fix: Complete stress extraction fix for NX Nastran OP2 files

THREE critical fixes applied:

1. API Access Pattern
   - Support dotted attribute names (e.g., 'stress.chexa_stress')
   - Compatible with newer pyNastran versions (NX 2412.5)
   - Fallback to older API formats for compatibility

2. Correct Von Mises Index
   - Solid elements (CHEXA, CTETRA, CPENTA): index 9
   - Shell elements (CQUAD4, CTRIA3): last column
   - Data structure: [oxx, oyy, ozz, txy, tyz, txz, o1, o2, o3, von_mises]

3. Units Conversion (CRITICAL)
   - NX Nastran outputs stress in kPa, not MPa
   - Apply conversion: kPa / 1000 = MPa
   - Example: 113094.73 kPa -> 113.09 MPa

Test Results:
- Before: 0.00 MPa (FAIL)
- After:  113.09 MPa at element 83 (SUCCESS)

Files modified:
- optimization_engine/result_extractors/op2_extractor_example.py

Test files added:
- examples/test_stress_direct.py
- examples/test_stress_fix.py
- examples/debug_op2_stress.py
- STRESS_EXTRACTION_FIXED.md
- TESTING_STRESS_FIX.md

optimization_engine/result_extractors/op2_extractor_example.py

@@ -71,7 +71,7 @@ def extract_max_stress(op2_path: Path, stress_type: str = 'von_mises') -> Dict[s
     """
     from pyNastran.op2.op2 import OP2
 
-    op2 = OP2()
+    op2 = OP2(debug=False)
     op2.read_op2(str(op2_path))
 
     # Stress can be in different tables depending on element type
@@ -81,6 +81,7 @@ def extract_max_stress(op2_path: Path, stress_type: str = 'von_mises') -> Dict[s
         'ctria3_stress',
         'ctetra_stress',
         'chexa_stress',
+        'cpenta_stress',
         'cbar_stress',
         'cbeam_stress'
     ]
@@ -89,37 +90,64 @@ def extract_max_stress(op2_path: Path, stress_type: str = 'von_mises') -> Dict[s
     max_element_id = None
     max_element_type = None
 
+    # Try to get stress from different pyNastran API formats
     for table_name in stress_tables:
-        if hasattr(op2, table_name):
+        stress_table = None
+
+        # Try format 1: Attribute name with dot (e.g., 'stress.chexa_stress')
+        # This is used in newer pyNastran versions
+        dotted_name = f'stress.{table_name}'
+        if hasattr(op2, dotted_name):
+            stress_table = getattr(op2, dotted_name)
+        # Try format 2: Nested attribute op2.stress.chexa_stress
+        elif hasattr(op2, 'stress') and hasattr(op2.stress, table_name):
+            stress_table = getattr(op2.stress, table_name)
+        # Try format 3: Direct attribute op2.chexa_stress (older pyNastran)
+        elif hasattr(op2, table_name):
             stress_table = getattr(op2, table_name)
-            if stress_table:
-                subcase_id = list(stress_table.keys())[0]
-                stress_data = stress_table[subcase_id]
 
-                # Extract von Mises stress
-                # Note: Structure varies by element type
-                element_ids = stress_data.element_node[:, 0].astype(int)
+        if stress_table:
+            subcase_id = list(stress_table.keys())[0]
+            stress_data = stress_table[subcase_id]
 
-                if stress_type == 'von_mises':
-                    # von Mises is usually last column
-                    stresses = stress_data.data[0, :, -1]  # timestep 0, all elements, last column
+            # Extract von Mises stress
+            # Note: Structure varies by element type
+            element_ids = stress_data.element_node[:, 0].astype(int)
+
+            if stress_type == 'von_mises':
+                # For solid elements (CHEXA, CTETRA, CPENTA): von Mises is at index 9
+                # For shell elements (CQUAD4, CTRIA3): von Mises is last column (-1)
+                if table_name in ['chexa_stress', 'ctetra_stress', 'cpenta_stress']:
+                    # Solid elements: data shape is [itime, nnodes, 10]
+                    # Index 9 is von_mises [oxx, oyy, ozz, txy, tyz, txz, o1, o2, o3, von_mises]
+                    stresses = stress_data.data[0, :, 9]
+                else:
+                    # Shell elements: von Mises is last column
+                    stresses = stress_data.data[0, :, -1]
+            else:
+                # Max principal stress
+                if table_name in ['chexa_stress', 'ctetra_stress', 'cpenta_stress']:
+                    stresses = stress_data.data[0, :, 6]  # o1 (max principal)
                 else:
-                    # Max principal stress (second-to-last column typically)
                     stresses = stress_data.data[0, :, -2]
 
-                max_stress_in_table = np.max(stresses)
-                if max_stress_in_table > max_stress_overall:
-                    max_stress_overall = max_stress_in_table
-                    max_idx = np.argmax(stresses)
-                    max_element_id = element_ids[max_idx]
-                    max_element_type = table_name.replace('_stress', '')
+            max_stress_in_table = np.max(stresses)
+            if max_stress_in_table > max_stress_overall:
+                max_stress_overall = max_stress_in_table
+                max_idx = np.argmax(stresses)
+                max_element_id = element_ids[max_idx]
+                max_element_type = table_name.replace('_stress', '')
+
+    # CRITICAL: NX Nastran outputs stress in kPa (mN/mm²), convert to MPa
+    # 1 kPa = 0.001 MPa
+    max_stress_overall_mpa = max_stress_overall / 1000.0
 
     return {
-        'max_stress': float(max_stress_overall),
+        'max_stress': float(max_stress_overall_mpa),
         'stress_type': stress_type,
         'element_id': int(max_element_id) if max_element_id else None,
         'element_type': max_element_type,
-        'units': 'MPa',  # NX typically uses MPa
+        'units': 'MPa',
     }