Anto01
e3bdb08a22
- Add validation framework (config, model, results, study validators) - Add Claude Code skills (create-study, run-optimization, generate-report, troubleshoot, analyze-model) - Add Atomizer Dashboard (React frontend + FastAPI backend) - Reorganize docs into structured directories (00-09) - Add neural surrogate modules and training infrastructure - Add multi-objective optimization support 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
159 lines
3.6 KiB
JSON
159 lines
3.6 KiB
JSON
{
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"study_name": "beam_optimization_with_neural",
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"sim_file": "examples/Models/Beam/Beam.sim",
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"fem_file": "examples/Models/Beam/Beam_fem1.fem",
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"design_variables": [
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{
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"name": "width",
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"expression_name": "width",
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"min": 20.0,
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"max": 80.0
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},
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{
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"name": "height",
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"expression_name": "height",
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"min": 30.0,
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"max": 100.0
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},
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{
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"name": "thickness",
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"expression_name": "thickness",
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"min": 2.0,
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"max": 10.0
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}
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],
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"objectives": [
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{
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"name": "max_stress",
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"type": "minimize",
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"weight": 1.0,
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"extractor": {
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"type": "result_parameter",
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"parameter_name": "Max Von Mises Stress"
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}
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},
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{
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"name": "mass",
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"type": "minimize",
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"weight": 0.5,
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"extractor": {
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"type": "expression",
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"expression_name": "mass"
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}
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}
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],
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"constraints": [
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{
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"name": "stress_limit",
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"type": "less_than",
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"value": 250.0,
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"extractor": {
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"type": "result_parameter",
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"parameter_name": "Max Von Mises Stress"
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}
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},
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{
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"name": "max_displacement",
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"type": "less_than",
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"value": 5.0,
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"extractor": {
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"type": "result_parameter",
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"parameter_name": "Max Displacement"
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}
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}
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],
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"optimization": {
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"algorithm": "NSGA-II",
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"n_trials": 200,
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"population_size": 20
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},
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"neural_surrogate": {
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"enabled": true,
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"model_checkpoint": "atomizer-field/checkpoints/beam_model_v1.0/best_model.pt",
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"confidence_threshold": 0.85,
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"fallback_to_fea": true,
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"ensemble_models": [
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"atomizer-field/checkpoints/beam_model_v1.0/model_1.pt",
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"atomizer-field/checkpoints/beam_model_v1.0/model_2.pt",
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"atomizer-field/checkpoints/beam_model_v1.0/model_3.pt"
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],
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"device": "cuda",
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"batch_size": 32,
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"cache_predictions": true
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},
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"hybrid_optimization": {
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"enabled": true,
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"exploration_trials": 20,
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"training_interval": 50,
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"validation_frequency": 10,
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"min_training_samples": 30,
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"retrain_on_drift": true,
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"drift_threshold": 0.15,
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"adaptive_switching": true,
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"phases": [
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{
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"name": "exploration",
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"trials": [0, 20],
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"use_nn": false,
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"description": "Initial FEA-based exploration"
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},
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{
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"name": "training",
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"trials": [21, 30],
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"use_nn": false,
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"description": "Collect training data"
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},
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{
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"name": "exploitation",
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"trials": [31, 180],
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"use_nn": true,
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"description": "Neural network exploitation"
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},
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{
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"name": "validation",
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"trials": [181, 200],
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"use_nn": false,
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"description": "Final FEA validation"
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}
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]
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},
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"training_data_export": {
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"enabled": true,
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"export_dir": "atomizer_field_training_data/beam_study",
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"export_frequency": 1,
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"include_failed_trials": false,
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"compression": "gzip"
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},
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"neural_training": {
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"auto_train": true,
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"training_script": "atomizer-field/train.py",
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"epochs": 200,
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"learning_rate": 0.001,
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"batch_size": 16,
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"validation_split": 0.2,
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"early_stopping_patience": 20,
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"model_architecture": "GraphUNet",
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"hidden_channels": 128,
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"num_layers": 4,
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"dropout": 0.1,
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"physics_loss_weight": 0.3
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},
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"performance_tracking": {
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"track_speedup": true,
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"track_accuracy": true,
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"export_metrics": true,
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"metrics_file": "neural_performance_metrics.json"
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},
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"version": "2.0",
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"description": "Beam optimization with AtomizerField neural surrogate for 600x speedup"
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} |