Commit Graph

13 Commits

Author SHA1 Message Date
6c30224341 feat(config): AtomizerSpec v2.0 Pydantic models, validators, and tests
Config Layer:
- spec_models.py: Pydantic models for AtomizerSpec v2.0
- spec_validator.py: Semantic validation with detailed error reporting

Extractors:
- custom_extractor_loader.py: Runtime custom extractor loading
- spec_extractor_builder.py: Build extractors from spec definitions

Tools:
- migrate_to_spec_v2.py: CLI tool for batch migration

Tests:
- test_migrator.py: Migration tests
- test_spec_manager.py: SpecManager service tests
- test_spec_api.py: REST API tests
- test_mcp_tools.py: MCP tool tests
- test_e2e_unified_config.py: End-to-end config tests
2026-01-20 13:12:03 -05:00
27e78d3d56 feat(canvas): Custom extractor components, migrator, and MCP spec tools
Canvas Components:
- CustomExtractorNode.tsx: Node for custom Python extractors
- CustomExtractorPanel.tsx: Configuration panel for custom extractors
- ConnectionStatusIndicator.tsx: WebSocket status display
- atomizer-spec.ts: TypeScript types for AtomizerSpec v2.0

Config:
- migrator.py: Legacy config to AtomizerSpec v2.0 migration
- Updated __init__.py exports for config and extractors

MCP Tools:
- spec.ts: MCP tools for spec manipulation
- index.ts: Tool registration updates
2026-01-20 13:11:42 -05:00
73a7b9d9f1 feat: Add dashboard chat integration and MCP server
Major changes:
- Dashboard: WebSocket-based chat with session management
- Dashboard: New chat components (ChatPane, ChatInput, ModeToggle)
- Dashboard: Enhanced UI with parallel coordinates chart
- MCP Server: New atomizer-tools server for Claude integration
- Extractors: Enhanced Zernike OPD extractor
- Reports: Improved report generator

New studies (configs and scripts only):
- M1 Mirror: Cost reduction campaign studies
- Simple Beam, Simple Bracket, UAV Arm studies

Note: Large iteration data (2_iterations/, best_design_archive/)
excluded via .gitignore - kept on local Gitea only.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-13 15:53:55 -05:00
eabcc4c3ca refactor: Major reorganization of optimization_engine module structure
BREAKING CHANGE: Module paths have been reorganized for better maintainability.
Backwards compatibility aliases with deprecation warnings are provided.

New Structure:
- core/           - Optimization runners (runner, intelligent_optimizer, etc.)
- processors/     - Data processing
  - surrogates/   - Neural network surrogates
- nx/             - NX/Nastran integration (solver, updater, session_manager)
- study/          - Study management (creator, wizard, state, reset)
- reporting/      - Reports and analysis (visualizer, report_generator)
- config/         - Configuration management (manager, builder)
- utils/          - Utilities (logger, auto_doc, etc.)
- future/         - Research/experimental code

Migration:
- ~200 import changes across 125 files
- All __init__.py files use lazy loading to avoid circular imports
- Backwards compatibility layer supports old import paths with warnings
- All existing functionality preserved

To migrate existing code:
  OLD: from optimization_engine.nx_solver import NXSolver
  NEW: from optimization_engine.nx.solver import NXSolver

  OLD: from optimization_engine.runner import OptimizationRunner
  NEW: from optimization_engine.core.runner import OptimizationRunner

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-29 12:30:59 -05:00
d19fc39a2a feat: Add OPD method support to Zernike visualization with Standard/OPD toggle
Major improvements to Zernike WFE visualization:

- Add ZernikeDashboardInsight: Unified dashboard with all orientations (40°, 60°, 90°)
  on one page with light theme and executive summary
- Add OPD method toggle: Switch between Standard (Z-only) and OPD (X,Y,Z) methods
  in ZernikeWFEInsight with interactive buttons
- Add lateral displacement maps: Visualize X,Y displacement for each orientation
- Add displacement component views: Toggle between WFE, ΔX, ΔY, ΔZ in relative views
- Add metrics comparison table showing both methods side-by-side

New extractors:
- extract_zernike_figure.py: ZernikeOPDExtractor using BDF geometry interpolation
- extract_zernike_opd.py: Parabola-based OPD with focal length

Key finding: OPD method gives 8-11% higher WFE values than Standard method
(more conservative/accurate for surfaces with lateral displacement under gravity)

Documentation updates:
- SYS_12: Added E22 ZernikeOPD as recommended method
- SYS_16: Added ZernikeDashboard, updated ZernikeWFE with OPD features
- Cheatsheet: Added Zernike method comparison table

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-22 21:03:19 -05:00
274081d977 refactor: Engine updates and NX hooks improvements
optimization_engine:
- Updated nx_solver.py with improvements
- Enhanced solve_simulation.py
- Updated extractors/__init__.py
- Improved NX CAD hooks (expression_manager, feature_manager,
  geometry_query, model_introspection, part_manager)
- Enhanced NX CAE solver_manager hook

Documentation:
- Updated OP_01_CREATE_STUDY.md protocol
- Updated SYS_12_EXTRACTOR_LIBRARY.md

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-20 13:47:21 -05:00
1612991d0d feat: Add Study Insights module (SYS_16) for physics visualizations
Introduces a new plugin architecture for study-specific physics
visualizations, separating "optimizer perspective" (Analysis) from
"engineer perspective" (Insights).

New module: optimization_engine/insights/
- base.py: StudyInsight base class, InsightConfig, InsightResult, registry
- zernike_wfe.py: Mirror WFE with 3D surface and Zernike decomposition
- stress_field.py: Von Mises stress contours with safety factors
- modal_analysis.py: Natural frequencies and mode shapes
- thermal_field.py: Temperature distribution visualization
- design_space.py: Parameter-objective landscape exploration

Features:
- 5 insight types: zernike_wfe, stress_field, modal, thermal, design_space
- CLI: python -m optimization_engine.insights generate <study>
- Standalone HTML generation with Plotly
- Enhanced Zernike viz: Turbo colorscale, smooth shading, 0.5x AMP
- Dashboard API fix: Added include_coefficients param to extract_relative()

Documentation:
- docs/protocols/system/SYS_16_STUDY_INSIGHTS.md
- Updated ATOMIZER_CONTEXT.md (v1.7)
- Updated 01_CHEATSHEET.md with insights section

Tools:
- tools/zernike_html_generator.py: Standalone WFE HTML generator
- tools/analyze_wfe.bat: Double-click to analyze OP2 files

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-20 13:46:28 -05:00
Antoine
d1261d62fd refactor: Major project cleanup and reorganization
## Removed Duplicate Directories
- Deleted old `dashboard/` (replaced by atomizer-dashboard)
- Deleted old `mcp_server/` Python tools (moved model_discovery to optimization_engine)
- Deleted `tests/mcp_server/` (obsolete tests)
- Deleted `launch_dashboard.bat` (old launcher)

## Consolidated Code
- Moved `mcp_server/tools/model_discovery.py` to `optimization_engine/model_discovery/`
- Updated import in `optimization_config_builder.py`
- Deleted stub `extract_mass.py` (use extract_mass_from_bdf instead)
- Deleted unused `intelligent_setup.py` and `hybrid_study_creator.py`
- Archived `result_extractors/` to `archive/deprecated/`

## Documentation Cleanup
- Deleted deprecated `docs/06_PROTOCOLS_DETAILED/` (14 files)
- Archived dated dev docs to `docs/08_ARCHIVE/sessions/`
- Archived old plans to `docs/08_ARCHIVE/plans/`
- Updated `docs/protocols/README.md` with SYS_15

## Skills Consolidation
- Archived redundant study creation skills to `.claude/skills/archive/`
- Kept `core/study-creation-core.md` as canonical

## Housekeeping
- Updated `.gitignore` to prevent `nul` and `_dat_run*.dat`

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-12 11:24:02 -05:00
Antoine
70ac34e3d3 feat: Add E11 Part Mass extractor, document pyNastran mass accuracy issue
New E11 Part Mass Extractor:
- Add nx_journals/extract_part_mass_material.py - NX journal using
  NXOpen.MeasureManager.NewMassProperties() for accurate geometry-based mass
- Add optimization_engine/extractors/extract_part_mass_material.py - Python
  wrapper that reads JSON output from journal
- Add E11 entry to extractors/catalog.json

Documentation Updates:
- SYS_12_EXTRACTOR_LIBRARY.md: Add mass accuracy warning noting pyNastran
  get_mass_breakdown() under-reports ~7% on hex-dominant meshes with
  tet/pyramid fill elements. E11 (geometry .prt) should be preferred over
  E4 (BDF) unless material is overridden at FEM level.
- 01_CHEATSHEET.md: Add mass extraction tip

V14 Config:
- Expand design variable bounds (blank_backface_angle max 4.5°,
  whiffle_triangle_closeness max 80mm, whiffle_min max 60mm)

Testing showed:
- E11 from .prt: 97.66 kg (accurate - matches NX GUI)
- E4 pyNastran get_mass_breakdown(): 90.73 kg (~7% under-reported)

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-11 22:15:36 -05:00
Antoine
0cb2808c44 feat: Add Phase 2 & 3 physics extractors for multi-physics optimization
Phase 2 - Structural Analysis:
- extract_principal_stress: σ1, σ2, σ3 principal stresses from OP2
- extract_strain_energy: Element and total strain energy
- extract_spc_forces: Reaction forces at boundary conditions

Phase 3 - Multi-Physics:
- extract_temperature: Nodal temperatures from thermal OP2 (SOL 153/159)
- extract_temperature_gradient: Thermal gradient approximation
- extract_heat_flux: Element heat flux from thermal analysis
- extract_modal_mass: Modal effective mass from F06 (SOL 103)
- get_first_frequency: Convenience function for first natural frequency

Documentation:
- Updated SYS_12_EXTRACTOR_LIBRARY.md with E12-E18 specifications
- Updated NX_OPEN_AUTOMATION_ROADMAP.md marking Phase 3 complete
- Added test_phase3_extractors.py for validation

All extractors follow consistent API pattern returning Dict with
success, data, and error fields for robust error handling.

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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-06 13:40:14 -05:00
Antoine
8cbdbcad78 feat: Add Protocol 13 adaptive optimization, Plotly charts, and dashboard improvements
## Protocol 13: Adaptive Multi-Objective Optimization
- Iterative FEA + Neural Network surrogate workflow
- Initial FEA sampling, NN training, NN-accelerated search
- FEA validation of top NN predictions, retraining loop
- adaptive_state.json tracks iteration history and best values
- M1 mirror study (V11) with 103 FEA, 3000 NN trials

## Dashboard Visualization Enhancements
- Added Plotly.js interactive charts (parallel coords, Pareto, convergence)
- Lazy loading with React.lazy() for performance
- Code splitting: plotly.js-basic-dist (~1MB vs 3.5MB)
- Chart library toggle (Recharts default, Plotly on-demand)
- ExpandableChart component for full-screen modal views
- ConsoleOutput component for real-time log viewing

## Documentation
- Protocol 13 detailed documentation
- Dashboard visualization guide
- Plotly components README
- Updated run-optimization skill with Mode 5 (adaptive)

## Bug Fixes
- Fixed TypeScript errors in dashboard components
- Fixed Card component to accept ReactNode title
- Removed unused imports across components

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-04 07:41:54 -05:00
Antoine
ec5e42d733 feat: Add M1 mirror Zernike optimization with correct RMS calculation
Major improvements to telescope mirror optimization workflow:

Assembly FEM Workflow (solve_simulation.py):
- Fixed multi-part assembly FEM update sequence
- Use ImportFromFile() for reliable expression updates
- Add DuplicateNodesCheckBuilder with MergeOccurrenceNodes=True
- Switch to Foreground solve mode for multi-subcase solutions
- Add detailed logging and diagnostics for node merge operations

Zernike RMS Calculation:
- CRITICAL FIX: Use correct surface-based RMS formula
  - Global RMS = sqrt(mean(W^2)) from actual WFE values
  - Filtered RMS = sqrt(mean(W_residual^2)) after removing low-order fit
  - This matches zernike_Post_Script_NX.py (optical standard)
- Previous WRONG formula was: sqrt(sum(coeffs^2))
- Add compute_rms_filter_j1to3() for optician workload metric

Subcase Mapping:
- Fix subcase mapping to match NX model:
  - Subcase 1 = 90 deg (polishing orientation)
  - Subcase 2 = 20 deg (reference)
  - Subcase 3 = 40 deg
  - Subcase 4 = 60 deg

New Study: M1 Mirror Zernike Optimization
- Full optimization config with 11 design variables
- 3 objectives: rel_filtered_rms_40_vs_20, rel_filtered_rms_60_vs_20, mfg_90_optician_workload
- Neural surrogate support for accelerated optimization

Documentation:
- Update ZERNIKE_INTEGRATION.md with correct RMS formula
- Update ASSEMBLY_FEM_WORKFLOW.md with expression import and node merge details
- Add reference scripts from original zernike_Post_Script_NX.py

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-28 16:30:15 -05:00
2b3573ec42 feat: Add AtomizerField training data export and intelligent model discovery
Major additions:
- Training data export system for AtomizerField neural network training
- Bracket stiffness optimization study with 50+ training samples
- Intelligent NX model discovery (auto-detect solutions, expressions, mesh)
- Result extractors module for displacement, stress, frequency, mass
- User-generated NX journals for advanced workflows
- Archive structure for legacy scripts and test outputs
- Protocol documentation and dashboard launcher

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Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 12:01:50 -05:00