Files
Atomizer/studies/bracket_displacement_maximizing
Anto01 d228ccec66 refactor: Archive experimental LLM features for MVP stability (Phase 1.1)
Moved experimental LLM integration code to optimization_engine/future/:
- llm_optimization_runner.py - Runtime LLM API runner
- llm_workflow_analyzer.py - Workflow analysis
- inline_code_generator.py - Auto-generate calculations
- hook_generator.py - Auto-generate hooks
- report_generator.py - LLM report generation
- extractor_orchestrator.py - Extractor orchestration

Added comprehensive optimization_engine/future/README.md explaining:
- MVP LLM strategy (Claude Code skills, not runtime LLM)
- Why files were archived
- When to revisit post-MVP
- Production architecture reference

Production runner confirmed: optimization_engine/runner.py is sole active runner.

This establishes clear separation between:
- Production code (stable, no runtime LLM dependencies)
- Experimental code (archived for post-MVP exploration)

Part of Phase 1: Core Stabilization & Organization for MVP

Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-24 09:12:36 -05:00
..

Bracket Displacement Maximization Study

Study Name: bracket_displacement_maximizing Created: 2025-11-16 Phase: 3.3 - Optimization Setup Wizard

Overview

This study demonstrates the complete Phase 3.3 workflow for optimizing a bracket design to maximize displacement while maintaining structural safety.

Problem Statement

Objective: Maximize the displacement of a bracket under load

Constraints:

  • Safety factor ≥ 4.0
  • Material: Aluminum 6061-T6 (Yield strength = 276 MPa)
  • Allowable stress: 69 MPa (276/4)

Design Variables:

  • tip_thickness: 15-25 mm (baseline: 17 mm)
  • support_angle: 20-40° (baseline: 38°)

Model Information

  • Geometry: Bracket part with tip and support features
  • Mesh: 585 nodes, 316 elements (CHEXA, CPENTA)
  • Load: Applied force at tip
  • Boundary Conditions: Fixed support at base

Optimization Setup

Phase 3.3 Wizard Workflow

  1. Model Introspection - Read NX expressions from .prt file
  2. Baseline Simulation - Run initial simulation to validate setup
  3. OP2 Introspection - Auto-detect element types (CHEXA, CPENTA)
  4. Workflow Configuration - Build LLM workflow with detected element types
  5. Pipeline Validation - Dry-run test of all components
  6. Optimization - Run 20-trial TPE optimization

Extractors

  • Displacement: Extract max displacement from OP2 file
  • Stress: Extract von Mises stress from solid elements (auto-detected: CHEXA)

Calculations

  • Safety Factor: SF = 276.0 / max_von_mises
  • Objective: neg_displacement = -max_displacement (minimize for maximization)

Constraints

  • Safety Factor Hook: Enforces SF ≥ 4.0 with penalty

Directory Structure

bracket_displacement_maximizing/
├── model/                    # NX model files (isolated from tests/)
│   ├── Bracket.prt          # Part geometry
│   ├── Bracket_fem1.fem     # FE model
│   └── Bracket_sim1.sim     # Simulation setup
├── results/                  # Optimization results
│   ├── optimization_history.json
│   ├── best_design.json
│   └── trial_*.op2          # OP2 files for each trial
├── config/                   # Study configuration
│   └── study_config.json    # Complete study setup
├── run_optimization.py       # Main optimization script
├── optimization_log.txt      # Execution log
└── README.md                # This file

Running the Study

cd studies/bracket_displacement_maximizing
python run_optimization.py

The script will:

  1. Initialize the Phase 3.3 wizard
  2. Validate the complete pipeline
  3. Run 20 optimization trials
  4. Save results to results/ directory
  5. Generate comprehensive report

Results

Results are saved in the results/ directory:

  • optimization_history.json: Complete trial history
  • best_design.json: Best design parameters and performance
  • optimization_report.md: Human-readable summary

Key Features Demonstrated

Phase 3.3 Wizard - Automated validation before optimization Dynamic Element Detection - Auto-detects all element types from OP2 Self-Contained Study - Isolated model files prevent conflicts Complete Logging - Full execution trace for debugging Reproducible - Configuration files enable exact reproduction

Notes

  • All simulations run in the model/ directory to isolate from test files
  • OP2 files are regenerated for each trial (no caching issues)
  • Study can be re-run without affecting other tests or studies
  • Configuration is fully documented in config/study_config.json

References