Atomizer/templates

Atomizer Study Templates

Quick-start templates for common structural optimization problems.

Available Templates

Template	Analysis	Objectives	Use Case
beam_stiffness_optimization	Static	Maximize stiffness	Cantilever beams, support arms
bracket_stress_minimization	Static	Minimize stress	Mounting brackets, L-brackets
frequency_tuning	Modal	Minimize mass + Maximize frequency	Motor mounts, drone arms

Usage

Option 1: Create Study from Template (Recommended)

python -m atomizer create-study --template beam_stiffness --name my_beam_study

This creates a new study folder with:

• 1_setup/optimization_config.json - Configuration (editable)
• 1_setup/model/ - Empty folder for your NX files
• 2_results/ - Empty folder for results
• run_optimization.py - Runner script
• README.md - Study-specific instructions

Option 2: Copy and Customize

1. Copy template JSON to your study folder:

   copy templates\beam_stiffness_optimization.json studies\my_study\1_setup\optimization_config.json
   

2. Edit the config:

   • Update study_name
   • Adjust design_variables bounds for your model
   • Modify constraints thresholds
   • Update simulation file names

3. Add your NX model files to 1_setup/model/

4. Run optimization:

   python studies\my_study\run_optimization.py --trials 50
   

Template Details

Beam Stiffness Optimization

Goal: Maximize bending stiffness (minimize tip displacement) while staying under mass budget.

Design Variables:

• beam_width - Cross-section width (mm)
• beam_height - Cross-section height (mm)
• beam_length - Overall length (mm)

Constraints:

• Maximum mass limit
• Maximum stress limit

Required NX Expressions: beam_width, beam_height, beam_length

---

Bracket Stress Minimization

Goal: Minimize peak von Mises stress to increase fatigue life and safety factor.

Design Variables:

• wall_thickness - Main wall thickness (mm)
• fillet_radius - Corner radius (mm) - key for stress relief
• web_thickness - Stiffening web thickness (mm)
• rib_count - Number of stiffening ribs (integer)

Constraints:

• Maximum displacement limit (stiffness)
• Maximum mass limit (weight budget)

Required NX Expressions: wall_thickness, fillet_radius, web_thickness, rib_count

---

Frequency Tuning

Goal: Multi-objective - minimize mass while maximizing first natural frequency to avoid resonance.

Design Variables:

• section_width - Cross-section width (mm)
• section_height - Cross-section height (mm)
• arm_length - Cantilever length (mm)
• wall_thickness - Wall thickness for hollow sections (mm)

Constraints:

• Minimum frequency limit (above excitation)
• Maximum stress limit (static strength)

Required NX Expressions: section_width, section_height, arm_length, wall_thickness

Note: Requires modal analysis solution (SOL 103) in NX simulation.

Customizing Templates

Templates are JSON files with placeholders. Key sections to customize:

{
  "study_name": "your_study_name",
  "design_variables": [
    {
      "parameter": "your_nx_expression_name",
      "bounds": [min_value, max_value],
      "description": "What this parameter controls"
    }
  ],
  "constraints": [
    {
      "name": "your_constraint",
      "type": "less_than",
      "threshold": your_limit
    }
  ],
  "simulation": {
    "model_file": "YourModel.prt",
    "sim_file": "YourModel_sim1.sim"
  }
}

Creating Custom Templates

1. Copy an existing template closest to your problem
2. Modify for your specific use case
3. Save as templates/your_template_name.json
4. The template will be available via --template your_template_name

Neural Network Training

All templates include training_data_export enabled by default:

"training_data_export": {
  "enabled": true,
  "export_dir": "atomizer_field_training_data/${study_name}"
}

This automatically exports training data for AtomizerField neural surrogate training.