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>
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# Create Optimization Study Skill
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**Last Updated**: December 4, 2025
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**Version**: 2.1 - Added Mandatory Documentation Requirements
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**Last Updated**: December 6, 2025
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**Version**: 2.2 - Added Model Introspection
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You are helping the user create a complete Atomizer optimization study from a natural language description.
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@@ -9,12 +9,50 @@ You are helping the user create a complete Atomizer optimization study from a na
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---
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## MANDATORY: Model Introspection
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**ALWAYS run introspection when user provides NX files or asks for model analysis:**
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```python
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from optimization_engine.hooks.nx_cad.model_introspection import (
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introspect_part,
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introspect_simulation,
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introspect_op2,
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introspect_study
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)
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# Introspect entire study directory (recommended)
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study_info = introspect_study("studies/my_study/")
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# Or introspect individual files
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part_info = introspect_part("path/to/model.prt")
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sim_info = introspect_simulation("path/to/model.sim")
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op2_info = introspect_op2("path/to/results.op2")
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```
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### What Introspection Provides
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| Source | Information Extracted |
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|--------|----------------------|
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| `.prt` | Expressions (potential design variables), bodies, mass, material, features |
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| `.sim` | Solutions (SOL types), boundary conditions, loads, materials, mesh info, output requests |
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| `.op2` | Available results (displacement, stress, strain, SPC forces, frequencies), subcases |
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### Generate MODEL_INTROSPECTION.md
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**MANDATORY**: Save introspection report at study creation:
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- Location: `studies/{study_name}/MODEL_INTROSPECTION.md`
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- Contains: All expressions, solutions, available results, optimization recommendations
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---
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## MANDATORY DOCUMENTATION CHECKLIST
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**EVERY study MUST have these files. A study is NOT complete without them:**
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| File | Purpose | When Created |
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|------|---------|--------------|
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| `MODEL_INTROSPECTION.md` | **Model Analysis** - Expressions, solutions, available results | At study creation |
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| `README.md` | **Engineering Blueprint** - Full mathematical formulation, design variables, objectives, algorithm config | At study creation |
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| `STUDY_REPORT.md` | **Results Tracking** - Progress, best designs, surrogate accuracy, recommendations | At study creation (template) |
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@@ -2053,6 +2091,7 @@ Multi-Solution: {Yes/No}
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✓ studies/{study_name}/1_setup/workflow_config.json
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✓ studies/{study_name}/run_optimization.py
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✓ studies/{study_name}/reset_study.py
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✓ studies/{study_name}/MODEL_INTROSPECTION.md # MANDATORY - Model analysis
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✓ studies/{study_name}/README.md # Engineering blueprint
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✓ studies/{study_name}/STUDY_REPORT.md # MANDATORY - Results report template
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[✓] studies/{study_name}/NX_FILE_MODIFICATIONS_REQUIRED.md (if needed)
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