feat: Add AtomizerField training data export and intelligent model discovery

Major additions:
- Training data export system for AtomizerField neural network training
- Bracket stiffness optimization study with 50+ training samples
- Intelligent NX model discovery (auto-detect solutions, expressions, mesh)
- Result extractors module for displacement, stress, frequency, mass
- User-generated NX journals for advanced workflows
- Archive structure for legacy scripts and test outputs
- Protocol documentation and dashboard launcher

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

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

optimization_engine/extractors/extract_mass_from_expression.py

@@ -0,0 +1,71 @@
+"""
+Extract mass from NX measure expression
+
+This extractor reads mass from a temp file written by solve_simulation.py journal.
+The journal extracts the mass from expression p173 and writes it to _temp_mass.txt
+"""
+
+from pathlib import Path
+from typing import Dict, Any
+import sys
+
+
+def extract_mass_from_expression(prt_file: Path, expression_name: str = "p173") -> float:
+    """
+    Extract mass from NX expression by reading temp file.
+
+    The solve_simulation.py journal extracts the p173 expression value
+    and writes it to _temp_mass.txt in the model directory.
+
+    Args:
+        prt_file: Path to .prt file with mass expression
+        expression_name: Name of the expression containing mass (default: "p173")
+
+    Returns:
+        Mass in kilograms
+    """
+    prt_file = Path(prt_file)
+
+    if not prt_file.exists():
+        raise FileNotFoundError(f"Part file not found: {prt_file}")
+
+    # The mass is written to _temp_mass.txt in the same directory as the .prt
+    model_dir = prt_file.parent
+    mass_file = model_dir / "_temp_mass.txt"
+
+    if not mass_file.exists():
+        raise FileNotFoundError(
+            f"Mass temp file not found: {mass_file}\n"
+            f"The solve_simulation.py journal should have created this file."
+        )
+
+    # Read mass from file
+    try:
+        with open(mass_file, 'r') as f:
+            mass_kg = float(f.read().strip())
+
+        print(f"[OK] Mass from {expression_name}: {mass_kg:.6f} kg ({mass_kg * 1000:.2f} g)")
+        return mass_kg
+
+    except ValueError as e:
+        raise ValueError(f"Could not parse mass from {mass_file}: {e}")
+    except Exception as e:
+        raise RuntimeError(f"Failed to read mass file: {e}")
+
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        prt_file = Path(sys.argv[1])
+        expression_name = sys.argv[2] if len(sys.argv) > 2 else "p173"
+    else:
+        print(f"Usage: python {sys.argv[0]} <prt_file> [expression_name]")
+        sys.exit(1)
+
+    try:
+        mass_kg = extract_mass_from_expression(prt_file, expression_name)
+        print(f"\nMass: {mass_kg:.6f} kg ({mass_kg * 1000:.2f} g)")
+    except Exception as e:
+        print(f"\nERROR: {e}")
+        import traceback
+        traceback.print_exc()
+        sys.exit(1)