feat: Add substudy system with live history tracking and workflow fixes

Major Features:
- Hierarchical substudy system (like NX Solutions/Subcases)
  * Shared model files across all substudies
  * Independent configuration per substudy
  * Continuation support from previous substudies
  * Real-time incremental history updates
- Live history tracking with optimization_history_incremental.json
- Complete bracket_displacement_maximizing study with substudy examples

Core Fixes:
- Fixed expression update workflow to pass design_vars through simulation_runner
  * Restored working NX journal expression update mechanism
  * OP2 timestamp verification instead of file deletion
  * Resolved issue where all trials returned identical objective values
- Fixed LLMOptimizationRunner to pass design variables to simulation runner
- Enhanced NXSolver with timestamp-based file regeneration verification

New Components:
- optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner
- optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard
- studies/bracket_displacement_maximizing/ - Complete substudy example
  * run_substudy.py - Substudy runner with continuation
  * run_optimization.py - Standalone optimization runner
  * config/substudy_template.json - Template for new substudies
  * substudies/coarse_exploration/ - 20-trial coarse search
  * substudies/fine_tuning/ - 50-trial refinement (continuation example)
  * SUBSTUDIES_README.md - Complete substudy documentation

Technical Improvements:
- Incremental history saving after each trial (optimization_history_incremental.json)
- Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve
- Trial indexing fix in substudy result saving
- Updated README with substudy system documentation

Testing:
- Successfully ran 20-trial coarse_exploration substudy
- Verified different objective values across trials (workflow fix validated)
- Confirmed live history updates in real-time
- Tested shared model file usage across substudies

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

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

optimization_engine/nx_updater.py

@@ -88,6 +88,24 @@ class NXParameterUpdater:
 
         return expressions
 
+    def get_all_expressions(self) -> Dict[str, Dict[str, any]]:
+        """
+        Get all expressions as a dictionary.
+
+        Returns:
+            Dict mapping expression name to info dict with 'value', 'units', 'type'
+        """
+        expressions_list = self.find_expressions()
+        return {
+            expr['name']: {
+                'value': expr['value'],
+                'units': expr['units'],
+                'type': expr['type'],
+                'formula': None  # Binary .prt files don't have formulas accessible
+            }
+            for expr in expressions_list
+        }
+
     def update_expression(self, name: str, new_value: float) -> bool:
         """
         Update a single expression value.