feat: Major update with validators, skills, dashboard, and docs reorganization
- Add validation framework (config, model, results, study validators) - Add Claude Code skills (create-study, run-optimization, generate-report, troubleshoot, analyze-model) - Add Atomizer Dashboard (React frontend + FastAPI backend) - Reorganize docs into structured directories (00-09) - Add neural surrogate modules and training infrastructure - Add multi-objective optimization support 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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.claude/skills/run-optimization.md
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# Run Optimization Skill
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**Last Updated**: November 25, 2025
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**Version**: 1.0 - Optimization Execution and Monitoring
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You are helping the user run and monitor Atomizer optimization studies.
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## Purpose
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Execute optimization studies with proper:
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1. Pre-flight validation
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2. Resource management
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3. Progress monitoring
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4. Error recovery
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5. Dashboard integration
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## Triggers
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- "run optimization"
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- "start the study"
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- "run {study_name}"
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- "execute optimization"
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- "begin the optimization"
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## Prerequisites
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- Study must exist in `studies/{study_name}/`
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- `optimization_config.json` must be present and valid
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- `run_optimization.py` must exist
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- NX model files must be in place
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## Pre-Flight Checklist
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Before running, verify:
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### 1. Study Structure
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```
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studies/{study_name}/
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├── 1_setup/
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│ ├── model/
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│ │ ├── {Model}.prt ✓ Required
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│ │ ├── {Model}_sim1.sim ✓ Required
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│ │ └── {Model}_fem1.fem ? Optional (created by NX)
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│ ├── optimization_config.json ✓ Required
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│ └── workflow_config.json ? Optional
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├── 2_results/ ? Created automatically
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└── run_optimization.py ✓ Required
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```
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### 2. Configuration Validation
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```python
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from optimization_engine.validators.config_validator import validate_config
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result = validate_config(study_dir / "1_setup" / "optimization_config.json")
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if result.errors:
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# STOP - fix errors first
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for error in result.errors:
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print(f"ERROR: {error}")
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if result.warnings:
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# WARN but can continue
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for warning in result.warnings:
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print(f"WARNING: {warning}")
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```
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### 3. NX Environment
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- Verify NX is installed (check `config.py` for `NX_VERSION`)
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- Verify Nastran solver is available
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- Check for any running NX processes that might conflict
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## Execution Modes
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### Mode 1: Quick Test (3-5 trials)
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```bash
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cd studies/{study_name}
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python run_optimization.py --trials 3
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```
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**Use when**: First time running, testing configuration
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### Mode 2: Standard Run
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```bash
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cd studies/{study_name}
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python run_optimization.py --trials 30
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```
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**Use when**: Production optimization with FEA only
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### Mode 3: Extended with NN Surrogate
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```bash
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cd studies/{study_name}
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python run_optimization.py --trials 200 --enable-nn
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```
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**Use when**: Large-scale optimization with trained surrogate
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### Mode 4: Resume Interrupted
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```bash
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cd studies/{study_name}
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python run_optimization.py --trials 30 --resume
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```
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**Use when**: Optimization was interrupted
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## Execution Steps
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### Step 1: Validate Study
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Run pre-flight checks and present status:
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```
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PRE-FLIGHT CHECK: {study_name}
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===============================
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Configuration:
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✓ optimization_config.json valid
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✓ 4 design variables defined
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✓ 2 objectives (multi-objective)
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✓ 2 constraints configured
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Model Files:
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✓ Beam.prt exists (3.2 MB)
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✓ Beam_sim1.sim exists (1.1 MB)
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✓ Beam_fem1.fem exists (0.8 MB)
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Environment:
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✓ NX 2412 detected
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✓ Nastran solver available
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? No NX processes running (clean slate)
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Estimated Runtime:
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- 30 trials × ~30s/trial = ~15 minutes
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- With NN: 200 trials × ~2s/trial = ~7 minutes (after training)
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Ready to run. Proceed? (Y/n)
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```
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### Step 2: Start Optimization
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```python
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import subprocess
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import sys
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from pathlib import Path
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def run_optimization(study_name: str, trials: int = 30,
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enable_nn: bool = False, resume: bool = False):
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"""Start optimization as background process."""
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study_dir = Path(f"studies/{study_name}")
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cmd = [
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sys.executable,
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str(study_dir / "run_optimization.py"),
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"--trials", str(trials)
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]
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if enable_nn:
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cmd.append("--enable-nn")
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if resume:
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cmd.append("--resume")
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# Run in background
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process = subprocess.Popen(
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cmd,
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cwd=study_dir,
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stdout=subprocess.PIPE,
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stderr=subprocess.STDOUT
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)
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return process.pid
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```
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### Step 3: Monitor Progress
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Provide real-time updates:
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```
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OPTIMIZATION RUNNING: {study_name}
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==================================
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Progress: [████████░░░░░░░░░░░░] 12/30 trials (40%)
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Elapsed: 5m 32s
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ETA: ~8 minutes
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Current Trial #12:
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Parameters: thickness=2.3, diameter=15.2, ...
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Status: Running FEA...
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Best So Far (Pareto Front):
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#1: mass=245g, freq=125Hz (feasible)
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#2: mass=280g, freq=142Hz (feasible)
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#3: mass=310g, freq=158Hz (feasible)
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Constraint Violations: 3/12 trials (25%)
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Common: max_stress exceeded
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Dashboard: http://localhost:3003
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Optuna Dashboard: http://localhost:8081
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```
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### Step 4: Handle Completion/Errors
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**On Success**:
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```
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OPTIMIZATION COMPLETE
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=====================
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Study: {study_name}
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Duration: 14m 23s
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Trials: 30/30
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Results:
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Feasible designs: 24/30 (80%)
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Pareto-optimal: 8 designs
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Best Designs:
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#1: mass=231g, freq=118Hz ← Lightest
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#2: mass=298g, freq=156Hz ← Stiffest
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#3: mass=265g, freq=138Hz ← Balanced
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Next Steps:
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1. View results: /generate-report {study_name}
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2. Continue optimization: python run_optimization.py --trials 50 --resume
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3. Export designs: python export_pareto.py
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```
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**On Error**:
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```
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OPTIMIZATION ERROR
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==================
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Trial #15 failed with:
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Error: NX simulation timeout after 600s
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Design: thickness=1.2, diameter=45, hole_count=12
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Possible causes:
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1. Mesh quality issues with extreme parameters
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2. Convergence problems in solver
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3. NX process locked/crashed
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Recovery options:
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1. [Recommended] Resume with --resume flag (skips failed)
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2. Narrow design variable bounds
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3. Check NX manually with these parameters
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Resume command:
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python run_optimization.py --trials 30 --resume
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```
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## Dashboard Integration
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Always inform user about monitoring options:
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```
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MONITORING OPTIONS
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==================
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1. Atomizer Dashboard (recommended):
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cd atomizer-dashboard/backend && python -m uvicorn api.main:app --port 8000
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cd atomizer-dashboard/frontend && npm run dev
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→ http://localhost:3003
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2. Optuna Dashboard:
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python -c "import optuna; from optuna_dashboard import run_server; ..."
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→ http://localhost:8081
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3. Command Line:
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Watch study.db for updates
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Tail the log file
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```
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## Resource Management
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### Before Running
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- Check available RAM (recommend 8GB+ free)
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- Check disk space (OP2 files can be large)
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- Close unnecessary NX sessions
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### During Run
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- Monitor CPU usage (Nastran is CPU-intensive)
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- Watch for disk space issues
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- Handle NX license timeouts
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### Cleanup After
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- Option to remove intermediate OP2 files
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- Compress results for archival
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- Clean worker directories
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## Error Handling
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| Error | Cause | Recovery |
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|-------|-------|----------|
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| NX not found | NX not installed/configured | Check config.py settings |
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| Simulation timeout | Complex mesh/convergence | Increase timeout or simplify |
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| License error | NX license unavailable | Wait for license or use queue |
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| Database locked | Multiple processes | Stop conflicting processes |
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| Out of memory | Large mesh | Reduce mesh density |
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| OP2 parse error | Corrupted output | Re-run trial |
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## Parallel Execution (Advanced)
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For large studies, can run parallel workers:
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```python
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# Warning: Requires careful NX session management
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# Each worker needs isolated model directory
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python run_training_fea.py --study {study_name} --workers 2
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```
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## Output Format
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After starting optimization:
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```
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OPTIMIZATION STARTED
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====================
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Study: {study_name}
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Trials: 30
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Mode: Multi-objective (NSGA-II)
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Started: 2025-11-25 15:30:00
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Process ID: 12345
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Log File: studies/{study_name}/2_results/optimization.log
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Monitoring:
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Dashboard: http://localhost:3003
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Database: studies/{study_name}/2_results/study.db
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Commands:
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Check progress: "how's the optimization going?"
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Stop: Ctrl+C in terminal or kill process 12345
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Resume: python run_optimization.py --resume
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```
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## Integration with Other Skills
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- After completion → `/generate-report`
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- On error → `/troubleshoot`
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- For more trials → `/configure-surrogate` (enable NN)
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## Example Conversation
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```
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USER: Run the uav_arm optimization
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CLAUDE: I'll start the UAV arm optimization. Let me run pre-flight checks...
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PRE-FLIGHT CHECK: uav_arm_optimization
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======================================
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✓ Configuration valid (Protocol 11, 30 trials)
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✓ Model files present
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✓ NX 2412 available
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Ready to start. This will take approximately 15 minutes.
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Starting now...
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OPTIMIZATION STARTED
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====================
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Process running in background.
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Monitor at: http://localhost:3003
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I'll let you know when it completes. You can ask "how's it going?" anytime.
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[... 15 minutes later ...]
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OPTIMIZATION COMPLETE
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=====================
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30/30 trials completed successfully.
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Found 8 Pareto-optimal designs.
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Best lightweight: 231g @ 118Hz
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Best stiff: 298g @ 156Hz
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Would you like me to generate a detailed report?
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```
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