diff --git a/docs/OPTIMIZATION_WORKFLOW.md b/docs/OPTIMIZATION_WORKFLOW.md
new file mode 100644
index 00000000..c9b71784
Binary files /dev/null and b/docs/OPTIMIZATION_WORKFLOW.md differ
diff --git a/docs/QUICK_CONFIG_REFERENCE.md b/docs/QUICK_CONFIG_REFERENCE.md
new file mode 100644
index 00000000..810b1a9e
--- /dev/null
+++ b/docs/QUICK_CONFIG_REFERENCE.md
@@ -0,0 +1,81 @@
+# Quick Configuration Reference
+
+## Change NX Version (e.g., when NX 2506 is released)
+
+**Edit ONE file**: [`config.py`](../config.py)
+
+```python
+# Line 14-15
+NX_VERSION = "2506"  # ← Change this
+NX_INSTALLATION_DIR = Path(f"C:/Program Files/Siemens/NX{NX_VERSION}")
+```
+
+**That's it!** All modules automatically use new paths.
+
+---
+
+## Change Python Environment
+
+**Edit ONE file**: [`config.py`](../config.py)
+
+```python
+# Line 49
+PYTHON_ENV_NAME = "my_new_env"  # ← Change this
+```
+
+---
+
+## Verify Configuration
+
+```bash
+python config.py
+```
+
+Output shows all paths and validates they exist.
+
+---
+
+## Using Config in Your Code
+
+```python
+from config import (
+    NX_RUN_JOURNAL,       # Path to run_journal.exe
+    NX_MATERIAL_LIBRARY,  # Path to material library XML
+    PYTHON_ENV_NAME,      # Current environment name
+    get_nx_journal_command,  # Helper function
+)
+
+# Generate journal command
+cmd = get_nx_journal_command(
+    journal_script,
+    arg1,
+    arg2
+)
+```
+
+---
+
+##  What Changed?
+
+**OLD** (hardcoded paths in multiple files):
+- `optimization_engine/nx_updater.py`: Line 66
+- `dashboard/api/app.py`: Line 598
+- `README.md`: Line 92
+- `docs/NXOPEN_INTELLISENSE_SETUP.md`: Line 269
+- ...and more
+
+**NEW** (all use `config.py`):
+- Edit `config.py` once
+- All files automatically updated
+
+---
+
+## Files Using Config
+
+- ✅ `optimization_engine/nx_updater.py`
+- ✅ `dashboard/api/app.py`
+- Future: All NX-related modules will use config
+
+---
+
+**See also**: [SYSTEM_CONFIGURATION.md](SYSTEM_CONFIGURATION.md) for full documentation
diff --git a/nx_journals/user_generated_journals/expressions_from_journal.exp b/nx_journals/user_generated_journals/expressions_from_journal.exp
new file mode 100644
index 00000000..01a5d7fd
--- /dev/null
+++ b/nx_journals/user_generated_journals/expressions_from_journal.exp
@@ -0,0 +1,31 @@
+// Version:  3
+Pattern_p7=hole_count
+[MilliMeter]Pattern_p8=444.444444444444
+[MilliMeter]Pattern_p9=p6
+Pattern_p10=1
+[MilliMeter]Pattern_p11=10
+[MilliMeter]Pattern_p12=0
+[MilliMeter]beam_face_thickness=20
+[MilliMeter]beam_half_core_thickness=20
+[MilliMeter]beam_half_height=250
+[MilliMeter]beam_half_width=150
+[MilliMeter]beam_lenght=5000
+hole_count=10
+[MilliMeter]holes_diameter=400
+[MilliMeter]p4=beam_lenght
+[MilliMeter]p5=0
+[MilliMeter]p6=4000
+[Degrees]p13=0
+[MilliMeter]p19=4000
+[MilliMeter]p34=4000
+[MilliMeter]p50=4000
+[MilliMeter]p119=4000
+p130=10
+[MilliMeter]p132=444.444444444444
+[MilliMeter]p134=4000
+[MilliMeter]p135=4000
+p137=1
+[MilliMeter]p139=10
+[MilliMeter]p141=0
+[Degrees]p143=0
+[Kilogram]p173=973.968443678471
diff --git a/nx_journals/user_generated_journals/journal_export_part_expressions.py b/nx_journals/user_generated_journals/journal_export_part_expressions.py
new file mode 100644
index 00000000..4d4840ac
--- /dev/null
+++ b/nx_journals/user_generated_journals/journal_export_part_expressions.py
@@ -0,0 +1,45 @@
+# NX 2412
+# Journal created by antoi on Mon Nov 17 11:00:55 2025 Eastern Standard Time
+#
+import math
+import NXOpen
+def main(args) : 
+
+    theSession  = NXOpen.Session.GetSession() #type: NXOpen.Session
+    workPart = theSession.Parts.Work
+    displayPart = theSession.Parts.Display
+    # ----------------------------------------------
+    #   Menu: Tools->Utilities->Expressions...
+    # ----------------------------------------------
+    markId1 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Visible, "Start")
+    
+    theSession.SetUndoMarkName(markId1, "Expressions Dialog")
+    
+    workPart.Expressions.ExportToFile(NXOpen.ExpressionCollection.ExportMode.WorkPart, "C:\\Users\\antoi\\Documents\\Atomaste\\Atomizer\\nx_journals\\user_generated_journals\\expressions_from_journal", NXOpen.ExpressionCollection.SortType.AlphaNum)
+    
+    markId2 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Expressions")
+    
+    theSession.DeleteUndoMark(markId2, None)
+    
+    markId3 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Expressions")
+    
+    markId4 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Make Up to Date")
+    
+    markId5 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "NX update")
+    
+    nErrs1 = theSession.UpdateManager.DoUpdate(markId5)
+    
+    theSession.DeleteUndoMark(markId5, "NX update")
+    
+    theSession.DeleteUndoMark(markId4, None)
+    
+    theSession.DeleteUndoMark(markId3, None)
+    
+    theSession.SetUndoMarkName(markId1, "Expressions")
+    
+    # ----------------------------------------------
+    #   Menu: Tools->Automation->Journal->Stop Recording
+    # ----------------------------------------------
+    
+if __name__ == '__main__':
+    main(sys.argv[1:])
\ No newline at end of file
diff --git a/nx_journals/user_generated_journals/journal_import_part_expressions.py b/nx_journals/user_generated_journals/journal_import_part_expressions.py
new file mode 100644
index 00000000..d70c3431
--- /dev/null
+++ b/nx_journals/user_generated_journals/journal_import_part_expressions.py
@@ -0,0 +1,49 @@
+# NX 2412
+# Journal created by antoi on Mon Nov 17 12:16:50 2025 Eastern Standard Time
+#
+import math
+import NXOpen
+def main(args) : 
+
+    theSession  = NXOpen.Session.GetSession() #type: NXOpen.Session
+    workPart = theSession.Parts.Work
+    displayPart = theSession.Parts.Display
+    # ----------------------------------------------
+    #   Menu: Tools->Utilities->Expressions...
+    # ----------------------------------------------
+    markId1 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Visible, "Start")
+    
+    theSession.SetUndoMarkName(markId1, "Expressions Dialog")
+    
+    markId2 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Visible, "Import Expressions")
+    
+    expModified1, errorMessages1 = workPart.Expressions.ImportFromFile("C:\\Users\\antoi\\Documents\\Atomaste\\Atomizer\\nx_journals\\user_generated_journals\\study_variables_expressions_from_journal.exp", NXOpen.ExpressionCollection.ImportMode.Replace)
+    
+    markId3 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Expressions")
+    
+    theSession.DeleteUndoMark(markId3, None)
+    
+    markId4 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Expressions")
+    
+    markId5 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Make Up to Date")
+    
+    markId6 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "NX update")
+    
+    nErrs1 = theSession.UpdateManager.DoUpdate(markId6)
+    
+    theSession.DeleteUndoMark(markId6, "NX update")
+    
+    theSession.DeleteUndoMark(markId5, None)
+    
+    theSession.DeleteUndoMark(markId4, None)
+    
+    theSession.SetUndoMarkName(markId1, "Expressions")
+    
+    theSession.DeleteUndoMark(markId2, None)
+    
+    # ----------------------------------------------
+    #   Menu: Tools->Automation->Journal->Stop Recording
+    # ----------------------------------------------
+    
+if __name__ == '__main__':
+    main(sys.argv[1:])
\ No newline at end of file
diff --git a/nx_journals/user_generated_journals/journal_load_from_folder.py b/nx_journals/user_generated_journals/journal_load_from_folder.py
new file mode 100644
index 00000000..b6f54f45
--- /dev/null
+++ b/nx_journals/user_generated_journals/journal_load_from_folder.py
@@ -0,0 +1,74 @@
+# NX 2412
+# Journal created by antoi on Mon Nov 17 10:26:53 2025 Eastern Standard Time
+#
+import math
+import NXOpen
+import NXOpen.CAE
+def main(args) : 
+
+    theSession  = NXOpen.Session.GetSession() #type: NXOpen.Session
+    workSimPart = theSession.Parts.BaseWork
+    displaySimPart = theSession.Parts.BaseDisplay
+    # ----------------------------------------------
+    #   Menu: File->Options->Assembly Load Options...
+    # ----------------------------------------------
+    markId1 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Start")
+    
+    theSession.SetUndoMarkName(markId1, "Assembly Load Options Dialog")
+    
+    markId2 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Assembly Load Options")
+    
+    theSession.DeleteUndoMark(markId2, None)
+    
+    markId3 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Assembly Load Options")
+    
+    theSession.Parts.LoadOptions.LoadLatest = False
+    
+    theSession.Parts.LoadOptions.ComponentLoadMethod = NXOpen.LoadOptions.LoadMethod.FromDirectory
+    
+    searchDirectories1 = [None] * 1 
+    searchDirectories1[0] = "C:\\ProgramData"
+    searchSubDirs1 = [None] * 1 
+    searchSubDirs1[0] = True
+    theSession.Parts.LoadOptions.SetSearchDirectories(searchDirectories1, searchSubDirs1)
+    
+    theSession.Parts.LoadOptions.ComponentsToLoad = NXOpen.LoadOptions.LoadComponents.All
+    
+    theSession.Parts.LoadOptions.PartLoadOption = NXOpen.LoadOptions.LoadOption.FullyLoad
+    
+    theSession.Parts.LoadOptions.SetInterpartData(True, NXOpen.LoadOptions.Parent.All)
+    
+    theSession.Parts.LoadOptions.AllowSubstitution = False
+    
+    theSession.Parts.LoadOptions.GenerateMissingPartFamilyMembers = True
+    
+    theSession.Parts.LoadOptions.AbortOnFailure = False
+    
+    theSession.Parts.LoadOptions.OptionUpdateSubsetOnLoad = NXOpen.LoadOptions.UpdateSubsetOnLoad.NotSet
+    
+    referenceSets1 = [None] * 5 
+    referenceSets1[0] = "As Saved"
+    referenceSets1[1] = "Use Simplified"
+    referenceSets1[2] = "Use Model"
+    referenceSets1[3] = "Entire Part"
+    referenceSets1[4] = "Empty"
+    theSession.Parts.LoadOptions.SetDefaultReferenceSets(referenceSets1)
+    
+    theSession.Parts.LoadOptions.ReferenceSetOverride = False
+    
+    theSession.Parts.LoadOptions.SetBookmarkComponentsToLoad(True, False, NXOpen.LoadOptions.BookmarkComponents.LoadVisible)
+    
+    theSession.Parts.LoadOptions.BookmarkRefsetLoadBehavior = NXOpen.LoadOptions.BookmarkRefsets.ImportData
+    
+    theSession.DeleteUndoMark(markId3, None)
+    
+    theSession.SetUndoMarkName(markId1, "Assembly Load Options")
+    
+    theSession.DeleteUndoMark(markId1, None)
+    
+    # ----------------------------------------------
+    #   Menu: Tools->Automation->Journal->Stop Recording
+    # ----------------------------------------------
+    
+if __name__ == '__main__':
+    main(sys.argv[1:])
\ No newline at end of file
diff --git a/nx_journals/user_generated_journals/study_variables_expressions_from_journal.exp b/nx_journals/user_generated_journals/study_variables_expressions_from_journal.exp
new file mode 100644
index 00000000..68adbf3f
--- /dev/null
+++ b/nx_journals/user_generated_journals/study_variables_expressions_from_journal.exp
@@ -0,0 +1,6 @@
+[MilliMeter]beam_face_thickness=20
+[MilliMeter]beam_half_core_thickness=20
+hole_count=10
+[MilliMeter]holes_diameter=400
+
+
diff --git a/optimization_engine/benchmarking_substudy.py b/optimization_engine/benchmarking_substudy.py
new file mode 100644
index 00000000..34ea176e
--- /dev/null
+++ b/optimization_engine/benchmarking_substudy.py
@@ -0,0 +1,472 @@
+"""
+Benchmarking Substudy - Mandatory Discovery & Validation System
+
+The benchmarking substudy is a mandatory first step for all optimization studies.
+It performs model introspection, validation, and configuration proposal before
+any optimization trials are run.
+
+Purpose:
+- Discover available expressions, OP2 contents, baseline performance
+- Validate that model can be simulated and results extracted
+- Propose initial optimization configuration
+- Act as gatekeeper before full optimization
+
+This substudy ALWAYS runs before any other substudy and auto-updates when
+new substudies are created.
+
+Author: Antoine Letarte
+Date: 2025-11-17
+Version: 1.0.0
+"""
+
+import json
+import logging
+from pathlib import Path
+from typing import Dict, Any, List, Optional
+from dataclasses import dataclass, asdict
+from datetime import datetime
+
+from optimization_engine.optimization_setup_wizard import OptimizationSetupWizard, ModelIntrospection, OP2Introspection
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class BenchmarkResults:
+    """Results from benchmarking analysis."""
+    timestamp: str
+
+    # Model introspection
+    expressions: Dict[str, Dict[str, Any]]  # name -> {value, units, formula}
+    expression_count: int
+
+    # OP2 introspection
+    element_types: List[str]
+    result_types: List[str]
+    subcases: List[int]
+    node_count: int
+    element_count: int
+
+    # Baseline simulation results
+    baseline_op2_path: str
+    baseline_results: Dict[str, float]  # e.g., max_stress, max_displacement, mass
+
+    # Validation status
+    simulation_works: bool
+    extraction_works: bool
+    validation_passed: bool
+
+    # Proposals
+    proposed_design_variables: List[Dict[str, Any]]
+    proposed_extractors: List[Dict[str, Any]]
+    proposed_objectives: List[str]
+
+    # Issues found
+    warnings: List[str]
+    errors: List[str]
+
+
+class BenchmarkingSubstudy:
+    """
+    Mandatory benchmarking substudy for discovery and validation.
+
+    This runs before any optimization to:
+    1. Discover what's in the model
+    2. Validate the pipeline works
+    3. Propose configuration
+    4. Gate-keep before optimization
+    """
+
+    def __init__(self, study_dir: Path, prt_file: Path, sim_file: Path):
+        """
+        Initialize benchmarking substudy.
+
+        Args:
+            study_dir: Root study directory
+            prt_file: Path to NX part file
+            sim_file: Path to NX simulation file
+        """
+        self.study_dir = Path(study_dir)
+        self.prt_file = Path(prt_file)
+        self.sim_file = Path(sim_file)
+
+        # Benchmarking substudy directory
+        self.benchmark_dir = self.study_dir / "substudies" / "benchmarking"
+        self.benchmark_dir.mkdir(parents=True, exist_ok=True)
+
+        # Results file
+        self.results_file = self.benchmark_dir / "benchmark_results.json"
+
+        # Use Phase 3.3 wizard for introspection
+        self.wizard = OptimizationSetupWizard(prt_file, sim_file)
+
+        logger.info(f"Benchmarking substudy initialized for: {study_dir.name}")
+
+    def run_discovery(self) -> BenchmarkResults:
+        """
+        Run complete discovery and validation.
+
+        Returns:
+            BenchmarkResults with all discovery information
+        """
+        logger.info("=" * 80)
+        logger.info("BENCHMARKING SUBSTUDY - Discovery & Validation")
+        logger.info("=" * 80)
+        logger.info("")
+
+        results = BenchmarkResults(
+            timestamp=datetime.now().isoformat(),
+            expressions={},
+            expression_count=0,
+            element_types=[],
+            result_types=[],
+            subcases=[],
+            node_count=0,
+            element_count=0,
+            baseline_op2_path="",
+            baseline_results={},
+            simulation_works=False,
+            extraction_works=False,
+            validation_passed=False,
+            proposed_design_variables=[],
+            proposed_extractors=[],
+            proposed_objectives=[],
+            warnings=[],
+            errors=[]
+        )
+
+        # Step 1: Model Introspection
+        logger.info("Step 1: Model Introspection")
+        logger.info("-" * 40)
+        try:
+            model_info = self.wizard.introspect_model()
+            results.expressions = model_info.expressions
+            results.expression_count = len(model_info.expressions)
+
+            logger.info(f"Found {results.expression_count} expressions:")
+            for name, info in model_info.expressions.items():
+                logger.info(f"  - {name}: {info['value']} {info['units']}")
+            logger.info("")
+        except Exception as e:
+            error_msg = f"Model introspection failed: {e}"
+            logger.error(error_msg)
+            results.errors.append(error_msg)
+            results.validation_passed = False
+            return results
+
+        # Step 2: Baseline Simulation
+        logger.info("Step 2: Baseline Simulation")
+        logger.info("-" * 40)
+        try:
+            baseline_op2 = self.wizard.run_baseline_simulation()
+            if baseline_op2:
+                results.baseline_op2_path = str(baseline_op2)
+                results.simulation_works = True
+                logger.info(f"Baseline simulation complete: {baseline_op2.name}")
+                logger.info("")
+            else:
+                warning_msg = "Baseline simulation returned no OP2 file"
+                logger.warning(warning_msg)
+                results.warnings.append(warning_msg)
+                logger.info("")
+        except Exception as e:
+            error_msg = f"Baseline simulation failed: {e}"
+            logger.error(error_msg)
+            results.errors.append(error_msg)
+            logger.info("Continuing with available information...")
+            logger.info("")
+
+        # Step 3: OP2 Introspection
+        logger.info("Step 3: OP2 Introspection")
+        logger.info("-" * 40)
+        try:
+            op2_info = self.wizard.introspect_op2()
+            results.element_types = op2_info.element_types
+            results.result_types = op2_info.result_types
+            results.subcases = op2_info.subcases
+            results.node_count = op2_info.node_count
+            results.element_count = op2_info.element_count
+
+            logger.info(f"OP2 Analysis:")
+            logger.info(f"  - Element types: {', '.join(results.element_types)}")
+            logger.info(f"  - Result types: {', '.join(results.result_types)}")
+            logger.info(f"  - Subcases: {results.subcases}")
+            logger.info(f"  - Nodes: {results.node_count}")
+            logger.info(f"  - Elements: {results.element_count}")
+            logger.info("")
+        except Exception as e:
+            error_msg = f"OP2 introspection failed: {e}"
+            logger.error(error_msg)
+            results.errors.append(error_msg)
+            results.validation_passed = False
+            return results
+
+        # Step 4: Extract Baseline Results
+        logger.info("Step 4: Extract Baseline Results")
+        logger.info("-" * 40)
+        try:
+            # Try to extract common results
+            baseline_results = self._extract_baseline_results(Path(results.baseline_op2_path))
+            results.baseline_results = baseline_results
+            results.extraction_works = True
+
+            logger.info("Baseline performance:")
+            for key, value in baseline_results.items():
+                logger.info(f"  - {key}: {value}")
+            logger.info("")
+        except Exception as e:
+            warning_msg = f"Baseline extraction partially failed: {e}"
+            logger.warning(warning_msg)
+            results.warnings.append(warning_msg)
+            # Not a hard failure - continue
+
+        # Step 5: Generate Proposals
+        logger.info("Step 5: Generate Configuration Proposals")
+        logger.info("-" * 40)
+        proposals = self._generate_proposals(model_info, op2_info, results.baseline_results)
+        results.proposed_design_variables = proposals['design_variables']
+        results.proposed_extractors = proposals['extractors']
+        results.proposed_objectives = proposals['objectives']
+
+        logger.info(f"Proposed design variables ({len(results.proposed_design_variables)}):")
+        for var in results.proposed_design_variables:
+            logger.info(f"  - {var['parameter']}: {var.get('suggested_range', 'range needed')}")
+
+        logger.info(f"\nProposed extractors ({len(results.proposed_extractors)}):")
+        for ext in results.proposed_extractors:
+            logger.info(f"  - {ext['action']}: {ext['description']}")
+
+        logger.info(f"\nProposed objectives ({len(results.proposed_objectives)}):")
+        for obj in results.proposed_objectives:
+            logger.info(f"  - {obj}")
+        logger.info("")
+
+        # Validation passed if simulation and basic extraction work
+        results.validation_passed = results.simulation_works and len(results.element_types) > 0
+
+        # Save results
+        self._save_results(results)
+
+        logger.info("=" * 80)
+        if results.validation_passed:
+            logger.info("BENCHMARKING COMPLETE - Validation PASSED")
+        else:
+            logger.info("BENCHMARKING COMPLETE - Validation FAILED")
+        logger.info("=" * 80)
+        logger.info("")
+
+        return results
+
+    def _extract_baseline_results(self, op2_file: Path) -> Dict[str, float]:
+        """Extract baseline results from OP2 file."""
+        from pyNastran.op2.op2 import OP2
+
+        results = {}
+
+        try:
+            op2 = OP2()
+            op2.read_op2(str(op2_file), load_geometry=False)
+
+            # Try to extract displacement
+            if hasattr(op2, 'displacements') and op2.displacements:
+                disp_data = list(op2.displacements.values())[0]
+                if hasattr(disp_data, 'data'):
+                    max_disp = float(abs(disp_data.data).max())
+                    results['max_displacement'] = round(max_disp, 6)
+
+            # Try to extract stress
+            if hasattr(op2, 'ctetra_stress') and op2.ctetra_stress:
+                stress_data = list(op2.ctetra_stress.values())[0]
+                if hasattr(stress_data, 'data'):
+                    max_stress = float(abs(stress_data.data).max())
+                    results['max_von_mises'] = round(max_stress, 3)
+            elif hasattr(op2, 'chexa_stress') and op2.chexa_stress:
+                stress_data = list(op2.chexa_stress.values())[0]
+                if hasattr(stress_data, 'data'):
+                    max_stress = float(abs(stress_data.data).max())
+                    results['max_von_mises'] = round(max_stress, 3)
+
+        except Exception as e:
+            logger.warning(f"Could not extract all baseline results: {e}")
+
+        return results
+
+    def _generate_proposals(self, model_info: ModelIntrospection, op2_info: OP2Introspection,
+                           baseline_results: Dict[str, float]) -> Dict[str, Any]:
+        """Generate configuration proposals based on discovery."""
+        proposals = {
+            'design_variables': [],
+            'extractors': [],
+            'objectives': []
+        }
+
+        # Propose design variables from expressions
+        # Filter out likely constants (e.g., material properties, loads)
+        constant_keywords = ['modulus', 'poisson', 'density', 'load', 'force', 'pressure']
+
+        for name, info in model_info.expressions.items():
+            # Skip if likely a constant
+            if any(keyword in name.lower() for keyword in constant_keywords):
+                continue
+
+            # Propose as design variable
+            proposals['design_variables'].append({
+                'parameter': name,
+                'current_value': info['value'],
+                'units': info['units'],
+                'suggested_range': f"±20% of {info['value']} {info['units']}"
+            })
+
+        # Propose extractors based on OP2 contents
+        if 'displacement' in op2_info.result_types or 'DISPLACEMENT' in op2_info.result_types:
+            proposals['extractors'].append({
+                'action': 'extract_displacement',
+                'description': 'Extract displacement results from OP2 file',
+                'params': {'result_type': 'displacement'}
+            })
+            proposals['objectives'].append('max_displacement (minimize or maximize)')
+
+        if op2_info.element_types:
+            element_type = op2_info.element_types[0].lower()
+            proposals['extractors'].append({
+                'action': 'extract_solid_stress',
+                'description': f'Extract stress from {element_type.upper()} elements',
+                'params': {
+                    'result_type': 'stress',
+                    'element_type': element_type
+                }
+            })
+            proposals['objectives'].append('max_von_mises (minimize for safety)')
+
+        return proposals
+
+    def _save_results(self, results: BenchmarkResults):
+        """Save benchmark results to JSON file."""
+        import numpy as np
+
+        results_dict = asdict(results)
+
+        # Convert numpy types to native Python types for JSON serialization
+        def convert_numpy(obj):
+            if isinstance(obj, np.integer):
+                return int(obj)
+            elif isinstance(obj, np.floating):
+                return float(obj)
+            elif isinstance(obj, np.ndarray):
+                return obj.tolist()
+            elif isinstance(obj, dict):
+                return {k: convert_numpy(v) for k, v in obj.items()}
+            elif isinstance(obj, list):
+                return [convert_numpy(item) for item in obj]
+            return obj
+
+        results_dict = convert_numpy(results_dict)
+
+        with open(self.results_file, 'w') as f:
+            json.dump(results_dict, f, indent=2)
+
+        logger.info(f"Benchmark results saved to: {self.results_file}")
+
+    def load_results(self) -> Optional[BenchmarkResults]:
+        """Load previous benchmark results if they exist."""
+        if not self.results_file.exists():
+            return None
+
+        with open(self.results_file, 'r') as f:
+            data = json.load(f)
+
+        return BenchmarkResults(**data)
+
+    def generate_report(self, results: BenchmarkResults) -> str:
+        """
+        Generate human-readable benchmark report.
+
+        Returns:
+            Markdown formatted report
+        """
+        report = []
+        report.append("# Benchmarking Report")
+        report.append("")
+        report.append(f"**Study**: {self.study_dir.name}")
+        report.append(f"**Date**: {results.timestamp}")
+        report.append(f"**Validation**: {'✅ PASSED' if results.validation_passed else '❌ FAILED'}")
+        report.append("")
+
+        report.append("## Model Introspection")
+        report.append("")
+        report.append(f"**Expressions Found**: {results.expression_count}")
+        report.append("")
+        report.append("| Expression | Value | Units |")
+        report.append("|------------|-------|-------|")
+        for name, info in results.expressions.items():
+            report.append(f"| {name} | {info['value']} | {info['units']} |")
+        report.append("")
+
+        report.append("## OP2 Analysis")
+        report.append("")
+        report.append(f"- **Element Types**: {', '.join(results.element_types)}")
+        report.append(f"- **Result Types**: {', '.join(results.result_types)}")
+        report.append(f"- **Subcases**: {results.subcases}")
+        report.append(f"- **Nodes**: {results.node_count}")
+        report.append(f"- **Elements**: {results.element_count}")
+        report.append("")
+
+        report.append("## Baseline Performance")
+        report.append("")
+        if results.baseline_results:
+            for key, value in results.baseline_results.items():
+                report.append(f"- **{key}**: {value}")
+        else:
+            report.append("*No baseline results extracted*")
+        report.append("")
+
+        report.append("## Configuration Proposals")
+        report.append("")
+
+        report.append("### Proposed Design Variables")
+        report.append("")
+        for var in results.proposed_design_variables:
+            report.append(f"- **{var['parameter']}**: {var['suggested_range']}")
+        report.append("")
+
+        report.append("### Proposed Extractors")
+        report.append("")
+        for ext in results.proposed_extractors:
+            report.append(f"- **{ext['action']}**: {ext['description']}")
+        report.append("")
+
+        report.append("### Proposed Objectives")
+        report.append("")
+        for obj in results.proposed_objectives:
+            report.append(f"- {obj}")
+        report.append("")
+
+        if results.warnings:
+            report.append("## Warnings")
+            report.append("")
+            for warning in results.warnings:
+                report.append(f"⚠️ {warning}")
+            report.append("")
+
+        if results.errors:
+            report.append("## Errors")
+            report.append("")
+            for error in results.errors:
+                report.append(f"❌ {error}")
+            report.append("")
+
+        return "\n".join(report)
+
+
+def main():
+    """Test benchmarking substudy."""
+    print("Benchmarking Substudy Test")
+    print("=" * 80)
+    print()
+    print("This module provides mandatory discovery and validation for all studies.")
+    print("Use it via the study setup workflow.")
+    print()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/optimization_engine/comprehensive_results_analyzer.py b/optimization_engine/comprehensive_results_analyzer.py
new file mode 100644
index 00000000..9ad9a817
--- /dev/null
+++ b/optimization_engine/comprehensive_results_analyzer.py
@@ -0,0 +1,393 @@
+"""
+Comprehensive Results Analyzer
+
+Performs thorough introspection of OP2, F06, and other Nastran output files
+to discover ALL available results, not just what we expect.
+
+This helps ensure we don't miss important data that's actually in the output files.
+"""
+
+from pathlib import Path
+from typing import Dict, Any, List, Optional
+import json
+from dataclasses import dataclass, asdict
+from pyNastran.op2.op2 import OP2
+
+
+@dataclass
+class OP2Contents:
+    """Complete inventory of OP2 file contents."""
+    file_path: str
+    subcases: List[int]
+
+    # Displacement results
+    displacement_available: bool
+    displacement_subcases: List[int]
+
+    # Stress results (by element type)
+    stress_results: Dict[str, List[int]]  # element_type -> [subcases]
+
+    # Strain results (by element type)
+    strain_results: Dict[str, List[int]]
+
+    # Force results
+    force_results: Dict[str, List[int]]
+
+    # Other results
+    other_results: Dict[str, Any]
+
+    # Grid point forces/stresses
+    grid_point_forces: List[int]
+    spc_forces: List[int]
+    mpc_forces: List[int]
+
+    # Summary
+    total_result_types: int
+    element_types_with_results: List[str]
+
+
+@dataclass
+class F06Contents:
+    """Complete inventory of F06 file contents."""
+    file_path: str
+    has_displacement: bool
+    has_stress: bool
+    has_strain: bool
+    has_forces: bool
+    element_types_found: List[str]
+    error_messages: List[str]
+    warning_messages: List[str]
+
+
+class ComprehensiveResultsAnalyzer:
+    """
+    Analyzes ALL Nastran output files to discover available results.
+
+    This is much more thorough than just checking expected results.
+    """
+
+    def __init__(self, output_dir: Path):
+        """
+        Initialize analyzer.
+
+        Args:
+            output_dir: Directory containing Nastran output files (.op2, .f06, etc.)
+        """
+        self.output_dir = Path(output_dir)
+
+    def analyze_op2(self, op2_file: Path) -> OP2Contents:
+        """
+        Comprehensively analyze OP2 file contents.
+
+        Args:
+            op2_file: Path to OP2 file
+
+        Returns:
+            OP2Contents with complete inventory
+        """
+        print(f"\n[OP2 ANALYSIS] Reading: {op2_file.name}")
+
+        model = OP2()
+        model.read_op2(str(op2_file))
+
+        # Discover all subcases
+        all_subcases = set()
+
+        # Check displacement
+        displacement_available = hasattr(model, 'displacements') and len(model.displacements) > 0
+        displacement_subcases = list(model.displacements.keys()) if displacement_available else []
+        all_subcases.update(displacement_subcases)
+
+        print(f"  Displacement: {'YES' if displacement_available else 'NO'}")
+        if displacement_subcases:
+            print(f"    Subcases: {displacement_subcases}")
+
+        # Check ALL stress results by scanning attributes
+        stress_results = {}
+        element_types_with_stress = []
+
+        # List of known stress attribute names (safer than scanning all attributes)
+        stress_attrs = [
+            'cquad4_stress', 'ctria3_stress', 'ctetra_stress', 'chexa_stress', 'cpenta_stress',
+            'cbar_stress', 'cbeam_stress', 'crod_stress', 'conrod_stress', 'ctube_stress',
+            'cshear_stress', 'cbush_stress', 'cgap_stress', 'celas1_stress', 'celas2_stress',
+            'celas3_stress', 'celas4_stress'
+        ]
+
+        for attr_name in stress_attrs:
+            if hasattr(model, attr_name):
+                try:
+                    stress_obj = getattr(model, attr_name)
+                    if isinstance(stress_obj, dict) and len(stress_obj) > 0:
+                        element_type = attr_name.replace('_stress', '')
+                        subcases = list(stress_obj.keys())
+                        stress_results[element_type] = subcases
+                        element_types_with_stress.append(element_type)
+                        all_subcases.update(subcases)
+                        print(f"  Stress [{element_type}]: YES")
+                        print(f"    Subcases: {subcases}")
+                except Exception as e:
+                    # Skip attributes that cause errors
+                    pass
+
+        if not stress_results:
+            print(f"  Stress: NO stress results found")
+
+        # Check ALL strain results
+        strain_results = {}
+        strain_attrs = [attr.replace('_stress', '_strain') for attr in stress_attrs]
+
+        for attr_name in strain_attrs:
+            if hasattr(model, attr_name):
+                try:
+                    strain_obj = getattr(model, attr_name)
+                    if isinstance(strain_obj, dict) and len(strain_obj) > 0:
+                        element_type = attr_name.replace('_strain', '')
+                        subcases = list(strain_obj.keys())
+                        strain_results[element_type] = subcases
+                        all_subcases.update(subcases)
+                        print(f"  Strain [{element_type}]: YES")
+                        print(f"    Subcases: {subcases}")
+                except Exception as e:
+                    pass
+
+        if not strain_results:
+            print(f"  Strain: NO strain results found")
+
+        # Check ALL force results
+        force_results = {}
+        force_attrs = [attr.replace('_stress', '_force') for attr in stress_attrs]
+
+        for attr_name in force_attrs:
+            if hasattr(model, attr_name):
+                try:
+                    force_obj = getattr(model, attr_name)
+                    if isinstance(force_obj, dict) and len(force_obj) > 0:
+                        element_type = attr_name.replace('_force', '')
+                        subcases = list(force_obj.keys())
+                        force_results[element_type] = subcases
+                        all_subcases.update(subcases)
+                        print(f"  Force [{element_type}]: YES")
+                        print(f"    Subcases: {subcases}")
+                except Exception as e:
+                    pass
+
+        if not force_results:
+            print(f"  Force: NO force results found")
+
+        # Check grid point forces
+        grid_point_forces = list(model.grid_point_forces.keys()) if hasattr(model, 'grid_point_forces') else []
+        if grid_point_forces:
+            print(f"  Grid Point Forces: YES")
+            print(f"    Subcases: {grid_point_forces}")
+            all_subcases.update(grid_point_forces)
+
+        # Check SPC/MPC forces
+        spc_forces = list(model.spc_forces.keys()) if hasattr(model, 'spc_forces') else []
+        mpc_forces = list(model.mpc_forces.keys()) if hasattr(model, 'mpc_forces') else []
+
+        if spc_forces:
+            print(f"  SPC Forces: YES")
+            print(f"    Subcases: {spc_forces}")
+            all_subcases.update(spc_forces)
+
+        if mpc_forces:
+            print(f"  MPC Forces: YES")
+            print(f"    Subcases: {mpc_forces}")
+            all_subcases.update(mpc_forces)
+
+        # Check for other interesting results
+        other_results = {}
+        interesting_attrs = ['eigenvalues', 'eigenvectors', 'thermal_load_vectors',
+                           'load_vectors', 'contact', 'glue', 'slide_lines']
+
+        for attr_name in interesting_attrs:
+            if hasattr(model, attr_name):
+                obj = getattr(model, attr_name)
+                if obj and (isinstance(obj, dict) and len(obj) > 0) or (not isinstance(obj, dict)):
+                    other_results[attr_name] = str(type(obj))
+                    print(f"  {attr_name}: YES")
+
+        # Collect all element types that have any results
+        all_element_types = set()
+        all_element_types.update(stress_results.keys())
+        all_element_types.update(strain_results.keys())
+        all_element_types.update(force_results.keys())
+
+        total_result_types = (
+            len(stress_results) +
+            len(strain_results) +
+            len(force_results) +
+            (1 if displacement_available else 0) +
+            (1 if grid_point_forces else 0) +
+            (1 if spc_forces else 0) +
+            (1 if mpc_forces else 0) +
+            len(other_results)
+        )
+
+        print(f"\n  SUMMARY:")
+        print(f"    Total subcases: {len(all_subcases)}")
+        print(f"    Total result types: {total_result_types}")
+        print(f"    Element types with results: {sorted(all_element_types)}")
+
+        return OP2Contents(
+            file_path=str(op2_file),
+            subcases=sorted(all_subcases),
+            displacement_available=displacement_available,
+            displacement_subcases=displacement_subcases,
+            stress_results=stress_results,
+            strain_results=strain_results,
+            force_results=force_results,
+            other_results=other_results,
+            grid_point_forces=grid_point_forces,
+            spc_forces=spc_forces,
+            mpc_forces=mpc_forces,
+            total_result_types=total_result_types,
+            element_types_with_results=sorted(all_element_types)
+        )
+
+    def analyze_f06(self, f06_file: Path) -> F06Contents:
+        """
+        Analyze F06 file for available results.
+
+        Args:
+            f06_file: Path to F06 file
+
+        Returns:
+            F06Contents with inventory
+        """
+        print(f"\n[F06 ANALYSIS] Reading: {f06_file.name}")
+
+        if not f06_file.exists():
+            print(f"  F06 file not found")
+            return F06Contents(
+                file_path=str(f06_file),
+                has_displacement=False,
+                has_stress=False,
+                has_strain=False,
+                has_forces=False,
+                element_types_found=[],
+                error_messages=[],
+                warning_messages=[]
+            )
+
+        # Read F06 file
+        with open(f06_file, 'r', encoding='latin-1', errors='ignore') as f:
+            content = f.read()
+
+        # Search for key sections
+        has_displacement = 'D I S P L A C E M E N T' in content
+        has_stress = 'S T R E S S E S' in content
+        has_strain = 'S T R A I N S' in content
+        has_forces = 'F O R C E S' in content
+
+        print(f"  Displacement: {'YES' if has_displacement else 'NO'}")
+        print(f"  Stress: {'YES' if has_stress else 'NO'}")
+        print(f"  Strain: {'YES' if has_strain else 'NO'}")
+        print(f"  Forces: {'YES' if has_forces else 'NO'}")
+
+        # Find element types mentioned
+        element_keywords = ['CQUAD4', 'CTRIA3', 'CTETRA', 'CHEXA', 'CPENTA', 'CBAR', 'CBEAM', 'CROD']
+        element_types_found = []
+
+        for elem_type in element_keywords:
+            if elem_type in content:
+                element_types_found.append(elem_type)
+
+        if element_types_found:
+            print(f"  Element types: {element_types_found}")
+
+        # Extract errors and warnings
+        error_messages = []
+        warning_messages = []
+
+        for line in content.split('\n'):
+            line_upper = line.upper()
+            if 'ERROR' in line_upper or 'FATAL' in line_upper:
+                error_messages.append(line.strip())
+            elif 'WARNING' in line_upper or 'WARN' in line_upper:
+                warning_messages.append(line.strip())
+
+        if error_messages:
+            print(f"  Errors found: {len(error_messages)}")
+            for err in error_messages[:5]:  # Show first 5
+                print(f"    {err}")
+
+        if warning_messages:
+            print(f"  Warnings found: {len(warning_messages)}")
+            for warn in warning_messages[:5]:  # Show first 5
+                print(f"    {warn}")
+
+        return F06Contents(
+            file_path=str(f06_file),
+            has_displacement=has_displacement,
+            has_stress=has_stress,
+            has_strain=has_strain,
+            has_forces=has_forces,
+            element_types_found=element_types_found,
+            error_messages=error_messages[:20],  # Keep first 20
+            warning_messages=warning_messages[:20]
+        )
+
+    def analyze_all(self, op2_pattern: str = "*.op2", f06_pattern: str = "*.f06") -> Dict[str, Any]:
+        """
+        Analyze all OP2 and F06 files in directory.
+
+        Args:
+            op2_pattern: Glob pattern for OP2 files
+            f06_pattern: Glob pattern for F06 files
+
+        Returns:
+            Dict with complete analysis results
+        """
+        print("="*80)
+        print("COMPREHENSIVE NASTRAN RESULTS ANALYSIS")
+        print("="*80)
+        print(f"\nDirectory: {self.output_dir}")
+
+        results = {
+            'directory': str(self.output_dir),
+            'op2_files': [],
+            'f06_files': []
+        }
+
+        # Find and analyze all OP2 files
+        op2_files = list(self.output_dir.glob(op2_pattern))
+        print(f"\nFound {len(op2_files)} OP2 file(s)")
+
+        for op2_file in op2_files:
+            op2_contents = self.analyze_op2(op2_file)
+            results['op2_files'].append(asdict(op2_contents))
+
+        # Find and analyze all F06 files
+        f06_files = list(self.output_dir.glob(f06_pattern))
+        print(f"\nFound {len(f06_files)} F06 file(s)")
+
+        for f06_file in f06_files:
+            f06_contents = self.analyze_f06(f06_file)
+            results['f06_files'].append(asdict(f06_contents))
+
+        print("\n" + "="*80)
+        print("ANALYSIS COMPLETE")
+        print("="*80)
+
+        return results
+
+
+if __name__ == '__main__':
+    import sys
+
+    if len(sys.argv) > 1:
+        output_dir = Path(sys.argv[1])
+    else:
+        output_dir = Path.cwd()
+
+    analyzer = ComprehensiveResultsAnalyzer(output_dir)
+    results = analyzer.analyze_all()
+
+    # Save results to JSON
+    output_file = output_dir / "comprehensive_results_analysis.json"
+    with open(output_file, 'w', encoding='utf-8') as f:
+        json.dump(results, f, indent=2)
+
+    print(f"\nResults saved to: {output_file}")
diff --git a/optimization_engine/result_extractors/generated/extract_expression.py b/optimization_engine/result_extractors/generated/extract_expression.py
new file mode 100644
index 00000000..5e3a4c2a
--- /dev/null
+++ b/optimization_engine/result_extractors/generated/extract_expression.py
@@ -0,0 +1,55 @@
+"""
+Extract expression value from NX .prt file
+Used for extracting computed values like mass, volume, etc.
+
+This extractor reads expressions using the .exp export method for accuracy.
+"""
+
+from pathlib import Path
+from typing import Dict, Any
+from optimization_engine.nx_updater import NXParameterUpdater
+
+
+def extract_expression(prt_file: Path, expression_name: str):
+    """
+    Extract an expression value from NX .prt file.
+
+    Args:
+        prt_file: Path to .prt file
+        expression_name: Name of expression to extract (e.g., 'p173' for mass)
+
+    Returns:
+        Dict with expression value and units
+    """
+    updater = NXParameterUpdater(prt_file, backup=False)
+    expressions = updater.get_all_expressions(use_exp_export=True)
+
+    if expression_name not in expressions:
+        raise ValueError(f"Expression '{expression_name}' not found in {prt_file}")
+
+    expr_info = expressions[expression_name]
+
+    # If expression is a formula (value is None), we need to evaluate it
+    # For now, we'll raise an error if it's a formula - user should use the computed value
+    if expr_info['value'] is None and expr_info['formula'] is not None:
+        raise ValueError(
+            f"Expression '{expression_name}' is a formula: {expr_info['formula']}. "
+            f"This extractor requires a computed value, not a formula reference."
+        )
+
+    return {
+        expression_name: expr_info['value'],
+        f'{expression_name}_units': expr_info['units']
+    }
+
+
+if __name__ == '__main__':
+    # Example usage
+    import sys
+    if len(sys.argv) > 2:
+        prt_file = Path(sys.argv[1])
+        expression_name = sys.argv[2]
+        result = extract_expression(prt_file, expression_name)
+        print(f"Extraction result: {result}")
+    else:
+        print(f"Usage: python {sys.argv[0]} <prt_file> <expression_name>")
diff --git a/optimization_engine/solve_simulation_simple.py b/optimization_engine/solve_simulation_simple.py
new file mode 100644
index 00000000..98bd12fd
--- /dev/null
+++ b/optimization_engine/solve_simulation_simple.py
@@ -0,0 +1,116 @@
+"""
+Simple NX Journal Script to Just Solve Simulation
+
+This is a simplified version that just opens and solves the simulation
+without trying to update linked parts (for simple models).
+
+Usage: run_journal.exe solve_simulation_simple.py <sim_file_path>
+"""
+
+import sys
+import NXOpen
+import NXOpen.CAE
+
+
+def main(args):
+    """
+    Open and solve a simulation file without updates.
+
+    Args:
+        args: Command line arguments
+              args[0]: .sim file path
+    """
+    if len(args) < 1:
+        print("ERROR: No .sim file path provided")
+        return False
+
+    sim_file_path = args[0]
+
+    print(f"[JOURNAL] Opening simulation: {sim_file_path}")
+
+    try:
+        theSession = NXOpen.Session.GetSession()
+
+        # Set load options to load linked parts from directory
+        print("[JOURNAL] Setting load options for linked parts...")
+        import os
+        working_dir = os.path.dirname(os.path.abspath(sim_file_path))
+
+        # Complete load options setup
+        theSession.Parts.LoadOptions.LoadLatest = False
+        theSession.Parts.LoadOptions.ComponentLoadMethod = NXOpen.LoadOptions.LoadMethod.FromDirectory
+
+        searchDirectories = [working_dir]
+        searchSubDirs = [True]
+        theSession.Parts.LoadOptions.SetSearchDirectories(searchDirectories, searchSubDirs)
+
+        theSession.Parts.LoadOptions.ComponentsToLoad = NXOpen.LoadOptions.LoadComponents.All
+        theSession.Parts.LoadOptions.PartLoadOption = NXOpen.LoadOptions.LoadOption.FullyLoad
+        theSession.Parts.LoadOptions.SetInterpartData(True, NXOpen.LoadOptions.Parent.All)
+        theSession.Parts.LoadOptions.AllowSubstitution = False
+        theSession.Parts.LoadOptions.GenerateMissingPartFamilyMembers = True
+        theSession.Parts.LoadOptions.AbortOnFailure = False
+
+        referenceSets = ["As Saved", "Use Simplified", "Use Model", "Entire Part", "Empty"]
+        theSession.Parts.LoadOptions.SetDefaultReferenceSets(referenceSets)
+        theSession.Parts.LoadOptions.ReferenceSetOverride = False
+
+        print(f"[JOURNAL] Load directory set to: {working_dir}")
+
+        # Close any currently open parts
+        print("[JOURNAL] Closing any open parts...")
+        try:
+            partCloseResponses1 = [NXOpen.BasePart.CloseWholeTree]
+            theSession.Parts.CloseAll(partCloseResponses1)
+        except:
+            pass
+
+        # Open the .sim file
+        print(f"[JOURNAL] Opening simulation...")
+        basePart1, partLoadStatus1 = theSession.Parts.OpenActiveDisplay(
+            sim_file_path,
+            NXOpen.DisplayPartOption.AllowAdditional
+        )
+
+        workSimPart = theSession.Parts.BaseWork
+        partLoadStatus1.Dispose()
+
+        # Switch to simulation application
+        theSession.ApplicationSwitchImmediate("UG_APP_SFEM")
+
+        simPart1 = workSimPart
+        theSession.Post.UpdateUserGroupsFromSimPart(simPart1)
+
+        # Solve the simulation directly
+        print("[JOURNAL] Starting solve...")
+        markId3 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Visible, "Start")
+        theSession.SetUndoMarkName(markId3, "Solve Dialog")
+
+        markId5 = theSession.SetUndoMark(NXOpen.Session.MarkVisibility.Invisible, "Solve")
+
+        theCAESimSolveManager = NXOpen.CAE.SimSolveManager.GetSimSolveManager(theSession)
+
+        # Get the first solution from the simulation
+        simSimulation1 = workSimPart.FindObject("Simulation")
+        simSolution1 = simSimulation1.FindObject("Solution[Solution 1]")
+
+        solution_solves = [simSolution1]
+
+        print("[JOURNAL] Submitting solve...")
+        theCAESimSolveManager.SubmitSolves(solution_solves)
+
+        theSession.DeleteUndoMark(markId5, "Solve")
+
+        print("[JOURNAL] Solve submitted successfully!")
+        return True
+
+    except Exception as e:
+        print(f"[JOURNAL] ERROR: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+
+if __name__ == '__main__':
+    success = main(sys.argv[1:])
+    sys.exit(0 if success else 1)
diff --git a/optimization_engine/study_creator.py b/optimization_engine/study_creator.py
new file mode 100644
index 00000000..2e6e6f25
--- /dev/null
+++ b/optimization_engine/study_creator.py
@@ -0,0 +1,412 @@
+"""
+Study Creator - Atomizer Optimization Study Management
+
+Creates and manages optimization studies with mandatory benchmarking workflow.
+
+Workflow:
+1. Create study structure
+2. User provides NX models
+3. Run benchmarking (mandatory)
+4. Create substudies (substudy_1, substudy_2, etc.)
+5. Each substudy validates against benchmarking before running
+
+Author: Antoine Letarte
+Date: 2025-11-17
+Version: 1.0.0
+"""
+
+import json
+import shutil
+from pathlib import Path
+from typing import Dict, Any, Optional, List
+from datetime import datetime
+import logging
+
+from optimization_engine.benchmarking_substudy import BenchmarkingSubstudy, BenchmarkResults
+
+logger = logging.getLogger(__name__)
+
+
+class StudyCreator:
+    """
+    Creates and manages Atomizer optimization studies.
+
+    Enforces mandatory benchmarking workflow and provides
+    study structure management.
+    """
+
+    def __init__(self, studies_root: Path = None):
+        """
+        Initialize study creator.
+
+        Args:
+            studies_root: Root directory for all studies (default: ./studies)
+        """
+        if studies_root is None:
+            studies_root = Path.cwd() / "studies"
+
+        self.studies_root = Path(studies_root)
+        self.studies_root.mkdir(parents=True, exist_ok=True)
+
+        logger.info(f"StudyCreator initialized: {self.studies_root}")
+
+    def create_study(self, study_name: str, description: str = "") -> Path:
+        """
+        Create a new optimization study with standard structure.
+
+        Args:
+            study_name: Name of the study (will be folder name)
+            description: Brief description of the study
+
+        Returns:
+            Path to created study directory
+        """
+        study_dir = self.studies_root / study_name
+
+        if study_dir.exists():
+            logger.warning(f"Study already exists: {study_name}")
+            return study_dir
+
+        logger.info(f"Creating new study: {study_name}")
+
+        # Create directory structure
+        (study_dir / "model").mkdir(parents=True)
+        (study_dir / "substudies" / "benchmarking").mkdir(parents=True)
+        (study_dir / "config").mkdir(parents=True)
+        (study_dir / "plugins" / "post_calculation").mkdir(parents=True)
+        (study_dir / "results").mkdir(parents=True)
+
+        # Create study metadata
+        metadata = {
+            "study_name": study_name,
+            "description": description,
+            "created": datetime.now().isoformat(),
+            "status": "created",
+            "benchmarking_completed": False,
+            "substudies": []
+        }
+
+        metadata_file = study_dir / "study_metadata.json"
+        with open(metadata_file, 'w') as f:
+            json.dump(metadata, f, indent=2)
+
+        # Create README
+        readme_content = self._generate_study_readme(study_name, description)
+        readme_file = study_dir / "README.md"
+        with open(readme_file, 'w', encoding='utf-8') as f:
+            f.write(readme_content)
+
+        logger.info(f"Study created: {study_dir}")
+        logger.info("")
+        logger.info("Next steps:")
+        logger.info(f"  1. Add NX model files to: {study_dir / 'model'}/")
+        logger.info(f"  2. Run benchmarking: study.run_benchmarking()")
+        logger.info("")
+
+        return study_dir
+
+    def run_benchmarking(self, study_dir: Path, prt_file: Path, sim_file: Path) -> BenchmarkResults:
+        """
+        Run mandatory benchmarking for a study.
+
+        This MUST be run before any optimization substudies.
+
+        Args:
+            study_dir: Study directory
+            prt_file: Path to NX part file
+            sim_file: Path to NX simulation file
+
+        Returns:
+            BenchmarkResults
+        """
+        logger.info("=" * 80)
+        logger.info(f"RUNNING BENCHMARKING FOR STUDY: {study_dir.name}")
+        logger.info("=" * 80)
+        logger.info("")
+
+        # Create benchmarking substudy
+        benchmark = BenchmarkingSubstudy(study_dir, prt_file, sim_file)
+
+        # Run discovery
+        results = benchmark.run_discovery()
+
+        # Generate report
+        report_content = benchmark.generate_report(results)
+        report_file = study_dir / "substudies" / "benchmarking" / "BENCHMARK_REPORT.md"
+        with open(report_file, 'w', encoding='utf-8') as f:
+            f.write(report_content)
+
+        logger.info(f"Benchmark report saved to: {report_file}")
+        logger.info("")
+
+        # Update metadata
+        self._update_metadata(study_dir, {
+            "benchmarking_completed": results.validation_passed,
+            "last_benchmarking": datetime.now().isoformat(),
+            "status": "benchmarked" if results.validation_passed else "benchmark_failed"
+        })
+
+        if not results.validation_passed:
+            logger.error("Benchmarking validation FAILED!")
+            logger.error("Fix issues before creating substudies")
+        else:
+            logger.info("Benchmarking validation PASSED!")
+            logger.info("Ready to create substudies")
+
+        logger.info("")
+
+        return results
+
+    def create_substudy(self, study_dir: Path, substudy_name: Optional[str] = None,
+                       config: Optional[Dict[str, Any]] = None) -> Path:
+        """
+        Create a new substudy.
+
+        Automatically validates against benchmarking before proceeding.
+
+        Args:
+            study_dir: Study directory
+            substudy_name: Name of substudy (if None, auto-generates substudy_N)
+            config: Optional configuration dict
+
+        Returns:
+            Path to substudy directory
+        """
+        # Check benchmarking completed
+        metadata = self._load_metadata(study_dir)
+
+        if not metadata.get('benchmarking_completed', False):
+            raise ValueError(
+                "Benchmarking must be completed before creating substudies!\n"
+                f"Run: study.run_benchmarking(prt_file, sim_file)"
+            )
+
+        # Auto-generate substudy name if not provided
+        if substudy_name is None:
+            existing_substudies = metadata.get('substudies', [])
+            # Filter out benchmarking
+            non_benchmark = [s for s in existing_substudies if s != 'benchmarking']
+            substudy_number = len(non_benchmark) + 1
+            substudy_name = f"substudy_{substudy_number}"
+
+        substudy_dir = study_dir / "substudies" / substudy_name
+
+        if substudy_dir.exists():
+            logger.warning(f"Substudy already exists: {substudy_name}")
+            return substudy_dir
+
+        logger.info(f"Creating substudy: {substudy_name}")
+
+        # Create substudy directory
+        substudy_dir.mkdir(parents=True, exist_ok=True)
+
+        # Create substudy config
+        if config is None:
+            # Use template
+            config = self._create_default_substudy_config(study_dir, substudy_name)
+
+        config_file = substudy_dir / "config.json"
+        with open(config_file, 'w') as f:
+            json.dump(config, f, indent=2)
+
+        # Update metadata
+        substudies = metadata.get('substudies', [])
+        if substudy_name not in substudies:
+            substudies.append(substudy_name)
+            self._update_metadata(study_dir, {'substudies': substudies})
+
+        logger.info(f"Substudy created: {substudy_dir}")
+        logger.info(f"Config: {config_file}")
+        logger.info("")
+
+        return substudy_dir
+
+    def _create_default_substudy_config(self, study_dir: Path, substudy_name: str) -> Dict[str, Any]:
+        """Create default substudy configuration based on benchmarking."""
+        # Load benchmark results
+        benchmark_file = study_dir / "substudies" / "benchmarking" / "benchmark_results.json"
+
+        if not benchmark_file.exists():
+            raise FileNotFoundError(f"Benchmark results not found: {benchmark_file}")
+
+        with open(benchmark_file, 'r') as f:
+            benchmark_data = json.load(f)
+
+        # Create config from benchmark proposals
+        config = {
+            "substudy_name": substudy_name,
+            "description": f"Substudy {substudy_name}",
+            "created": datetime.now().isoformat(),
+
+            "optimization": {
+                "algorithm": "TPE",
+                "direction": "minimize",
+                "n_trials": 20,
+                "n_startup_trials": 10,
+                "design_variables": []
+            },
+
+            "continuation": {
+                "enabled": False
+            },
+
+            "solver": {
+                "nastran_version": "2412",
+                "use_journal": True,
+                "timeout": 300
+            }
+        }
+
+        # Add proposed design variables
+        for var in benchmark_data.get('proposed_design_variables', []):
+            config["optimization"]["design_variables"].append({
+                "parameter": var['parameter'],
+                "min": 0.0,  # User must fill
+                "max": 0.0,  # User must fill
+                "units": var.get('units', ''),
+                "comment": f"From benchmarking: {var.get('suggested_range', 'define range')}"
+            })
+
+        return config
+
+    def _load_metadata(self, study_dir: Path) -> Dict[str, Any]:
+        """Load study metadata."""
+        metadata_file = study_dir / "study_metadata.json"
+
+        if not metadata_file.exists():
+            return {}
+
+        with open(metadata_file, 'r') as f:
+            return json.load(f)
+
+    def _update_metadata(self, study_dir: Path, updates: Dict[str, Any]):
+        """Update study metadata."""
+        metadata = self._load_metadata(study_dir)
+        metadata.update(updates)
+
+        metadata_file = study_dir / "study_metadata.json"
+        with open(metadata_file, 'w') as f:
+            json.dump(metadata, f, indent=2)
+
+    def _generate_study_readme(self, study_name: str, description: str) -> str:
+        """Generate README for new study."""
+        readme = []
+        readme.append(f"# {study_name}")
+        readme.append("")
+        readme.append(f"**Description**: {description}")
+        readme.append(f"**Created**: {datetime.now().strftime('%Y-%m-%d')}")
+        readme.append("")
+        readme.append("## Study Structure")
+        readme.append("")
+        readme.append("```")
+        readme.append(f"{study_name}/")
+        readme.append("├── model/                 # NX model files (.prt, .sim)")
+        readme.append("├── substudies/")
+        readme.append("│   ├── benchmarking/      # Mandatory discovery & validation")
+        readme.append("│   ├── substudy_1/        # First optimization campaign")
+        readme.append("│   └── substudy_2/        # Additional campaigns")
+        readme.append("├── config/                # Configuration templates")
+        readme.append("├── plugins/               # Study-specific hooks")
+        readme.append("├── results/               # Optimization results")
+        readme.append("└── README.md              # This file")
+        readme.append("```")
+        readme.append("")
+        readme.append("## Workflow")
+        readme.append("")
+        readme.append("### 1. Add NX Models")
+        readme.append("Place your `.prt` and `.sim` files in the `model/` directory.")
+        readme.append("")
+        readme.append("### 2. Run Benchmarking (Mandatory)")
+        readme.append("```python")
+        readme.append("from optimization_engine.study_creator import StudyCreator")
+        readme.append("")
+        readme.append("creator = StudyCreator()")
+        readme.append(f"results = creator.run_benchmarking(")
+        readme.append(f"    study_dir=Path('studies/{study_name}'),")
+        readme.append("    prt_file=Path('studies/{study_name}/model/YourPart.prt'),")
+        readme.append("    sim_file=Path('studies/{study_name}/model/YourSim.sim')")
+        readme.append(")")
+        readme.append("```")
+        readme.append("")
+        readme.append("### 3. Review Benchmark Report")
+        readme.append("Check `substudies/benchmarking/BENCHMARK_REPORT.md` for:")
+        readme.append("- Discovered expressions")
+        readme.append("- OP2 contents")
+        readme.append("- Baseline performance")
+        readme.append("- Configuration proposals")
+        readme.append("")
+        readme.append("### 4. Create Substudies")
+        readme.append("```python")
+        readme.append("# Auto-numbered: substudy_1, substudy_2, etc.")
+        readme.append(f"substudy_dir = creator.create_substudy(Path('studies/{study_name}'))")
+        readme.append("")
+        readme.append("# Or custom name:")
+        readme.append(f"substudy_dir = creator.create_substudy(")
+        readme.append(f"    Path('studies/{study_name}'), ")
+        readme.append("    substudy_name='coarse_exploration'")
+        readme.append(")")
+        readme.append("```")
+        readme.append("")
+        readme.append("### 5. Configure & Run Optimization")
+        readme.append("Edit `substudies/substudy_N/config.json` with:")
+        readme.append("- Design variable ranges")
+        readme.append("- Objectives and constraints")
+        readme.append("- Number of trials")
+        readme.append("")
+        readme.append("Then run the optimization!")
+        readme.append("")
+        readme.append("## Status")
+        readme.append("")
+        readme.append("See `study_metadata.json` for current study status.")
+        readme.append("")
+
+        return "\n".join(readme)
+
+    def list_studies(self) -> List[Dict[str, Any]]:
+        """List all studies in the studies root."""
+        studies = []
+
+        for study_dir in self.studies_root.iterdir():
+            if not study_dir.is_dir():
+                continue
+
+            metadata_file = study_dir / "study_metadata.json"
+            if metadata_file.exists():
+                with open(metadata_file, 'r') as f:
+                    metadata = json.load(f)
+                    studies.append({
+                        'name': study_dir.name,
+                        'path': study_dir,
+                        'status': metadata.get('status', 'unknown'),
+                        'created': metadata.get('created', 'unknown'),
+                        'benchmarking_completed': metadata.get('benchmarking_completed', False),
+                        'substudies_count': len(metadata.get('substudies', [])) - 1  # Exclude benchmarking
+                    })
+
+        return studies
+
+
+def main():
+    """Example usage of StudyCreator."""
+    print("=" * 80)
+    print("Atomizer Study Creator")
+    print("=" * 80)
+    print()
+
+    creator = StudyCreator()
+
+    # List existing studies
+    studies = creator.list_studies()
+    print(f"Existing studies: {len(studies)}")
+    for study in studies:
+        status_icon = "✅" if study['benchmarking_completed'] else "⚠️"
+        print(f"  {status_icon} {study['name']} ({study['status']}) - {study['substudies_count']} substudies")
+    print()
+
+    print("To create a new study:")
+    print("  creator.create_study('my_study_name', 'Brief description')")
+    print()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/studies/simple_beam_optimization/OPTIMIZATION_RESULTS_50TRIALS.md b/studies/simple_beam_optimization/OPTIMIZATION_RESULTS_50TRIALS.md
new file mode 100644
index 00000000..c164cef8
--- /dev/null
+++ b/studies/simple_beam_optimization/OPTIMIZATION_RESULTS_50TRIALS.md
@@ -0,0 +1,274 @@
+# Simple Beam Optimization - 50 Trials Results
+
+**Date**: 2025-11-17
+**Study**: simple_beam_optimization
+**Substudy**: full_optimization_50trials
+**Total Runtime**: ~21 minutes
+
+---
+
+## Executive Summary
+
+The 50-trial optimization successfully explored the 4D design space but **did not find a feasible design** that meets the displacement constraint (< 10mm). The best design achieved 11.399 mm displacement, which is **14% over the limit**.
+
+### Key Findings
+
+- **Total Trials**: 50
+- **Feasible Designs**: 0 (0%)
+- **Best Design**: Trial 43
+  - Displacement: 11.399 mm (1.399 mm over limit)
+  - Stress: 70.263 MPa
+  - Mass: 1987.556 kg
+  - Objective: 702.717
+
+### Design Variables (Best Trial 43)
+
+```
+beam_half_core_thickness: 39.836 mm  (upper bound: 40 mm) ✓
+beam_face_thickness:      39.976 mm  (upper bound: 40 mm) ✓
+holes_diameter:           235.738 mm (mid-range)
+hole_count:               11         (mid-range)
+```
+
+**Observation**: The optimizer pushed beam thickness to the **maximum allowed values**, suggesting that the constraint might not be achievable within the current design variable bounds.
+
+---
+
+## Detailed Analysis
+
+### Performance Statistics
+
+| Metric | Minimum | Maximum | Range |
+|--------|---------|---------|-------|
+| Displacement (mm) | 11.399 | 37.075 | 25.676 |
+| Stress (MPa) | 70.263 | 418.652 | 348.389 |
+| Mass (kg) | 645.90 | 1987.56 | 1341.66 |
+
+### Constraint Violation Analysis
+
+- **Minimum Violation**: 1.399 mm (Trial 43) - **Closest to meeting constraint**
+- **Maximum Violation**: 27.075 mm (Trial 1)
+- **Average Violation**: 5.135 mm across all 50 trials
+
+### Top 5 Trials (Closest to Feasibility)
+
+| Trial | Displacement (mm) | Violation (mm) | Stress (MPa) | Mass (kg) | Objective |
+|-------|------------------|----------------|--------------|-----------|-----------|
+| 43 | 11.399 | 1.399 | 70.263 | 1987.56 | 842.59 |
+| 49 | 11.578 | 1.578 | 73.339 | 1974.84 | 857.25 |
+| 42 | 11.614 | 1.614 | 71.674 | 1951.52 | 852.44 |
+| 47 | 11.643 | 1.643 | 73.596 | 1966.00 | 860.82 |
+| 32 | 11.682 | 1.682 | 71.887 | 1930.16 | 852.06 |
+
+**Pattern**: All top designs cluster around 11.4-11.7 mm displacement with masses near 2000 kg, suggesting this is the **practical limit** for the current design space.
+
+---
+
+## Physical Interpretation
+
+### Why No Feasible Design Was Found
+
+1. **Beam Thickness Maxed Out**: Both beam_half_core_thickness (39.836mm) and beam_face_thickness (39.976mm) are at or very near the upper bound (40mm), indicating that **thicker beams are needed** to meet the constraint.
+
+2. **Moderate Hole Configuration**: hole_count=11 and holes_diameter=235.738mm suggest a balance between:
+   - Weight reduction (more/larger holes)
+   - Stiffness maintenance (fewer/smaller holes)
+
+3. **Trade-off Tension**: The multi-objective formulation (minimize displacement, stress, AND mass) creates competing goals:
+   - Reducing displacement requires thicker beams → **increases mass**
+   - Reducing mass requires thinner beams → **increases displacement**
+
+### Engineering Insights
+
+The best design (Trial 43) achieved:
+- **Low stress**: 70.263 MPa (well within typical aluminum limits ~200-300 MPa)
+- **High stiffness**: Displacement only 14% over limit
+- **Heavy**: 1987.56 kg (high mass due to thick beams)
+
+This suggests the design is **structurally sound** but **overweight** for the displacement target.
+
+---
+
+## Recommendations
+
+### Option 1: Relax Displacement Constraint (Quick Win)
+
+Change displacement limit from 10mm to **12.5mm** (10% margin above best achieved).
+
+**Why**: Trial 43 is very close (11.399mm). A slightly relaxed constraint would immediately yield 5+ feasible designs.
+
+**Implementation**:
+```json
+// In beam_optimization_config.json
+"constraints": [
+  {
+    "name": "displacement_limit",
+    "type": "less_than",
+    "value": 12.5,  // Changed from 10.0
+    "units": "mm"
+  }
+]
+```
+
+**Expected Outcome**: Feasible designs with good mass/stiffness trade-off.
+
+---
+
+### Option 2: Expand Design Variable Ranges (Engineering Solution)
+
+Allow thicker beams to meet the original constraint.
+
+**Why**: The optimizer is already at the upper bounds, indicating it needs more thickness to achieve <10mm displacement.
+
+**Implementation**:
+```json
+// In beam_optimization_config.json
+"design_variables": {
+  "beam_half_core_thickness": {
+    "min": 10.0,
+    "max": 60.0,  // Increased from 40.0
+    ...
+  },
+  "beam_face_thickness": {
+    "min": 10.0,
+    "max": 60.0,  // Increased from 40.0
+    ...
+  }
+}
+```
+
+**Trade-off**: Heavier beams (mass will increase significantly).
+
+---
+
+### Option 3: Adjust Objective Weights (Prioritize Stiffness)
+
+Give more weight to displacement reduction.
+
+**Current Weights**:
+- minimize_displacement: 33%
+- minimize_stress: 33%
+- minimize_mass: 34%
+
+**Recommended Weights**:
+```json
+"objectives": [
+  {
+    "name": "minimize_displacement",
+    "weight": 0.50,  // Increased from 0.33
+    ...
+  },
+  {
+    "name": "minimize_stress",
+    "weight": 0.25,  // Decreased from 0.33
+    ...
+  },
+  {
+    "name": "minimize_mass",
+    "weight": 0.25   // Decreased from 0.34
+    ...
+  }
+]
+```
+
+**Expected Outcome**: Optimizer will prioritize meeting displacement constraint even at the cost of higher mass.
+
+---
+
+### Option 4: Run Refined Optimization in Promising Region
+
+Focus search around the best trial's design space.
+
+**Strategy**:
+1. Use Trial 43 design as baseline
+2. Narrow variable ranges around these values:
+   - beam_half_core_thickness: 35-40 mm (Trial 43: 39.836)
+   - beam_face_thickness: 35-40 mm (Trial 43: 39.976)
+   - holes_diameter: 200-270 mm (Trial 43: 235.738)
+   - hole_count: 9-13 (Trial 43: 11)
+
+3. Run 30-50 additional trials with tighter bounds
+
+**Why**: TPE sampler may find feasible designs by exploiting local gradients near Trial 43.
+
+---
+
+### Option 5: Multi-Stage Optimization (Advanced)
+
+**Stage 1**: Focus solely on meeting displacement constraint
+- Objective: minimize displacement only
+- Constraint: displacement < 10mm
+- Run 20 trials
+
+**Stage 2**: Optimize mass while maintaining feasibility
+- Use Stage 1 best design as starting point
+- Objective: minimize mass
+- Constraint: displacement < 10mm
+- Run 30 trials
+
+**Why**: Decoupling objectives can help find feasible designs first, then optimize them.
+
+---
+
+## Validation of 4D Expression Updates
+
+All 50 trials successfully updated all 4 design variables using the new .exp import system:
+
+- ✅ beam_half_core_thickness: Updated correctly in all trials
+- ✅ beam_face_thickness: Updated correctly in all trials
+- ✅ holes_diameter: Updated correctly in all trials
+- ✅ **hole_count**: Updated correctly in all trials (previously failing!)
+
+**Verification**: Mesh element counts varied across trials (e.g., Trial 43: 5665 nodes), confirming that hole_count changes are affecting geometry.
+
+---
+
+## Next Steps
+
+### Immediate Actions
+
+1. **Choose a strategy** from the 5 options above based on project priorities:
+   - Need quick results? → Option 1 (relax constraint)
+   - Engineering rigor? → Option 2 (expand bounds)
+   - Balanced approach? → Option 3 (adjust weights)
+
+2. **Update configuration** accordingly
+
+3. **Run refined optimization** (30-50 trials should suffice)
+
+### Long-Term Enhancements
+
+1. **Pareto Front Analysis**: Since this is multi-objective, generate Pareto front to visualize displacement-mass-stress trade-offs
+
+2. **Sensitivity Analysis**: Identify which design variables have the most impact on displacement
+
+3. **Constraint Reformulation**: Instead of hard constraint, use soft penalty with higher weight
+
+---
+
+## Conclusion
+
+The 50-trial optimization was **successful from a technical standpoint**:
+- All 4 design variables updated correctly (validation of .exp import system)
+- Optimization converged to a consistent region (11.4-11.7mm displacement)
+- Multiple trials explored the full design space
+
+However, the **displacement constraint appears infeasible** with the current design variable bounds. The optimizer is telling us: "To meet <10mm displacement, I need thicker beams than you're allowing me to use."
+
+**Recommended Action**: Start with **Option 1** (relax constraint to 12.5mm) to validate the workflow, then decide if achieving <10mm is worth the mass penalty of thicker beams (Options 2-5).
+
+---
+
+## Files
+
+- **Configuration**: [beam_optimization_config.json](beam_optimization_config.json)
+- **Best Trial**: [substudies/full_optimization_50trials/best_trial.json](substudies/full_optimization_50trials/best_trial.json)
+- **Full Log**: [../../beam_optimization_50trials.log](../../beam_optimization_50trials.log)
+- **Analysis Script**: [../../analyze_beam_results.py](../../analyze_beam_results.py)
+- **Summary Data**: [../../beam_optimization_summary.json](../../beam_optimization_summary.json)
+
+---
+
+**Generated**: 2025-11-17
+**Analyst**: Claude Code
+**Atomizer Version**: Phase 3.2 (NX Expression Import System)
diff --git a/studies/simple_beam_optimization/substudies/full_optimization_50trials/best_trial.json b/studies/simple_beam_optimization/substudies/full_optimization_50trials/best_trial.json
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+++ b/studies/simple_beam_optimization/substudies/full_optimization_50trials/best_trial.json
@@ -0,0 +1,11 @@
+{
+  "best_trial_number": 43,
+  "best_params": {
+    "beam_half_core_thickness": 39.835977148950434,
+    "beam_face_thickness": 39.97606330808705,
+    "holes_diameter": 235.73841184921832,
+    "hole_count": 11
+  },
+  "best_value": 842.5871322101043,
+  "timestamp": "2025-11-17T12:56:49.443658"
+}
\ No newline at end of file
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+++ b/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_000/results.json
@@ -0,0 +1,18 @@
+{
+  "trial_number": 0,
+  "design_variables": {
+    "beam_half_core_thickness": 30.889245901635,
+    "beam_face_thickness": 25.734879738683965,
+    "holes_diameter": 196.88120747479843,
+    "hole_count": 8
+  },
+  "results": {
+    "max_displacement": 15.094435691833496,
+    "max_stress": 94.004625,
+    "mass": 1579.95831975008
+  },
+  "objective": 573.1885187433323,
+  "penalty": 509.44356918334967,
+  "total_objective": 1082.632087926682,
+  "timestamp": "2025-11-17T12:35:07.090019"
+}
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+++ b/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_001/results.json
@@ -0,0 +1,18 @@
+{
+  "trial_number": 1,
+  "design_variables": {
+    "beam_half_core_thickness": 11.303198040010104,
+    "beam_face_thickness": 16.282803447622868,
+    "holes_diameter": 429.3010428935242,
+    "hole_count": 6
+  },
+  "results": {
+    "max_displacement": 37.07490158081055,
+    "max_stress": 341.66096875,
+    "mass": 645.897660512099
+  },
+  "objective": 344.58804178328114,
+  "penalty": 2707.4901580810547,
+  "total_objective": 3052.078199864336,
+  "timestamp": "2025-11-17T12:35:32.903554"
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+{
+  "trial_number": 2,
+  "design_variables": {
+    "beam_half_core_thickness": 22.13055862881592,
+    "beam_face_thickness": 10.613383555548651,
+    "holes_diameter": 208.51035503920883,
+    "hole_count": 15
+  },
+  "results": {
+    "max_displacement": 28.803829193115234,
+    "max_stress": 418.65240625,
+    "mass": 965.750784009661
+  },
+  "objective": 476.0158242595128,
+  "penalty": 1880.3829193115234,
+  "total_objective": 2356.398743571036,
+  "timestamp": "2025-11-17T12:35:59.234414"
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+{
+  "trial_number": 3,
+  "design_variables": {
+    "beam_half_core_thickness": 39.78301412313181,
+    "beam_face_thickness": 30.16401688307248,
+    "holes_diameter": 226.25741233381117,
+    "hole_count": 11
+  },
+  "results": {
+    "max_displacement": 12.913118362426758,
+    "max_stress": 79.3666484375,
+    "mass": 1837.45194552324
+  },
+  "objective": 655.1859845218776,
+  "penalty": 291.3118362426758,
+  "total_objective": 946.4978207645534,
+  "timestamp": "2025-11-17T12:36:28.057060"
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+{
+  "trial_number": 4,
+  "design_variables": {
+    "beam_half_core_thickness": 39.70778774581336,
+    "beam_face_thickness": 24.041841898010958,
+    "holes_diameter": 166.95548469781374,
+    "hole_count": 7
+  },
+  "results": {
+    "max_displacement": 13.88154411315918,
+    "max_stress": 86.727765625,
+    "mass": 1884.56761364204
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+  "objective": 673.9540608518862,
+  "penalty": 388.15441131591797,
+  "total_objective": 1062.1084721678042,
+  "timestamp": "2025-11-17T12:36:55.243019"
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@@ -0,0 +1,18 @@
+{
+  "trial_number": 5,
+  "design_variables": {
+    "beam_half_core_thickness": 24.66688696685749,
+    "beam_face_thickness": 21.365405059488964,
+    "holes_diameter": 286.4471575094528,
+    "hole_count": 12
+  },
+  "results": {
+    "max_displacement": 19.82601547241211,
+    "max_stress": 117.1086640625,
+    "mass": 1142.21061932314
+  },
+  "objective": 433.5400548163886,
+  "penalty": 982.6015472412109,
+  "total_objective": 1416.1416020575996,
+  "timestamp": "2025-11-17T12:37:22.635864"
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@@ -0,0 +1,18 @@
+{
+  "trial_number": 6,
+  "design_variables": {
+    "beam_half_core_thickness": 39.242879452291646,
+    "beam_face_thickness": 32.18506500188219,
+    "holes_diameter": 436.51250169202365,
+    "hole_count": 13
+  },
+  "results": {
+    "max_displacement": 16.844642639160156,
+    "max_stress": 306.56965625,
+    "mass": 1914.99718165845
+  },
+  "objective": 757.8257603972959,
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+{
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@@ -0,0 +1,18 @@
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@@ -0,0 +1,18 @@
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new file mode 100644
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+{
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+    "holes_diameter": 221.86713778262373,
+    "hole_count": 13
+  },
+  "results": {
+    "max_displacement": 11.724766731262207,
+    "max_stress": 72.4340234375,
+    "mass": 1925.97299370716
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+  "objective": 682.6032186161259,
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+  "total_objective": 855.0798917423466,
+  "timestamp": "2025-11-17T12:56:23.436440"
+}
\ No newline at end of file
diff --git a/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/Beam.prt b/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/Beam.prt
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diff --git a/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/Beam_fem1.fem b/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/Beam_fem1.fem
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diff --git a/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/Beam_sim1.sim b/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/Beam_sim1.sim
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diff --git a/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/results.json b/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/results.json
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+++ b/studies/simple_beam_optimization/substudies/full_optimization_50trials/trial_049/results.json
@@ -0,0 +1,18 @@
+{
+  "trial_number": 49,
+  "design_variables": {
+    "beam_half_core_thickness": 34.900827947904915,
+    "beam_face_thickness": 39.89789174684708,
+    "holes_diameter": 168.0380849411955,
+    "hole_count": 13
+  },
+  "results": {
+    "max_displacement": 11.57779598236084,
+    "max_stress": 73.3386875,
+    "mass": 1974.83622116564
+  },
+  "objective": 699.4667547454967,
+  "penalty": 157.77959823608398,
+  "total_objective": 857.2463529815807,
+  "timestamp": "2025-11-17T12:56:49.436502"
+}
\ No newline at end of file