name: gmsh version: 1.0.0 category: engineering description: The GMSH Agent is a specialized AI module for finite element mesh generation and manipulation. It provides automated mesh generation, quality assessment, optimization, and integration with engineer... type: reference tags: [] scripts_exempt: true

Gmsh

GMSH Agent

Overview

The GMSH Agent is a specialized AI module for finite element mesh generation and manipulation. It provides automated mesh generation, quality assessment, optimization, and integration with engineering analysis tools.

Features

Core Capabilities

• 1D/2D/3D Mesh Generation: Create meshes for beams, surfaces, and volumes
• Geometry Processing: Import and heal CAD geometries (STEP, IGES, STL)
• Quality Assessment: Evaluate mesh quality with industry-standard metrics
• Mesh Optimization: Improve mesh quality through smoothing and refinement
• Batch Processing: Process multiple geometries in parallel
• Tool Integration: Export to OrcaFlex, ANSYS, and other analysis tools

Supported Formats

• Import: STEP, IGES, STL, BREP, GEO
• Export: MSH, VTK, CGNS, MED, INP, CDB, STL

Installation

Prerequisites

# Ensure Python 3.10+ is installed
python --version

# Install GMSH Python bindings
uv pip install gmsh numpy scipy pyvista pyyaml click

Setup

# Navigate to agent directory
cd agents/gmsh

# Verify installation
python run_gmsh_agent.py --version

Usage

Command Line Interface

Basic Mesh Generation

# Generate mesh from geometry
python run_gmsh_agent.py generate \
    --input geometry.step \
    --output mesh.msh \
    --element-size 0.5

Batch Processing

# Process multiple files
python run_gmsh_agent.py batch \
    --input-directory ./geometries \
    --output-directory ./meshes \
    --config batch_config.yml \
    --parallel 4

Quality Assessment

# Assess mesh quality
python run_gmsh_agent.py assess \
    --mesh mesh.msh \
    --report quality_report.html

Mesh Optimization

# Optimize mesh quality
python run_gmsh_agent.py optimize \
    --input mesh.msh \
    --output optimized.msh \
    --method laplacian \
    --iterations 10

Python API

from agents.gmsh import GMSHAgent

# Initialize agent
agent = GMSHAgent(config="agent_config.json")

# Generate mesh
mesh = agent.generate_mesh(
    geometry="platform.step",
    config={
        "algorithm": "frontal-delaunay",
        "element_size": 0.5,
        "element_type": "tetrahedron"
    }
)

# Assess quality
quality = agent.assess_quality(mesh)
print(f"Minimum Jacobian: {quality['min_jacobian']}")
print(f"Average Aspect Ratio: {quality['avg_aspect_ratio']}")

# Optimize if needed
if quality['min_jacobian'] < 0.3:
    optimized = agent.optimize_mesh(
        mesh,
        method="laplacian_smoothing",
        iterations=10
    )

# Export to ANSYS
agent.export_to_ansys(mesh, "model.cdb")

Integration Examples

OrcaFlex Integration

# Generate panel mesh for hydrodynamics
panel_mesh = agent.generate_panel_mesh(
    geometry="hull.step",
    panel_size=2.0,
    refinement_zones=["waterline", "appendages"]
)

# Export to OrcaFlex
agent.export_to_orcaflex(panel_mesh, "hull_panels.dat")

ANSYS Integration

# Generate structural mesh
struct_mesh = agent.generate_mesh(
    geometry="structure.step",
    element_type="hexahedron",
    boundary_layers={
        "walls": {"layers": 5, "growth_rate": 1.2}
    }
)

# Export with boundary conditions
agent.export_to_ansys(
    struct_mesh,
    output="model.cdb",
    named_selections=["inlet", "outlet", "walls"]
)

Configuration

Agent Configuration (agent_config.json)

{
  "configuration": {
    "default_algorithm": "frontal-delaunay",
    "default_element_size": 1.0,
    "quality_thresholds": {
      "min_jacobian": 0.3,
      "max_aspect_ratio": 5.0
    },
    "performance": {
      "parallel_workers": 4,
      "memory_limit_gb": 4
    }
  }
}

Batch Configuration (batch_config.yml)

mesh_generation:
  algorithm: frontal-delaunay
  element_size:
    min: 0.1
    max: 1.0
  
quality_targets:
  min_jacobian: 0.4
  max_aspect_ratio: 4.0
  
optimization:
  enabled: true
  method: laplacian_smoothing
  iterations: 10
  
export:
  formats: [msh, vtk]
  directory: ./output

Workflows

Standard Meshing Workflow

1. Import geometry
2. Heal geometry defects
3. Generate mesh
4. Assess quality
5. Optimize if needed
6. Export to desired format

Batch Processing Workflow

1. Configure batch settings
2. Process files in parallel
3. Generate quality reports
4. Optimize poor meshes
5. Export all results

Quality Metrics

Performance

• Mesh Generation: >100K elements/second
• Quality Assessment: <1 second for 1M elements
• Optimization: ~10 seconds per iteration for 100K elements
• Batch Processing: Linear scaling with CPU cores

Troubleshooting

Common Issues

GMSH Not Found

# Install GMSH Python bindings
pip install gmsh

# Verify installation
python -c "import gmsh; print(gmsh.version())"

Memory Issues with Large Meshes

# Use chunked processing
agent = GMSHAgent(config={
    "performance": {
        "chunk_size": 10000,
        "memory_limit_gb": 2
    }
})

Poor Quality Meshes

# Increase optimization iterations
optimized = agent.optimize_mesh(
    mesh,
    method="remeshing",
    iterations=20,
    quality_targets={
        "min_jacobian": 0.4,
        "max_aspect_ratio": 3.0
    }
)

Development

Running Tests

# Run unit tests
pytest tests/unit/

# Run integration tests
pytest tests/integration/

# Run with coverage
pytest --cov=agents.gmsh tests/

Contributing

1. Follow repository coding standards
2. Add tests for new features
3. Update documentation
4. Submit PR with detailed description

Support

Documentation

• GMSH Documentation
• Python API Reference
• Repository Wiki

Contact

• GitHub Issues: Create Issue
• Email: support@digitalmodel.com

License

This agent is part of the DigitalModel repository and follows the same licensing terms.

Changelog

Version 1.0.0 (2024-12-24)

• Initial release
• Core mesh generation functionality
• Quality assessment and optimization
• OrcaFlex and ANSYS integration
• Batch processing support

GMSH Agent - Automated Finite Element Mesh Generation

Source: templates/README.md

GMSH Agent Geometry Templates

This directory contains parametric geometry templates for common offshore engineering structures and features.

Available Templates

1. Offshore Platform (offshore_platform.geo)

Parametric model for typical offshore platform structures including:

• Configurable deck dimensions and elevation
• Variable number of jacket legs (4, 6, 8)
• Automatic bracing generation with X-bracing
• Helideck with configurable radius
• Pile foundations with mudline penetration
• Adaptive mesh refinement near structural members

Key Parameters:

• Platform dimensions (length, width, height)
• Water depth and mudline penetration
• Number of legs and spacing
• Helideck configuration
• Mesh density control

2. Mooring Line (mooring_line.geo)

Parametric catenary mooring line model featuring:

• Chain-wire-chain configuration
• Catenary shape calculation
• Touchdown point modeling
• Seabed interaction zone
• Optional buoyancy modules
• Detailed chain link geometry (for small models)

Key Parameters:

• Total line length and segment lengths
• Fairlead and anchor positions
• Line properties (diameter, weight)
• Pretension and catenary parameters
• Number of discretization segments

3. Seabed Terrain (seabed_terrain.geo)

Parametric seabed terrain with multiple features:

• General slope with configurable gradient
• Valley features with adjustable dimensions
• Mounds and hills
• Scour pits around structures
• Sand ridges and ripples
• Multiple sediment layers

Key Parameters:

• Domain dimensions
• Terrain feature toggles (slope, valley, mound, etc.)
• Feature dimensions and positions
• Grid resolution
• Sediment layer configuration

Usage

Direct GMSH Usage

# Open template in GMSH GUI
gmsh offshore_platform.geo

# Generate mesh from command line
gmsh offshore_platform.geo -3 -o platform.msh

Python API Usage

from agents.gmsh.utilities.template_manager import TemplateManager

# Initialize manager
manager = TemplateManager()

# List available templates
templates = manager.list_templates()

# Generate geometry with custom parameters
params = {
    'deck_length': 50.0,
    'water_depth': 150.0,
    'num_legs': 6
}
geo_file = manager.generate_geometry('offshore_platform', params)

# Create parameter study
param_ranges = {
    'water_depth': [100, 150, 200],
    'num_legs': [4, 6, 8]
}
files = manager.create_parameter_study('offshore_platform', param_ranges)

CLI Usage

# Generate geometry from template
python -m agents.gmsh generate --template offshore_platform --param water_depth=150

# Run parameter study
python -m agents.gmsh parameter-study --template mooring_line \
    --vary total_length=1000,1500,2000 --vary pretension=300,500,700

Parameter Customization

All templates use GMSH's DefineNumber syntax for parameters, allowing:

• Interactive modification in GMSH GUI
• Command-line parameter override
• Programmatic control via API
• Parameter constraints (min/max values)

Example Parameter Definition

water_depth = DefineNumber[100.0, Name "Environment/Water Depth (m)"];

This creates a parameter that:

• Has default value of 100.0
• Appears in GUI under "Environment" category
• Shows units in meters
• Can be modified at runtime

Template Development

Creating New Templates

1. Start with a .geo file in this directory
2. Use DefineNumber for all configurable parameters
3. Add descriptive comments at the top of the file
4. Group parameters by category (e.g., Platform/, Environment/)
5. Define physical groups for boundary conditions
6. Include mesh refinement fields where appropriate

Template Structure

// Template Name and Description
// Author: Your Name
// Version: 1.0

// ============================================================================
// PARAMETERS
// ============================================================================
param1 = DefineNumber[default, Name "Category/Parameter Name (unit)"];

// ============================================================================
// GEOMETRY CREATION
// ============================================================================
// Geometry construction code

// ============================================================================
// PHYSICAL GROUPS
// ============================================================================
Physical Surface("Surface_Name") = {surface_ids[]};

// ============================================================================
// MESH FIELDS
// ============================================================================
// Mesh refinement configuration

Best Practices

1. Parameter Naming: Use descriptive names with units
2. Default Values: Choose reasonable defaults for typical use cases
3. Validation: Include parameter constraints where applicable
4. Documentation: Comment complex geometry operations
5. Modularity: Break complex geometries into logical sections
6. Physical Groups: Define groups for all important features
7. Mesh Control: Provide appropriate mesh refinement controls

Integration with Workflows

Templates can be used in batch processing workflows:

# workflow.yml
input:
  template: offshore_platform
  parameter_file: platform_params.json
  
stages:
  - name: geometry_generation
    template_params:
      water_depth: 150
      num_legs: 6
  - name: mesh_generation
    mesh_size: adaptive
  - name: quality_check
    min_quality: 0.7

Template Validation

Validate templates before use:

# Validate template syntax and parameters
results = manager.validate_template('offshore_platform')
print(f"Valid: {results['valid']}")
print(f"Warnings: {results['warnings']}")

Export and Documentation

Generate documentation for all templates:

# Export as Markdown
manager.export_template_docs('templates.md', format='markdown')

# Export as HTML
manager.export_template_docs('templates.html', format='html')

# Export as JSON
manager.export_template_docs('templates.json', format='json')

Contributing

To contribute new templates:

1. Create a .geo file following the structure above
2. Test with various parameter combinations
3. Add documentation to this README
4. Submit with example use cases

License

These templates are part of the GMSH Agent module and follow the repository's licensing terms.