feat: Major update with validators, skills, dashboard, and docs reorganization

- 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>

optimization_engine/runner.py

@@ -24,6 +24,7 @@ from datetime import datetime
 import pickle
 
 from optimization_engine.plugins import HookManager
+from optimization_engine.training_data_exporter import create_exporter_from_config
 
 
 class OptimizationRunner:
@@ -79,6 +80,11 @@ class OptimizationRunner:
             if summary['total_hooks'] > 0:
                 print(f"Loaded {summary['enabled_hooks']}/{summary['total_hooks']} plugins")
 
+        # Initialize training data exporter (if enabled in config)
+        self.training_data_exporter = create_exporter_from_config(self.config)
+        if self.training_data_exporter:
+            print(f"Training data export enabled: {self.training_data_exporter.export_dir}")
+
     def _load_config(self) -> Dict[str, Any]:
         """Load and validate optimization configuration."""
         with open(self.config_path, 'r') as f:
@@ -436,6 +442,32 @@ class OptimizationRunner:
         }
         self.hook_manager.execute_hooks('post_extraction', post_extraction_context, fail_fast=False)
 
+        # Export training data (if enabled)
+        if self.training_data_exporter:
+            # Determine .dat and .op2 file paths from result_path
+            # NX naming: sim_name-solution_N.dat and sim_name-solution_N.op2
+            if result_path:
+                sim_dir = Path(result_path).parent if Path(result_path).is_file() else Path(result_path)
+                sim_name = self.config.get('sim_file', '').replace('.sim', '')
+
+                # Try to find the .dat and .op2 files
+                # Typically: sim_name-solution_1.dat and sim_name-solution_1.op2
+                dat_files = list(sim_dir.glob(f"{Path(sim_name).stem}*.dat"))
+                op2_files = list(sim_dir.glob(f"{Path(sim_name).stem}*.op2"))
+
+                if dat_files and op2_files:
+                    simulation_files = {
+                        'dat_file': dat_files[0],  # Use first match
+                        'op2_file': op2_files[0]
+                    }
+
+                    self.training_data_exporter.export_trial(
+                        trial_number=trial.number,
+                        design_variables=design_vars,
+                        results=extracted_results,
+                        simulation_files=simulation_files
+                    )
+
         # 5. Evaluate constraints
         for const in self.config.get('constraints', []):
             value = extracted_results[const['name']]
@@ -614,6 +646,11 @@ class OptimizationRunner:
         self._save_study_metadata(study_name)
         self._save_final_results()
 
+        # Finalize training data export (if enabled)
+        if self.training_data_exporter:
+            self.training_data_exporter.finalize()
+            print(f"Training data export finalized: {self.training_data_exporter.trial_count} trials exported")
+
         # Post-processing: Visualization and Model Cleanup
         self._run_post_processing()