feat: Add AtomizerField training data export and intelligent model discovery

Major additions:
- Training data export system for AtomizerField neural network training
- Bracket stiffness optimization study with 50+ training samples
- Intelligent NX model discovery (auto-detect solutions, expressions, mesh)
- Result extractors module for displacement, stress, frequency, mass
- User-generated NX journals for advanced workflows
- Archive structure for legacy scripts and test outputs
- Protocol documentation and dashboard launcher

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

archive/test_scripts/test_nn_surrogate.py

@@ -0,0 +1,35 @@
+"""Test neural surrogate integration"""
+import sys
+from pathlib import Path
+
+# Add project paths
+project_root = Path(__file__).parent
+sys.path.insert(0, str(project_root))
+sys.path.insert(0, str(project_root / 'atomizer-field'))
+
+from optimization_engine.neural_surrogate import create_parametric_surrogate_for_study
+
+# Create surrogate
+print("Creating parametric surrogate...")
+surrogate = create_parametric_surrogate_for_study(project_root=project_root)
+
+if surrogate:
+    print('Surrogate created successfully!')
+    print(f'Design vars: {surrogate.design_var_names}')
+    print(f'Number of nodes: {surrogate.num_nodes}')
+
+    # Test prediction with example params
+    test_params = {name: 2.0 for name in surrogate.design_var_names}
+    print(f'\nTest params: {test_params}')
+
+    results = surrogate.predict(test_params)
+    print(f'\nTest prediction:')
+    print(f'  Mass: {results["mass"]:.2f}')
+    print(f'  Frequency: {results["frequency"]:.2f}')
+    print(f'  Max Displacement: {results["max_displacement"]:.6f}')
+    print(f'  Max Stress: {results["max_stress"]:.2f}')
+    print(f'  Inference time: {results["inference_time_ms"]:.2f} ms')
+
+    print('\nSurrogate is ready for use in optimization!')
+else:
+    print('Failed to create surrogate')