feat: Add MLP surrogate with Turbo Mode for 100x faster optimization

Neural Acceleration (MLP Surrogate):
- Add run_nn_optimization.py with hybrid FEA/NN workflow
- MLP architecture: 4-layer (64->128->128->64) with BatchNorm/Dropout
- Three workflow modes:
  - --all: Sequential export->train->optimize->validate
  - --hybrid-loop: Iterative Train->NN->Validate->Retrain cycle
  - --turbo: Aggressive single-best validation (RECOMMENDED)
- Turbo mode: 5000 NN trials + 50 FEA validations in ~12 minutes
- Separate nn_study.db to avoid overloading dashboard

Performance Results (bracket_pareto_3obj study):
- NN prediction errors: mass 1-5%, stress 1-4%, stiffness 5-15%
- Found minimum mass designs at boundary (angle~30deg, thick~30mm)
- 100x speedup vs pure FEA exploration

Protocol Operating System:
- Add .claude/skills/ with Bootstrap, Cheatsheet, Context Loader
- Add docs/protocols/ with operations (OP_01-06) and system (SYS_10-14)
- Update SYS_14_NEURAL_ACCELERATION.md with MLP Turbo Mode docs

NX Automation:
- Add optimization_engine/hooks/ for NX CAD/CAE automation
- Add study_wizard.py for guided study creation
- Fix FEM mesh update: load idealized part before UpdateFemodel()

New Study:
- bracket_pareto_3obj: 3-objective Pareto (mass, stress, stiffness)
- 167 FEA trials + 5000 NN trials completed
- Demonstrates full hybrid workflow

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

studies/bracket_pareto_3obj/reset_study.py

@@ -0,0 +1,48 @@
+"""
+Reset study - Delete results database and logs.
+
+Usage:
+    python reset_study.py
+    python reset_study.py --confirm  # Skip confirmation
+"""
+
+from pathlib import Path
+import shutil
+
+
+def main():
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--confirm', action='store_true', help='Skip confirmation')
+    args = parser.parse_args()
+
+    study_dir = Path(__file__).parent
+    results_dir = study_dir / "2_results"
+
+    if not args.confirm:
+        print(f"This will delete all results in: {results_dir}")
+        response = input("Are you sure? (y/N): ")
+        if response.lower() != 'y':
+            print("Cancelled.")
+            return
+
+    # Delete database files
+    for f in results_dir.glob("*.db"):
+        f.unlink()
+        print(f"Deleted: {f.name}")
+
+    # Delete log files
+    for f in results_dir.glob("*.log"):
+        f.unlink()
+        print(f"Deleted: {f.name}")
+
+    # Delete JSON results
+    for f in results_dir.glob("*.json"):
+        f.unlink()
+        print(f"Deleted: {f.name}")
+
+    print("Study reset complete.")
+
+
+if __name__ == "__main__":
+    main()