Anto01
cb6b130908
Added JSON Schema: - optimization_engine/schemas/atomizer_spec_v2.json Migrated 28 studies to AtomizerSpec v2.0 format: - Drone_Gimbal studies (1) - M1_Mirror studies (21) - M2_Mirror studies (2) - SheetMetal_Bracket studies (4) Each atomizer_spec.json is the unified configuration containing: - Design variables with bounds and expressions - Extractors (standard and custom) - Objectives and constraints - Optimization algorithm settings - Canvas layout information
bracket_pareto_3obj
Three-objective Pareto optimization: minimize mass, minimize stress, maximize stiffness
Generated: 2025-12-06 14:43 Protocol: Multi-Objective NSGA-II Trials: 100
1. Engineering Problem
Three-objective Pareto optimization: minimize mass, minimize stress, maximize stiffness
2. Mathematical Formulation
Design Variables
| Parameter | Bounds | Units | Description |
|---|---|---|---|
support_angle |
[20, 70] | degrees | Angle of support arm relative to base |
tip_thickness |
[30, 60] | mm | Thickness at bracket tip where load is applied |
Objectives
| Objective | Goal | Extractor | Weight |
|---|---|---|---|
| mass | minimize | extract_mass_from_bdf |
1.0 |
| stress | minimize | extract_solid_stress |
1.0 |
| stiffness | maximize | extract_displacement |
1.0 |
Constraints
| Constraint | Type | Threshold | Units |
|---|---|---|---|
| stress_limit | less_than | 300 | MPa |
3. Optimization Algorithm
- Protocol: protocol_11_multi
- Sampler: NSGAIISampler
- Trials: 100
- Neural Acceleration: Disabled
4. Simulation Pipeline
Design Variables → NX Expression Update → Nastran Solve → Result Extraction → Objective Evaluation
5. Result Extraction Methods
| Result | Extractor | Source |
|---|---|---|
| mass | extract_mass_from_bdf |
OP2/DAT |
| stress | extract_solid_stress |
OP2/DAT |
| stiffness | extract_displacement |
OP2/DAT |
6. Study File Structure
bracket_pareto_3obj/
├── 1_setup/
│ ├── model/
│ │ ├── Bracket.prt
│ │ ├── Bracket_sim1.sim
│ │ └── Bracket_fem1.fem
│ ├── optimization_config.json
│ └── workflow_config.json
├── 2_results/
│ ├── study.db
│ └── optimization.log
├── run_optimization.py
├── reset_study.py
├── README.md
├── STUDY_REPORT.md
└── MODEL_INTROSPECTION.md
7. Quick Start
# 1. Discover model outputs
python run_optimization.py --discover
# 2. Validate setup with single trial
python run_optimization.py --validate
# 3. Run integration test (3 trials)
python run_optimization.py --test
# 4. Run full optimization
python run_optimization.py --run --trials 100
# 5. Resume if interrupted
python run_optimization.py --run --trials 50 --resume
8. Results Location
| File | Description |
|---|---|
2_results/study.db |
Optuna SQLite database |
2_results/optimization.log |
Structured log file |
2_results/pareto_front.json |
Pareto-optimal solutions |