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>
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tests/test_bracket_full_optimization.py
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tests/test_bracket_full_optimization.py
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"""
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Full End-to-End Bracket Optimization Test - Phase 3.2
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This test demonstrates the complete LLM-enhanced optimization workflow:
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1. LLM workflow configuration
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2. Automatic extractor generation (displacement + stress)
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3. Inline calculation generation (safety factor)
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4. Manual safety factor constraint hook
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5. Real NX simulation execution
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6. OP2 result extraction
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7. Constraint checking
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8. Optimization with Optuna
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9. Report generation
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Objective: Maximize displacement
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Constraint: Safety factor >= 4.0 (stress < yield/4)
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Material: Aluminum 6061-T6 (Yield = 276 MPa)
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Design Variable: wall_thickness (3-8mm)
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"""
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import sys
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from pathlib import Path
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from datetime import datetime
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import json
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from optimization_engine.llm_optimization_runner import LLMOptimizationRunner
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from optimization_engine.nx_solver import NXSolver
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from optimization_engine.nx_updater import NXParameterUpdater
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# LLM workflow for bracket optimization
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llm_workflow = {
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'engineering_features': [
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{
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'action': 'extract_displacement',
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'domain': 'result_extraction',
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'description': 'Extract displacement results from OP2 file',
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'params': {'result_type': 'displacement'}
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},
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{
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'action': 'extract_solid_stress',
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'domain': 'result_extraction',
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'description': 'Extract von Mises stress from solid elements',
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'params': {
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'result_type': 'stress',
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'element_type': 'chexa' # Bracket uses CHEXA elements, not CTETRA
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}
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}
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],
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'inline_calculations': [
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{
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'action': 'calculate_safety_factor',
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'params': {
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'input': 'max_von_mises',
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'yield_strength': 276.0, # MPa for Aluminum 6061-T6
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'operation': 'divide'
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},
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'code_hint': 'safety_factor = 276.0 / max_von_mises'
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},
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{
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'action': 'negate_displacement',
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'params': {
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'input': 'max_displacement',
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'operation': 'negate'
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},
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'code_hint': 'neg_displacement = -max_displacement'
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}
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],
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'post_processing_hooks': [], # Using manual safety_factor_constraint hook
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'optimization': {
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'algorithm': 'TPE',
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'direction': 'minimize', # Minimize neg_displacement = maximize displacement
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'design_variables': [
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{
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'parameter': 'tip_thickness',
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'min': 15.0,
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'max': 25.0,
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'units': 'mm'
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},
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{
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'parameter': 'support_angle',
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'min': 20.0,
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'max': 40.0,
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'units': 'degrees'
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}
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]
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}
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}
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def create_model_updater(prt_file: Path):
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"""Create model updater for NX."""
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updater = NXParameterUpdater(prt_file_path=prt_file)
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def update_model(design_vars: dict):
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"""Update NX model with design variables."""
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updater.update_expressions(design_vars)
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updater.save() # Save changes to disk
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return update_model
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def create_simulation_runner(sim_file: Path):
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"""Create simulation runner for NX."""
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solver = NXSolver(nastran_version='2412', use_journal=True)
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def run_simulation() -> Path:
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"""Run NX simulation and return OP2 file path."""
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result = solver.run_simulation(sim_file)
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return result['op2_file'] # Extract Path from result dict
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return run_simulation
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def generate_report(results: dict, output_dir: Path):
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"""Generate optimization report with history."""
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report_file = output_dir / "optimization_report.md"
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best_params = results['best_params']
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best_value = results['best_value']
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history = results['history']
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with open(report_file, 'w') as f:
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f.write("# Bracket Optimization Report - Phase 3.2\n\n")
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f.write(f"**Generated**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n")
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f.write("## Problem Definition\n\n")
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f.write("- **Objective**: Maximize displacement\n")
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f.write("- **Constraint**: Safety factor >= 4.0\n")
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f.write("- **Material**: Aluminum 6061-T6 (Yield = 276 MPa)\n")
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f.write("- **Allowable Stress**: 69 MPa (276/4)\n")
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f.write("- **Design Variables**:\n")
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f.write(" - tip_thickness (15-25 mm)\n")
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f.write(" - support_angle (20-40 degrees)\n\n")
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f.write("## Optimization Results\n\n")
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f.write(f"- **Best tip_thickness**: {best_params['tip_thickness']:.3f} mm\n")
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f.write(f"- **Best support_angle**: {best_params['support_angle']:.3f} degrees\n")
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f.write(f"- **Best objective value**: {best_value:.6f}\n")
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f.write(f"- **Total trials**: {len(history)}\n\n")
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# Find best trial details
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best_trial = history[results['best_trial_number']]
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best_results = best_trial['results']
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best_calcs = best_trial['calculations']
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f.write("## Best Design Details\n\n")
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f.write(f"- **Max displacement**: {best_results.get('max_displacement', 0):.6f} mm\n")
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f.write(f"- **Max stress**: {best_results.get('max_von_mises', 0):.3f} MPa\n")
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f.write(f"- **Safety factor**: {best_calcs.get('safety_factor', 0):.3f}\n")
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f.write(f"- **Constraint status**: {'SATISFIED' if best_calcs.get('safety_factor', 0) >= 4.0 else 'VIOLATED'}\n\n")
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f.write("## Optimization History\n\n")
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f.write("| Trial | Tip Thick (mm) | Support Angle (°) | Displacement (mm) | Stress (MPa) | Safety Factor | Constraint | Objective |\n")
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f.write("|-------|----------------|-------------------|-------------------|--------------|---------------|------------|-----------|\n")
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for trial in history:
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trial_num = trial['trial_number']
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tip_thick = trial['design_variables']['tip_thickness']
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support_ang = trial['design_variables']['support_angle']
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disp = trial['results'].get('max_displacement', 0)
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stress = trial['results'].get('max_von_mises', 0)
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sf = trial['calculations'].get('safety_factor', 0)
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constraint = 'OK' if sf >= 4.0 else 'FAIL'
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obj = trial['objective']
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f.write(f"| {trial_num} | {tip_thick:.3f} | {support_ang:.3f} | {disp:.6f} | {stress:.3f} | {sf:.3f} | {constraint} | {obj:.6f} |\n")
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f.write("\n## LLM-Enhanced Workflow\n\n")
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f.write("This optimization was run using the Phase 3.2 LLM-enhanced runner with:\n\n")
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f.write("- **Automatic extractor generation**: Displacement + Stress (Phase 3.1)\n")
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f.write("- **Inline calculations**: Safety factor + Objective negation (Phase 2.8)\n")
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f.write("- **Manual constraint hook**: Safety factor constraint (demonstrates flexibility)\n")
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f.write("- **Real NX simulation**: Journal-based solver execution\n")
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f.write("- **Optuna optimization**: TPE sampler\n\n")
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f.write("---\n\n")
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f.write("*Generated by Atomizer Phase 3.2 - LLM-Enhanced Optimization Framework*\n")
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print(f"\nReport saved to: {report_file}")
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return report_file
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if __name__ == '__main__':
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print("=" * 80)
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print("Phase 3.2: Full End-to-End Bracket Optimization Test")
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print("=" * 80)
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print()
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print("Problem:")
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print(" Maximize displacement while maintaining safety factor >= 4.0")
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print(" Material: Aluminum 6061-T6 (Yield = 276 MPa)")
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print(" Design Variables:")
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print(" - tip_thickness (15-25 mm)")
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print(" - support_angle (20-40 degrees)")
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print()
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# Configuration
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sim_file = Path("tests/Bracket_sim1.sim")
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prt_file = Path("tests/Bracket.prt")
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n_trials = 5 # Start with 5 trials for testing
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if not sim_file.exists():
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print(f"ERROR: Simulation file not found: {sim_file}")
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print("Please ensure the bracket .sim file is available")
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sys.exit(1)
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if not prt_file.exists():
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print(f"ERROR: Part file not found: {prt_file}")
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print("Please ensure the bracket .prt file is available")
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sys.exit(1)
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print(f"Simulation file: {sim_file}")
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print(f"Part file: {prt_file}")
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print(f"Number of trials: {n_trials}")
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print()
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try:
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# Create model updater and simulation runner
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print("Setting up NX integration...")
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model_updater = create_model_updater(prt_file)
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simulation_runner = create_simulation_runner(sim_file)
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print(" NX updater: OK")
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print(" NX solver: OK")
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print()
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# Initialize LLM optimization runner
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print("Initializing LLM-enhanced optimization runner...")
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runner = LLMOptimizationRunner(
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llm_workflow=llm_workflow,
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model_updater=model_updater,
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simulation_runner=simulation_runner,
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study_name='bracket_maximize_disp_sf4'
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)
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print(f" Extractors generated: {len(runner.extractors)}")
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for ext in runner.extractors:
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print(f" - {ext}")
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print(f" Inline calculations: {len(runner.inline_code)}")
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hook_summary = runner.hook_manager.get_summary()
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print(f" Hooks loaded: {hook_summary['enabled_hooks']}")
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print(" (Including manual safety_factor_constraint hook)")
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print()
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# Run optimization
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print("=" * 80)
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print("Starting Optimization...")
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print("=" * 80)
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print()
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results = runner.run_optimization(n_trials=n_trials)
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print()
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print("=" * 80)
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print("Optimization Complete!")
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print("=" * 80)
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print()
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print(f"Best tip_thickness: {results['best_params']['tip_thickness']:.3f} mm")
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print(f"Best support_angle: {results['best_params']['support_angle']:.3f} degrees")
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print(f"Best objective value: {results['best_value']:.6f}")
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print()
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# Generate report
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print("Generating optimization report...")
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report_file = generate_report(results, runner.output_dir)
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print()
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print("=" * 80)
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print("Test Complete!")
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print("=" * 80)
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print(f"Results directory: {runner.output_dir}")
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print(f"Report: {report_file}")
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except Exception as e:
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print(f"\nERROR during optimization: {e}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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