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Atomizer/studies/bracket_displacement_maximizing/model/Bracket.prt

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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
UGS::VIEWj UGS::LAYOUTUGS::Assy::ReferenceSetUGS::SC_SECTION UGS::SKETCH!+UGS::Display::SimpleHighEndDisplayMaterial UGS::LIGHT UGS::DAXIS
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
UGS::DIRR UGS::XFORM6 UGS::CS2 UGS::Leader::Plain UGS::DISPLAYFUGS::Part::Unit::Root+UGS::Attr::DAttributeDescriptionDepository
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
<EFBFBD>0<00>R8-s_P<00>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
<02><>M@0p*<2A><>}L/<2F>u%F
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
<EFBFBD>0<00>R8-s_P<00>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
=q0w<30><77><EFBFBD>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
=rPnP4<01><01><>!A<00>WW<00>fXScene Right Top<02>>`b<><62>O<EFBFBD><4F><EFBFBD>0<><30>+S<>;w0<77><30><EFBFBD>S<EFBFBD><53><EFBFBD>0y<>E<EFBFBD>40<><30><EFBFBD><EFBFBD><EFBFBD><EFBFBD>k0<6B><30>V<56>(zMXPnP4<01><01><> A<00>WW<00>fX Scene Front<02>>`b<><62>MPM@0<>>F<><1E>MP0<>6F<36><1E>PnP4<01><01><>!A<00>WW<00>fXScene Left Bottom<02>>`b<><62>0\(<28><><01><><EFBFBD>+S<>;w<><77><EFBFBD><EFBFBD>S<EFBFBD><53><EFBFBD>0y<>E<EFBFBD>2<00><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>k<EFBFBD><6B><EFBFBD>V<56>(z<>XPnP4<01><01><>A<00>WW<00>fXScene Bottom<02>>`b<><62>Oٙ<4F><01><00>x8<78><38>
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
=q<00>w<EFBFBD><77><EFBFBD>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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<EFBFBD>E<><03><><EFBFBD>CP<43><50><EFBFBD><EFBFBD><EFBFBD>0!<21>TD-/<2F>u%F
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
<EFBFBD>0<00>R8-scP<00>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
<02><><EFBFBD>CP<43><50><EFBFBD><EFBFBD><EFBFBD>0n|<<3C>@<40>02<30>|3!<21>/<2F>u%F
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
<EFBFBD>0<00>R8-scP<00>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
<EFBFBD>0<00>R8-saP<00>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
<EFBFBD>0<00>R8-saP<00>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
<02><>0z<30>4<EFBFBD>5Y<35>0n|<<3C>@<40>02<30>|3!<21>/<2F>u%F
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
<EFBFBD>0<00>R8-saP<00>
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
Tool ID IJKLMNA<02>UUUV<02>eU<65>VBend Radius  Bend Angle Neutral Factor <02>eU<65>VMaterial Thickness Physical Material Sheet Metal Material <02>fU<66><55>Interior Cutout - Count Total Cut Length  Minimum X Exterior Cut Length  Minimum Y Interior Cut Length <02>fe<66><65>Bend Radius Bend Sequence ID  Bend Name Outside Bend Angle Inside Bend Angle Bend Direction Neutral Factor <02>UU<55>VJoggle Runout Joggle Depth <02>UU<55>VHole Diameter Cutout Diameter <02>fe<66><65><02>UU<55>V<02>fU<66><55><02>UU<55>V<02>eU<65>V<02>eU<65>V<02>fU<66>VTHRUTHRUTHRUTHRU<02>fU<66>V6H6H6H6H6H<02>fU<66>V6g6g6g6g6gP40f<30>P40f<30><02>fU<66>V`<60><><EFBFBD><EFBFBD>a<EFBFBD>b<EFBFBD><62><EFBFBD><EFBFBD>c<EFBFBD>d<EFBFBD><02>fU<66><55>A<><41>B<EFBFBD>C<EFBFBD>D<EFBFBD><44><EFBFBD><EFBFBD>E<EFBFBD>F<EFBFBD><02>fU<66>Vo<><6F><EFBFBD><EFBFBD>p<EFBFBD>q<EFBFBD><71><EFBFBD><EFBFBD>r<EFBFBD>s<EFBFBD><02>UU<55>Vl<><6C><EFBFBD><EFBFBD><EFBFBD><EFBFBD>m<EFBFBD><6D><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>Vi<><69><EFBFBD><EFBFBD><EFBFBD><EFBFBD>j<EFBFBD><6A><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>eU<65>Vd<><64><EFBFBD><EFBFBD>e<EFBFBD>f<EFBFBD><66><EFBFBD><EFBFBD><EFBFBD><EFBFBD>g<EFBFBD><02>UU<55>Va<><61><EFBFBD><EFBFBD><EFBFBD><EFBFBD>b<EFBFBD><62><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>V^<5E><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>_<EFBFBD><5F><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>eU<65>VA<><41><EFBFBD><EFBFBD>B<EFBFBD>C<EFBFBD><43><EFBFBD><EFBFBD><EFBFBD><EFBFBD>D<EFBFBD>  <02>fe<66><65>st<73>u<EFBFBD>v<EFBFBD>w<EFBFBD><77>x<EFBFBD>y<EFBFBD>z<EFBFBD><02>eU<65>Vo<><6F><EFBFBD><EFBFBD><EFBFBD><EFBFBD>p<EFBFBD><70><EFBFBD><EFBFBD><EFBFBD><EFBFBD>q<EFBFBD><02>UU<55>Vl<><6C><EFBFBD><EFBFBD><EFBFBD><EFBFBD>m<EFBFBD><6D><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UUUVj<><6A><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>eU<65>VA<><41><EFBFBD><EFBFBD><EFBFBD><EFBFBD>B<EFBFBD><42><EFBFBD><EFBFBD><EFBFBD><EFBFBD>C<EFBFBD><02>eU<65>Vz<><7A><EFBFBD><EFBFBD>{<7B>|<7C><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>}<7D><02>UU<55>Vw<><77><EFBFBD><EFBFBD><EFBFBD><EFBFBD>x<EFBFBD><78><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>Vt<><74><EFBFBD><EFBFBD><EFBFBD><EFBFBD>u<EFBFBD><75><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>fe<66><65>A<><41>B<EFBFBD>C<EFBFBD>D<EFBFBD><44>E<EFBFBD>F<EFBFBD>G<EFBFBD>

refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
 <02>ff<66><66><11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UUUV<11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>V<11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>V<><7F><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>V|<7C><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>}<7D><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>Vy<><79><EFBFBD><EFBFBD><EFBFBD><EFBFBD>z<EFBFBD><7A><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>eU<65>Vt<><74><EFBFBD><EFBFBD>u<EFBFBD>v<EFBFBD><76><EFBFBD><EFBFBD><EFBFBD><EFBFBD>w<EFBFBD><02>fU<66><55>A<><41>B<EFBFBD>C<EFBFBD>D<EFBFBD><44><EFBFBD><EFBFBD>E<EFBFBD>F<EFBFBD><02>eU<65>V<11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>V<11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>V<11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>fU<66>V<11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>V<11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><02>UU<55>V<11><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>90+% CBORE<o> 2- DEEP1 CSINK<o> 0X/ CBORE<o>  X  -  DEEP CSINK<o>   CSINK<o> ,X+ CSINK<o> .X -Other End- X* - ( -  DEEP<o>  Minor:<o>  X 
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
 Major:<o> Tap Drill:<o> )Shaft Size:<o> ( X -  DEEP-7 -6-2x CSINK<o> .X -Other End- CSINK<o> ,X+ X -  DEEP-5<o>  CSINK<o> 4X+X3 CSINK<o> , X 
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
**PARASOLID !"#$%&'()*+,-./:;<=>?@[\]^_`{|}~0123456789**************************
**PART1;
MC=^_;
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
DATE=21-nov-2025;
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
**PART2;
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
SCH=SCH_3700213_36001;
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
USFLD_SIZE=0;
**PART3;
**END_OF_HEADER*****************************************************************
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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<00> <00> <00> <00><00><00><00><00><00><00><00><00><00><00><00><00><00><00><00><00><00><00> <00>!<00>"<00>#<00>$%%WorldModifier<00><>GlobalVariables<00><>%%ug_objects_for_p44<00>`%%ug_objects_for_p41<00>Whostbasedesign<00><> Host%%World<00><>p63<00><19>p52<00><19>p43<00>[p49<00>bp48<00>i%%ug_objects_for_p50<00>p%%ug_objects_for_p63<00><1B>ug_base_part<00><>%%world_internal<00><>support_angle<00><18>%%globalvariables<00><>tip_thickness<00><18>p50<00>n%%ug_objects_for_p56<00>|%%ug_objects_for_p62<00><1B>bracket_mass<00><1B>%%ug_objects_for_p49<00>mp39<00>X saveClass?<00>& renderSelf<00>Ip60<00><19>p44<00>^%%ug_objects_for_p46<00>ep61<00><19>p56<00>s%%ug_objects_for_p55<00>z%%ug_objects_for_p58<00><1B>%%ug_objects_for_p61<00><1B>GlobalVariablesModifier<00><> %%world<00><>p58<00><19>%renderedChildren<00>G%%ug_objects_for_p40<00>U%%ug_objects_for_p45<00>cp46<00><19>%%ug_objects_for_p54<00>x%%ug_objects_for_p57<00>%%ug_objects_for_p60<00><1B>hostglobalvariables<00><>p38<00>m%%ug_objects_for_p52<00>tp41<00>[p55<00>S%%ug_objects_for_p42<00>Zp45<00>a%%ug_objects_for_p47<00>h%%ug_objects_for_p53<00>vp57<00>}%%ug_objects_for_p59<00><1B>BaseDesignModifier<00><>%%ug_objects_for_bracket_mass<00><1B>%%basedesign<00><> basedesign<00><>%%ug_objects_for_p39<00>S%%ug_objects_for_p38<00>Qp42<00>Xsupport_blend_radius<00><18>p47<00>fp51<00><19>p40<00>tp59<00><1B>%%ug_objects_for_p11<00><18>p62<00><19>p53<00><19>p54<00>n%%ug_objects_for_p43<00>]p11<00><18>%%ug_objects_for_p48<00>k%%ug_objects_for_p51<00>rp3z7(Number [degrees]) support_angle: 36.54595394544202; <00><18>3(Number [mm]) tip_thickness: 24.946257551293495; <00><18>(Number [mm]) p3: 10; z+(Number [mm]) p11: support_blend_radius; <00><18>*(Number [mm]) support_blend_radius: 10; <00><18>5(Number [mm^2]) p38: body_property12.surface_area; <00>m/(Number [mm^3]) p39: body_property13.volume; <00>X4(Point [mm]) p40: body_property14.center_of_mass; <00>t+(Number [kg]) p41: body_property15.mass; <00>[,(Number [N]) p42: body_property16.weight; <00>X3(Number [kg/mm^3]) p43: body_property17.density; <00>[@(List [kg-mm]) p44: body_property18.first_moments_of_inertia; <00>^<(List [kg-mm^2]) p45: body_property19.moments_of_inertia; <00>aG(List [kg-mm^2]) p46: body_property20.moments_of_inertia_centroidal; <00><19>H(Number [kg-mm^2]) p47: body_property21.moments_of_inertia_spherical; <00>f=(List [kg-mm^2]) p48: body_property22.products_of_inertia; <00>iH(List [kg-mm^2]) p49: body_property23.products_of_inertia_centroidal; <00>b6(List [mm]) p50: body_property24.radii_of_gyration; <00>nA(List [mm]) p51: body_property25.radii_of_gyration_centroidal; <00><19>B(Number [mm]) p52: body_property26.radii_of_gyration_spherical; <00><19>3(Vector) p53: body_property27.principal_axes_xp; <00><19>3(Vector) p54: body_property28.principal_axes_yp; <00>n3(Vector) p55: body_property29.principal_axes_zp; <00>S;(List [kg-mm^2]) p56: body_property30.principal_moments; <00>s<(Number [mm^2]) p57: body_property31.area_error_estimate; <00>}>(Number [mm^3]) p58: body_property32.volume_error_estimate; <00><19>:(Number [kg]) p59: body_property33.mass_error_estimate; <00><1B>D(Number [mm]) p60: body_property34.radius_for_cog_error_estimate; <00><19>7(List [mm]) p61: body_property35.cog_error_estimate; <00><19>@(List [kg-mm^2]) p62: body_property36.moments_error_estimate; <00><19>J(List [kg-mm^2]) p63: body_property37.principal_moments_error_estimate; <00><19>#(Number [kg]) bracket_mass: p41; <00><1B>/
feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
(Child) root: {
Class; ug_base_part;
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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feat: Add substudy system with live history tracking and workflow fixes Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 21:29:54 -05:00
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<00>Version 9.4 JT DM 10.7.0.1
refactor: Archive experimental LLM features for MVP stability (Phase 1.1) Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
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