docs: Complete M1 mirror optimization campaign V11-V15
## M1 Mirror Campaign Summary - V11-V15 optimization campaign completed (~1,400 FEA evaluations) - Best design: V14 Trial #725 with Weighted Sum = 121.72 - V15 NSGA-II confirmed V14 TPE found optimal solution - Campaign improved from WS=129.33 (V11) to WS=121.72 (V14): -5.9% ## Key Results - 40° tracking: 5.99 nm (target 4.0 nm) - 60° tracking: 13.10 nm (target 10.0 nm) - Manufacturing: 26.28 nm (target 20.0 nm) - Targets not achievable within current design space ## Documentation Added - V15 STUDY_REPORT.md: Detailed NSGA-II results analysis - M1_MIRROR_CAMPAIGN_SUMMARY.md: Full V11-V15 campaign overview - Updated CLAUDE.md, ATOMIZER_CONTEXT.md with NXSolver patterns - Updated 01_CHEATSHEET.md with --resume guidance - Updated OP_01_CREATE_STUDY.md with FEARunner template ## Studies Added - m1_mirror_adaptive_V13: TPE validation (291 trials) - m1_mirror_adaptive_V14: TPE intensive (785 trials, BEST) - m1_mirror_adaptive_V15: NSGA-II exploration (126 new FEA) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Antoine
@@ -61,11 +61,9 @@ Use keyword matching to load appropriate context:
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```bash
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# Optimization workflow
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python run_optimization.py --discover # 1 trial - model introspection
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python run_optimization.py --validate # 1 trial - verify pipeline
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python run_optimization.py --test # 3 trials - quick sanity check
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python run_optimization.py --run --trials 50 # Full optimization
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python run_optimization.py --resume # Continue existing study
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python run_optimization.py --start --trials 50 # Run optimization
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python run_optimization.py --start --resume # Continue interrupted run
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python run_optimization.py --test # Single trial test
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# Neural acceleration
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python run_nn_optimization.py --turbo --nn-trials 5000 # Fast NN exploration
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@@ -75,6 +73,17 @@ python -m optimization_engine.method_selector config.json study.db # Get recomm
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cd atomizer-dashboard && npm run dev # Start at http://localhost:3003
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```
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### When to Use --resume
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| Scenario | Use --resume? |
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|----------|---------------|
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| First run of new study | NO |
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| First run with seeding (e.g., V15 from V14) | NO - seeding is automatic |
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| Continue interrupted run | YES |
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| Add more trials to completed study | YES |
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**Key**: `--resume` continues existing `study.db`. Seeding from `source_studies` in config happens automatically on first run - don't confuse seeding with resuming!
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### Study Structure (100% standardized)
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```
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@@ -248,6 +257,54 @@ surrogate.run() # Handles --train, --turbo, --all
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---
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## CRITICAL: NXSolver Initialization Pattern
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**NEVER pass full config dict to NXSolver.** This causes `TypeError: expected str, bytes or os.PathLike object, not dict`.
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### WRONG
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```python
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self.nx_solver = NXSolver(self.config) # ❌ NEVER DO THIS
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```
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### CORRECT - FEARunner Pattern
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Always wrap NXSolver in a `FEARunner` class with explicit parameters:
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```python
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class FEARunner:
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def __init__(self, config: Dict):
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self.config = config
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self.nx_solver = None
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self.master_model_dir = SETUP_DIR / "model"
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def setup(self):
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import re
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nx_settings = self.config.get('nx_settings', {})
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nx_install_dir = nx_settings.get('nx_install_path', 'C:\\Program Files\\Siemens\\NX2506')
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version_match = re.search(r'NX(\d+)', nx_install_dir)
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nastran_version = version_match.group(1) if version_match else "2506"
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self.nx_solver = NXSolver(
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master_model_dir=str(self.master_model_dir),
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nx_install_dir=nx_install_dir,
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nastran_version=nastran_version,
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timeout=nx_settings.get('simulation_timeout_s', 600),
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use_iteration_folders=True,
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study_name=self.config.get('study_name', 'my_study')
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)
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def run_fea(self, params, iter_num):
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if self.nx_solver is None:
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self.setup()
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# ... run simulation
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```
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**Reference implementations**:
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- `studies/m1_mirror_adaptive_V14/run_optimization.py`
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- `studies/m1_mirror_adaptive_V15/run_optimization.py`
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---
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## Skill Registry (Phase 3 - Consolidated Skills)
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All skills now have YAML frontmatter with metadata for versioning and dependency tracking.
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@@ -354,17 +411,18 @@ python -m optimization_engine.auto_doc templates
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| Component | Version | Last Updated |
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|-----------|---------|--------------|
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| ATOMIZER_CONTEXT | 1.5 | 2025-12-07 |
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| ATOMIZER_CONTEXT | 1.6 | 2025-12-12 |
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| BaseOptimizationRunner | 1.0 | 2025-12-07 |
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| GenericSurrogate | 1.0 | 2025-12-07 |
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| Study State Detector | 1.0 | 2025-12-07 |
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| Template Registry | 1.0 | 2025-12-07 |
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| Extractor Library | 1.3 | 2025-12-07 |
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| Extractor Library | 1.4 | 2025-12-12 |
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| Method Selector | 2.1 | 2025-12-07 |
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| Protocol System | 2.0 | 2025-12-06 |
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| Skill System | 2.0 | 2025-12-07 |
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| Protocol System | 2.1 | 2025-12-12 |
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| Skill System | 2.1 | 2025-12-12 |
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| Auto-Doc Generator | 1.0 | 2025-12-07 |
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| Subagent Commands | 1.0 | 2025-12-07 |
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| FEARunner Pattern | 1.0 | 2025-12-12 |
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---
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