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>

optimization_engine/hooks/__init__.py

@@ -0,0 +1,72 @@
+"""
+Atomizer NX Open Hooks
+======================
+
+Direct Python hooks for NX CAD/CAE operations via NX Open API.
+
+This module provides a clean Python interface for manipulating NX parts
+programmatically. Each hook executes NX journals via `run_journal.exe`
+and returns structured JSON results.
+
+Modules
+-------
+nx_cad : CAD manipulation hooks
+    - part_manager : Open, close, save parts
+    - expression_manager : Get/set design parameters
+    - geometry_query : Mass properties, bodies, volumes
+    - feature_manager : Suppress/unsuppress features
+
+nx_cae : CAE/Simulation hooks (Phase 2)
+    - solver_manager : BDF export, solve simulations
+
+Quick Start
+-----------
+>>> from optimization_engine.hooks.nx_cad import expression_manager
+>>> result = expression_manager.get_expressions("C:/model.prt")
+>>> if result["success"]:
+...     for name, expr in result["data"]["expressions"].items():
+...         print(f"{name} = {expr['value']}")
+
+>>> from optimization_engine.hooks.nx_cae import solver_manager
+>>> result = solver_manager.get_bdf_from_solution_folder("C:/model.sim")
+
+Requirements
+------------
+- Siemens NX 2506+ installed
+- NX_BIN_PATH environment variable (or default path)
+- Python 3.8+ with atomizer conda environment
+
+See Also
+--------
+- optimization_engine/hooks/README.md : Full documentation
+- docs/plans/NX_OPEN_AUTOMATION_ROADMAP.md : Development roadmap
+
+Version
+-------
+1.1.0 (2025-12-06) - Added nx_cae module with solver_manager
+1.0.0 (2025-12-06) - Initial release with nx_cad hooks
+"""
+
+from .nx_cad import (
+    part_manager,
+    expression_manager,
+    geometry_query,
+    feature_manager,
+)
+
+from .nx_cae import (
+    solver_manager,
+)
+
+__all__ = [
+    # CAD hooks
+    'part_manager',
+    'expression_manager',
+    'geometry_query',
+    'feature_manager',
+    # CAE hooks
+    'solver_manager',
+]
+
+__version__ = '1.1.0'
+__author__ = 'Atomizer'