Atomizer

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Author	SHA1	Message	Date
Antoine	602560c46a	feat: Add MLP surrogate with Turbo Mode for 100x faster optimization Neural Acceleration (MLP Surrogate): - Add run_nn_optimization.py with hybrid FEA/NN workflow - MLP architecture: 4-layer (64->128->128->64) with BatchNorm/Dropout - Three workflow modes: - --all: Sequential export->train->optimize->validate - --hybrid-loop: Iterative Train->NN->Validate->Retrain cycle - --turbo: Aggressive single-best validation (RECOMMENDED) - Turbo mode: 5000 NN trials + 50 FEA validations in ~12 minutes - Separate nn_study.db to avoid overloading dashboard Performance Results (bracket_pareto_3obj study): - NN prediction errors: mass 1-5%, stress 1-4%, stiffness 5-15% - Found minimum mass designs at boundary (angle~30deg, thick~30mm) - 100x speedup vs pure FEA exploration Protocol Operating System: - Add .claude/skills/ with Bootstrap, Cheatsheet, Context Loader - Add docs/protocols/ with operations (OP_01-06) and system (SYS_10-14) - Update SYS_14_NEURAL_ACCELERATION.md with MLP Turbo Mode docs NX Automation: - Add optimization_engine/hooks/ for NX CAD/CAE automation - Add study_wizard.py for guided study creation - Fix FEM mesh update: load idealized part before UpdateFemodel() New Study: - bracket_pareto_3obj: 3-objective Pareto (mass, stress, stiffness) - 167 FEA trials + 5000 NN trials completed - Demonstrates full hybrid workflow 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>	2025-12-06 20:01:59 -05:00
Anto01	91fb929f6a	refactor: Centralize NX and environment configuration in config.py MAJOR IMPROVEMENT: Single source of truth for all system paths Now to change NX version or Python environment, edit ONE file (config.py): NX_VERSION = "2412" # Change this for NX updates PYTHON_ENV_NAME = "atomizer" # Change this for env updates All code automatically uses new paths - no manual file hunting! New Central Configuration (config.py): - NX_VERSION: Automatically updates all NX paths - NX_INSTALLATION_DIR: Derived from version - NX_RUN_JOURNAL: Path to run_journal.exe - NX_MATERIAL_LIBRARY: Path to physicalmateriallibrary.xml - NX_PYTHON_STUBS: Path to Python stubs for intellisense - PYTHON_ENV_NAME: Python environment name - PROJECT_ROOT: Auto-detected project root - Helper functions: get_nx_journal_command(), validate_config(), print_config() Updated Files to Use Config: - optimization_engine/nx_updater.py: Uses NX_RUN_JOURNAL from config - dashboard/api/app.py: Uses NX_RUN_JOURNAL from config - Both have fallbacks if config unavailable Benefits: 1. Change NX version in 1 place, not 10+ files 2. Automatic validation of paths on import 3. Helper functions for common operations 4. Clear error messages if paths missing 5. Easy to add new Simcenter versions Future NX Update Process: 1. Edit config.py: NX_VERSION = "2506" 2. Run: python config.py (verify paths) 3. Done! All code uses NX 2506 Migration Scripts Included: - migrate_to_config.py: Full migration with documentation - apply_config_migration.py: Applied to update dashboard 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>	2025-11-17 14:31:33 -05:00

Author

SHA1

Message

Date

Antoine

602560c46a

feat: Add MLP surrogate with Turbo Mode for 100x faster optimization

Neural Acceleration (MLP Surrogate):
- Add run_nn_optimization.py with hybrid FEA/NN workflow
- MLP architecture: 4-layer (64->128->128->64) with BatchNorm/Dropout
- Three workflow modes:
  - --all: Sequential export->train->optimize->validate
  - --hybrid-loop: Iterative Train->NN->Validate->Retrain cycle
  - --turbo: Aggressive single-best validation (RECOMMENDED)
- Turbo mode: 5000 NN trials + 50 FEA validations in ~12 minutes
- Separate nn_study.db to avoid overloading dashboard

Performance Results (bracket_pareto_3obj study):
- NN prediction errors: mass 1-5%, stress 1-4%, stiffness 5-15%
- Found minimum mass designs at boundary (angle~30deg, thick~30mm)
- 100x speedup vs pure FEA exploration

Protocol Operating System:
- Add .claude/skills/ with Bootstrap, Cheatsheet, Context Loader
- Add docs/protocols/ with operations (OP_01-06) and system (SYS_10-14)
- Update SYS_14_NEURAL_ACCELERATION.md with MLP Turbo Mode docs

NX Automation:
- Add optimization_engine/hooks/ for NX CAD/CAE automation
- Add study_wizard.py for guided study creation
- Fix FEM mesh update: load idealized part before UpdateFemodel()

New Study:
- bracket_pareto_3obj: 3-objective Pareto (mass, stress, stiffness)
- 167 FEA trials + 5000 NN trials completed
- Demonstrates full hybrid workflow

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2025-12-06 20:01:59 -05:00

Anto01

91fb929f6a

refactor: Centralize NX and environment configuration in config.py

MAJOR IMPROVEMENT: Single source of truth for all system paths

Now to change NX version or Python environment, edit ONE file (config.py):
  NX_VERSION = "2412"           # Change this for NX updates
  PYTHON_ENV_NAME = "atomizer"  # Change this for env updates

All code automatically uses new paths - no manual file hunting!

New Central Configuration (config.py):
- NX_VERSION: Automatically updates all NX paths
- NX_INSTALLATION_DIR: Derived from version
- NX_RUN_JOURNAL: Path to run_journal.exe
- NX_MATERIAL_LIBRARY: Path to physicalmateriallibrary.xml
- NX_PYTHON_STUBS: Path to Python stubs for intellisense
- PYTHON_ENV_NAME: Python environment name
- PROJECT_ROOT: Auto-detected project root
- Helper functions: get_nx_journal_command(), validate_config(), print_config()

Updated Files to Use Config:
- optimization_engine/nx_updater.py: Uses NX_RUN_JOURNAL from config
- dashboard/api/app.py: Uses NX_RUN_JOURNAL from config
- Both have fallbacks if config unavailable

Benefits:
1. Change NX version in 1 place, not 10+ files
2. Automatic validation of paths on import
3. Helper functions for common operations
4. Clear error messages if paths missing
5. Easy to add new Simcenter versions

Future NX Update Process:
1. Edit config.py: NX_VERSION = "2506"
2. Run: python config.py (verify paths)
3. Done! All code uses NX 2506

Migration Scripts Included:
- migrate_to_config.py: Full migration with documentation
- apply_config_migration.py: Applied to update dashboard

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

Co-Authored-By: Claude <noreply@anthropic.com>

2025-11-17 14:31:33 -05:00

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