNSGAIISampler:parent:33[482, 619, 654, 655, 610, 638, 660, 659, 565, 648, 277, 428, 588, 575, 622, 651, 637, 652, 643, 649] 7<00><0F>p(<0E><0E>P <0A> x 0
<EFBFBD>
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 <09> <09> @<08><08>h <07><07>H<06>p(<05><05>P<04>x0<03><03>X<02><02>8<01><01>`<00><00>E<>M AAhCOMPLETE2025-11-27 13:34:29.9975462025-11-27 13:34:30.089973E<EFBFBD>L AAgCOMPLETE2025-11-27 13:34:29.8898852025-11-27 13:34:29.984546E<EFBFBD>K AAfCOMPLETE2025-11-27 13:34:29.7767622025-11-27 13:34:29.876116E<EFBFBD>J AAeCOMPLETE2025-11-27 13:34:29.6728082025-11-27 13:34:29.766057E<EFBFBD>I AAdCOMPLETE2025-11-27 13:34:29.5741862025-11-27 13:34:29.662107E<EFBFBD>H AAcCOMPLETE2025-11-27 13:34:29.4735142025-11-27 13:34:29.561971E<EFBFBD>G AAbCOMPLETE2025-11-27 13:34:29.3548082025-11-27 13:34:29.461004E<EFBFBD>F AAaCOMPLETE2025-11-27 13:34:29.2314702025-11-27 13:34:29.338797E<EFBFBD>E AA`COMPLETE2025-11-27 13:34:29.1143752025-11-27 13:34:29.218967E<EFBFBD>D AA_COMPLETE2025-11-27 13:34:28.9983112025-11-27 13:34:29.102374E<EFBFBD>C AA^COMPLETE2025-11-27 13:34:28.8881092025-11-27 13:34:28.985313E<EFBFBD>B AA]COMPLETE2025-11-27 13:34:28.7800312025-11-27 13:34:28.873929E<EFBFBD>A AA\COMPLETE2025-11-27 13:34:28.6728502025-11-27 13:34:28.770525E<EFBFBD>@ AA[COMPLETE2025-11-27 13:34:28.5416052025-11-27 13:34:28.658581E<EFBFBD>? AAZCOMPLETE2025-11-27 13:34:28.4383802025-11-27 13:34:28.530640E<EFBFBD>> AAYCOMPLETE2025-11-27 13:34:28.3239752025-11-27 13:34:28.426380E<EFBFBD>= AAXCOMPLETE2025-11-27 13:34:28.2089072025-11-27 13:34:28.312462E<EFBFBD>< AAWCOMPLETE2025-11-27 13:34:28.0956212025-11-27 13:34:28.197908E<EFBFBD>; AAVCOMPLETE2025-11-27 13:34:27.9831862025-11-27 13:34:28.084611E<EFBFBD>: AAUCOMPLETE2025-11-27 13:34:27.8750402025-11-27 13:34:27.971679E<EFBFBD>9 AATCOMPLETE2025-11-27 13:34:27.7569552025-11-27 13:34:27.862528E<EFBFBD>8 AASCOMPLETE2025-11-27 13:34:27.6435742025-11-27 13:34:27.743446E<EFBFBD>7 AARCOMPLETE2025-11-27 13:34:27.5341632025-11-27 13:34:27.633568E<EFBFBD>6 AAQCOMPLETE2025-11-27 13:34:27.4276132025-11-27 13:34:27.521319E<EFBFBD>5 AAPCOMPLETE2025-11-27 13:34:27.3118172025-11-27 13:34:27.416612E<EFBFBD>4 AAOCOMPLETE2025-11-27 13:34:27.1983462025-11-27 13:34:27.301757E<EFBFBD>3 AANCOMPLETE2025-11-27 13:34:27.0906962025-11-27 13:34:27.187340E<EFBFBD>2 AAMCOMPLETE2025-11-27 13:34:26.9885102025-11-27 13:34:27.080070E<EFBFBD>1 AALCOMPLETE2025-11-27 13:34:26.8780692025-11-27 13:34:26.978905E<EFBFBD>0 AAKCOMPLETE2025-11-27 13:34:26.7695762025-11-27 13:34:26.867069E<EFBFBD>/ AAJCOMPLETE2025-11-27 13:34:26.6643982025-11-27 13:34:26.759404E<EFBFBD>. AAICOMPLETE2025-11-27 13:34:26.5581402025-11-27 13:34:26.652280E<EFBFBD>- AAHCOMPLETE2025-11-27 13:34:26.4418782025-11-27 13:34:26.544875E<EFBFBD>, AAGCOMPLETE2025-11-27 13:34:26.3018222025-11-27 13:34:26.429873E<EFBFBD>+ AAFCOMPLETE2025-11-27 13:34:26.1528212025-11-27 13:34:26.286171E<EFBFBD>* AAECOMPLETE2025-11-27 13:34:25.9923922025-11-27 13:34:26.136117E<EFBFBD>) AADCOMPLETE2025-11-27 13:34:25.8497102025-11-27 13:34:25.971236E<EFBFBD>( AACCOMPLETE2025-11-27 13:34:25.6870182025-11-27 13:34:25.834688E<EFBFBD>' AABCOMPLETE2025-11-27 13:34:25.5500162025-11-27 13:34:25.674863E<EFBFBD>& AAACOMPLETE2025-11-27 13:34:25.4117952025-11-27 13:34:25.533304E<EFBFBD>% AA@COMPLETE2025-11-27 13:34:25.2912422025-11-27 13:34:25.398794E<EFBFBD>$ AA?COMPLETE2025-11-27 13:34:25.1610062025-11-27 13:34:25.274456E<EFBFBD># AA>COMPLETE2025-11-27 13:34:25.0389232025-11-27 13:34:25.146614E<EFBFBD>" AA=COMPLETE2025-11-27 13:34:24.8971232025-11-27 13:34:25.022577E<EFBFBD>! AA<COMPLETE2025-11-27 13:34:24.7665232025-11-27 13:34:24.882150E<EFBFBD>  AA;COMPLETE2025-11-27 13:34:24.6355432025-11-27 13:34:24.748839E<EFBFBD> AA:COMPLETE2025-11-27 13:34:24.5128612025-11-27 13:34:24.622427E<EFBFBD> AA9COMPLETE2025-11-27 13:34:24.3863842025-11-27 13:34:24.499860E<EFBFBD> AA8COMPLETE2025-11-27 13:34:24.2669912025-11-27 13:34:24.374172E<EFBFBD> AA7COMPLETE2025-11-27 13:34:24.1491482025-11-27 13:34:24.255304E<EFBFBD> AA6COMPLETE2025-11-27 13:34:24.0239352025-11-27 13:34:24.137485E<EFBFBD> AA5COMPLETE2025-11-27 13:34:23.8963952025-11-27 13:34:24.006931E<EFBFBD> AA4COMPLETE2025-11-27 13:34:23.7517162025-11-27 13:34:23.881882E<EFBFBD> AA3COMPLETE2025-11-27 13:34:23.6163552025-11-27 13:34:23.736716E<EFBFBD> AA2COMPLETE2025-11-27 13:34:23.4709472025-11-27 13:34:23.601350
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T<02><02>wV5<01><01><01><01>oN- =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =<02>NSGAIISampler:generation<02> =NSGAIISampler:generation =~NSGAIISampler:generation~ =<02>NSGAIISampler:generation<02> =}NSGAIISampler:generation} =|NSGAIISampler:generation| ={NSGAIISampler:generation{ =zNSGAIISampler:generationz =yNSGAIISampler:generationy =xNSGAIISampler:generationx =wNSGAIISampler:generationw =vNSGAIISampler:generationv =uNSGAIISampler:generationu =tNSGAIISampler:generationt =sNSGAIISampler:generations =rNSGAIISampler:generationr =qNSGAIISampler:generationq =pNSGAIISampler:generationp
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mass0.1247020320170308"<22>%1
stiffness14246.378645308572*<2A>$/1 inference_time_ms11.522054672241211<1B>#- neural_predictedtrue<13>" feasibletrue*<2A>!-3 max_displacement0.06748183212682934<1E> 3 mass0.12112044468003588"<22>1 stiffness14818.803350219372*<2A>/1inference_time_ms14.075994491577148<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.16110955251673992<1E>3mass0.09645714829129376!<21>/stiffness6206.956598033478*<2A>/1inference_time_ms13.672828674316406<1B>-neural_predictedtrue<13>feasibletrue+<2B>-5max_displacement0.055656219062667406<1D>1mass0.1380329966807342!<21>/stiffness17967.44401329215*<2A>/1inference_time_ms13.278961181640625<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.05972934940497185<1E>3mass0.13600013488328902"<22> 1stiffness16742.188052642014*<2A> /1inference_time_ms13.750076293945312<1B> -neural_predictedtrue<13>
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feasiblestiffness<10>-neural_predicted-max_displacement mass/inference_time_msfeasiblestiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10>stiffness<10>-neural_predicted<10>-max_displacement<10> mass<10>/inference_time_ms<10>feasible<10> stiffness<10>- neural_predicted<10>- max_displacement<10>  mass<10>/ inference_time_ms<10> feasible<10> stiffness<10>- neural_predicted<10>- max_displacement<10>  mass<10>/ inference_time_ms<10> feasible<10> stiffness<10>- neural_predicted<10>- max_displacement<10>  mass<10>/ inference_time_ms<10> feasible<10>
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<EFBFBD><+<02><02><02><02><02><02>oVD3 <01><01><01><01><01><01>w-Hmax_displacement Hmass/Hinference_time_msHfeasibleGstiffness-Gneural_predicted-Gmax_displacement Gmass/Ginference_time_msGfeasibleFstiffness -Fneural_predicted-Fmax_displacement Fmass/Finference_time_msFfeasibleEstiffness-Eneural_predicted -Emax_displacement Emass/Einference_time_ms Efeasible
Dstiffness/@inference_time_ms<17>-@neural_predicted<17>@feasible<17>-@max_displacement<17> @mass<17>@stiffness<17>/?inference_time_ms<17>-?neural_predicted<17>?feasible<17>-?max_displacement<17> ?mass<17>?stiffness<17>/>inference_time_ms<17>->neural_predicted<17>>feasible<17>->max_displacement<17> >mass<17>>stiffness<17>/=inference_time_ms<17>-=neural_predicted<17>=feasible<17>-=max_displacement<17> =mass<17>=stiffness<17>/<inference_time_ms<17>-<neural_predicted<17><feasible<17>-<max_displacement<17> <mass<17><stiffness<17>/;inference_time_ms<17>-;neural_predicted<17>;feasible<17>-;max_displacement<17> ;mass<17>;stiffness<17>/:inference_time_ms<17>-:neural_predicted<17>:feasible<17>-:max_displacement<17> :mass<17>:stiffness<17>/9inference_time_ms<17>-9neural_predicted<17>9feasible<17>-9max_displacement<17> 9mass<17>9stiffness<17>/8inference_time_ms<17>-8neural_predicted<17>8feasible<17>-8max_displacement<17> 8mass<17>8stiffness<17>/7inference_time_ms<17>-7neural_predicted<17>7feasible<17>-7max_displacement<17> 7mass<17>7stiffness<17>/6inference_time_ms<17>-6neural_predicted<17>6feasible<17>-6max_displacement<17> 6mass<17>6stiffness<17>/5inference_time_ms<17>-5neural_predicted<17>5stiffness<17>-5max_displacement<17> 5mass<17>5feasible<17>4stiffness<17>-4neural_predicted<17>-4max_displacement<17> 4mass<17>/4inference_time_ms<17>4feasible<17>3stiffness<17>-3neural_predicted<17>-3max_displacement<17> 3mass<17>/3inference_time_ms<17>3feasible<17>2stiffness<17>-2neural_predicted<17>-2max_displacement<17> 2mass<17>/2inference_time_ms<17>2feasible<17>-Dneural_predictedH-Dmax_displacement Dmass/Dinference_time_msDfeasibleCstiffness<17>-Cneural_predicted<17>-Cmax_displacement<17> Cmass<17>/Cinference_time_msCfeasible<17>Bstiffness<17>-Bneural_predicted<17>-Bmax_displacement<17> Bmass<17>/Binference_time_ms<17>Bfeasible<17>Astiffness<17>-Aneural_predicted<17>-Amax_displacement<17> Amass<17>/Ainference_time_ms<17>Afeasible<17>1stiffness<17>-1neural_predicted<17>-1max_displacement<17> 1mass<17>/1inference_time_ms<17>1feasible<17>0stiffness<17>-0neural_predicted<17>-0max_displacement<17> 0mass<17>/0inference_time_ms<17>0feasible<17>/stiffness<17>-/neural_predicted<17>-/max_displacement<17> /mass<17>//inference_time_ms<17>/feasible<17>.stiffness}-.neural_predicted<17>-.max_displacement .mass~/.inference_time_ms<17>.feasible<17>-stiffnessw--neural_predicted{--max_displacementy -massx/-inference_time_ms|-feasiblez,stiffnessq-,neural_predictedu-,max_displacements ,massr/,inference_time_msv,feasiblet+stiffnessk-+neural_predictedo-+max_displacementm +massl/+inference_time_msp+feasiblen*stiffnesse-*neural_predictedi m<00><0F><0F><0F>y[.
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Efeasibletrue*<2A> -3Emax_displacement0.05506144723790261<1E>3Emass0.13905580628834133!<21>/Estiffness18161.52771428846*<2A>/1Dinference_time_ms12.523174285888672<1B>-Dneural_predictedtrue<13>Dfeasibletrue*<2A>-3Dmax_displacement0.06470150929737276<1E>3Dmass0.13486108366704117"<22>1Dstiffness15455.589998742202*<2A>/1Cinference_time_ms16.757726669311523<1B>-Cneural_predictedtrue<13>~Cfeasibletrue*<2A>}-3Cmax_displacement0.06172368138662397<1E>|3Cmass0.13591726740354526"<22>{1Cstiffness16201.237151365185*<2A>z/1Binference_time_ms13.058900833129883<1B>y-Bneural_predictedtrue<13>xBfeasibletrue*<2A>w-3Bmax_displacement0.04728088139447803<1E>v3Bmass0.15972082872756316!<21>u/Bstiffness21150.19793427097)<29>t//Ainference_time_ms16.62445068359375<1B>s-Aneural_predictedtrue<13>rAfeasibletrue*<2A>q-3Amax_displacement0.04804268986078376<1E>p3Amass0.15635550381300398"<22>o1Astiffness20814.821212087856*<2A>n/1@inference_time_ms14.512062072753906<1B>m-@neural_predictedtrue<13>l@feasibletrue)<29>k-1@max_displacement0.0898436448091588<1E>j3@mass0.11250744001125818"<22>i1@stiffness11130.447814357354*<2A>h/1?inference_time_ms14.399528503417969<1B>g-?neural_predictedtrue<13>f?feasibletrue*<2A>e-3?max_displacement0.16110955251673992<1E>d3?mass0.09645714829129376!<21>c/?stiffness6206.956598033478*<2A>b/1>inference_time_ms14.252662658691406<1B>a->neural_predictedtrue<13>`>feasibletrue+<2B>_-5>max_displacement0.051784075225959444<1E>^3>mass0.14689319052864686"<22>]1>stiffness19310.956034968418*<2A>\/1=inference_time_ms20.525455474853516<1B>[-=neural_predictedtrue<13>Z=feasibletrue+<2B>Y-5=max_displacement0.047484565865977525<1D>X1=mass0.1598991125096162"<22>W1=stiffness21059.474415801607*<2A>V/1<inference_time_ms11.000394821166992<1B>U-<neural_predictedtrue<13>T<feasibletrue*<2A>S-3<max_displacement0.06250985982305972<1E>R3<mass0.12781644452811258"<22>Q1<stiffness15997.476283431093*<2A>P/1;inference_time_ms14.267444610595703<1B>O-;neural_predictedtrue<13>N;feasibletrue+<2B>M-5;max_displacement0.061453971234222075<1E>L3;mass0.13664540703859798!<21>K/;stiffness16272.34139497118*<2A>J/1:inference_time_ms12.735366821289062<1B>I-:neural_predictedtrue<13>H:feasibletrue*<2A>G-3:max_displacement0.04692453288098225<1E>F3:mass0.16029587824570823!<21>E/:stiffness21310.81416487118*<2A>D/19inference_time_ms14.270305633544922<1B>C-9neural_predictedtrue<13>B9feasibletrue+<2B>A-59max_displacement0.051784075225959444<1E>@39mass0.14689319052864686"<22>?19stiffness19310.956034968418*<2A>>/18inference_time_ms13.518810272216797<1B>=-8neural_predictedtrue<13><8feasibletrue*<2A>;-38max_displacement0.06791756373523812<1D>:18mass0.1207303269503399"<22>918stiffness14723.731903845712*<2A>8/17inference_time_ms15.226364135742188<1B>7-7neural_predictedtrue<13>67feasibletrue+<2B>5-57max_displacement0.061453971234222075<1E>437mass0.13664540703859798!<21>3/7stiffness16272.34139497118*<2A>2/16inference_time_ms17.806053161621094<1B>1-6neural_predictedtrue<13>06feasibletrue*<2A>/-36max_displacement0.04722108843780554<1D>.16mass0.1604713432333169!<21>-/6stiffness21176.97903802219 Lz<0E>n <0A> b <0C> V <0B> J
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3pmass0.16029587824570823!<21> /pstiffness21310.81416487118*<2A>/1oinference_time_ms12.541055679321289<1B>-oneural_predictedtrue<13>ofeasibletrue*<2A>-3omax_displacement0.04697719379145715<1E>3omass0.16025502228143998"<22>1ostiffness21286.924979794152*<2A>/1ninference_time_ms12.833595275878906<1B>-nneural_predictedtrue<13>nfeasibletrue+<2B>-5nmax_displacement0.049340486863403164<1E>~3nmass0.15292543712784734!<21>}/nstiffness20267.33142638931*<2A>|/1minference_time_ms11.043071746826172<1B>{-mneural_predictedtrue<13>zmfeasibletrue*<2A>y-3mmax_displacement0.05907289034617935<1C>x/mmass0.136835326901241 <20>w-mstiffness16928.2388950294*<2A>v/1linference_time_ms10.518789291381836<1B>u-lneural_predictedtrue
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inference_time_ms10.525703430175781<1B>)-
neural_predictedtrue<13>(
feasibletrue*<2A>'-3
max_displacement0.08702542654741274<1D>&1
mass0.1131580705248394"<22>%1
stiffness11490.894554308046)<29>$// inference_time_ms12.99595832824707<1B>#- neural_predictedtrue<13>" feasibletrue*<2A>!-3 max_displacement0.05826602382627877<1E> 3 mass0.13444509185451187!<21>/ stiffness17162.66074687915*<2A>/1inference_time_ms10.798215866088867<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.06722610284477144<1E>3mass0.12118696944296883"<22>1stiffness14875.174339780662*<2A>/1inference_time_ms13.079404830932617<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.04692453288098225<1E>3mass0.16029587824570823!<21>/stiffness21310.81416487118*<2A>/1inference_time_ms11.507272720336914<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.07576461319651796<1E>3mass0.12716250187587533"<22> 1stiffness13198.773910535303)<29> //inference_time_ms12.00413703918457<1B> -neural_predictedtrue<13>
feasibletrue*<2A> -3max_displacement0.07266810788991301<1D>1mass0.1283149854091886!<21>/stiffness13761.19495934762*<2A>/1inference_time_ms10.439157485961914<1B>-neural_predictedtrue<13>feasibletrue*<2A>-3max_displacement0.12995861382991303<1E>3mass0.10182868448276255!<21>/stiffness7694.757357975347*<2A>/1inference_time_ms14.274120330810547<1B>-neural_predictedtrue<13>~feasibletrue*<2A>}-3max_displacement0.13616161077908293<1E>|3mass0.10059037726730963"<22>{1stiffness7344.2139401718905)<29>z//inference_time_ms10.68425178527832<1B>y-neural_predictedtrue<13>xfeasibletrue*<2A>w-3max_displacement0.06932996083963941<1E>v3mass0.11973987332837409"<22>u1stiffness14423.778520703418%<25>t/'inference_time_ms12.5732421875<1B>s-neural_predictedtrue<13>rfeasibletrue*<2A>q-3max_displacement0.04692453288098225<1E>p3mass0.16029587824570823!<21>o/stiffness21310.81416487118*<2A>n/1inference_time_ms13.513803482055664<1B>m-neural_predictedtrue<13>lfeasibletrue*<2A>k-3max_displacement0.11411231799783106<1E>j3mass0.10856606454231231!<21>i/stiffness8763.295825951122*<2A>h/1<04>inference_time_ms11.781930923461914<1B>g-<04>neural_predictedtrue<13>f<04>feasibletrue*<2A>e-3<04>max_displacement0.04815657087281236<1D>d1<04>mass0.1559750570646387"<22>c1<04>stiffness20765.598170208745)<29>b//<04>inference_time_ms9.617090225219727
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feasiblestiffness<1C>-neural_predicted-max_displacement mass/inference_time_msfeasiblestiffness<1C>/inference_time_ms<1C>-neural_predicted<1C>feasible<1C>-max_displacement<1C> mass<1C>stiffness<1C>/inference_time_ms<1C>-neural_predicted<1C>feasible<1C>-max_displacement<1C> mass<1C>stiffness<1C>/inference_time_ms<1C>-neural_predicted<1C>feasible<1C>-max_displacement<1C> mass<1C>stiffness<1C>/inference_time_ms<1C>-neural_predicted<1C>feasible<1C>-max_displacement<1C> mass<1C>stiffness<1C>/inference_time_ms<1C>-neural_predicted<1C>feasible<1C>-max_displacement<1C> mass<1C>stiffness<1C>/inference_time_ms<1C>-neural_predicted<1C>feasible<1C>-max_displacement<1C> mass<1C>stiffness<1C>/inference_time_ms<1C>-neural_predicted<1C>feasible<1C>-max_displacement<1C> mass<1C>stiffness<1C>/ inference_time_ms<1C>- neural_predicted<1C> feasible<1C>- max_displacement<1C>  mass<1C> stiffness<1C>/ inference_time_ms<1C>- neural_predicted<1C> feasible<1C>- max_displacement<1C>  mass<1C> stiffness<1C>/ inference_time_ms<1C>- neural_predicted<1C> feasible<1C>- max_displacement<1C>  mass<1C> stiffness<1C>/
inference_time_ms<1C>-
neural_predicted<1C>
feasible<1C>-
max_displacement<1C> 
mass<1C>
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