OpenMC Guide

❮ DepletionParallel Computing ❯

Multi-physics Coupling in OpenMC

Introduction to Multi-physics

While OpenMC excels at neutron transport calculations, real nuclear systems involve multiple interacting physical phenomena. Building on our understanding of transport physics and tallies, we can now explore how to couple OpenMC with other physics solvers.

Key Physics Interactions

  • Neutronics → Heat Generation
  • Temperature → Cross Sections
  • Density → Moderation
  • Deformation → Geometry

Common Applications

  • Fuel temperature feedback
  • Coolant density effects
  • Material deformation
  • Fuel performance

Temperature Feedback

The most common coupling is temperature feedback. We'll build on our knowledge of materials and cross sections to implement this:

Basic Temperature Treatment

python
# Create material (from Materials section)
fuel = openmc.Material(name='UO2')
fuel.set_density('g/cm3', 10.4)
fuel.add_nuclide('U235', 0.04)
fuel.add_nuclide('U238', 0.96)
fuel.add_element('O', 2.0)

# Add temperature (new for multi-physics)
fuel.temperature = 900.0  # K

# Configure temperature treatment
settings = openmc.Settings()
settings.temperature = {
    'method': 'interpolation',
    'range': (294.0, 1500.0),
    'multipole': True  # Use multipole method when available
}

Per-Region Temperatures

python
# Assign different temperatures by cell (after building geometry)
temperature_map = {
    fuel_cell.id: 1200.0,
    clad_cell.id: 700.0,
    water_cell.id: 580.0,
}

all_cells = geometry.get_all_cells()
for cell_id, temp in temperature_map.items():
    all_cells[cell_id].temperature = temp

Coupling Patterns

Using our knowledge of tallies and results processing, we can implement different coupling approaches:

Operator Splitting

  1. Run neutronics (OpenMC)
  2. Extract power distribution
  3. Run coupled physics
  4. Update temperatures
  5. Repeat until converged

Tight Coupling

  • Direct API integration
  • Shared memory access
  • Common time stepping
  • Consistent convergence

Basic Coupling Example

python
# Coupling iteration loop
for i in range(max_iterations):
    # 1. Run OpenMC
    openmc.run()
    
    # 2. Get power distribution
    sp = openmc.StatePoint('statepoint.h5')
    power_tally = sp.get_tally(name='power')
    power_density = power_tally.mean
    
    # 3. Run thermal model
    temperatures = calculate_temperatures(power_density)
    
    # 4. Update OpenMC materials
    update_temperatures(materials, temperatures)
    
    # 5. Check convergence
    if check_convergence():
        break

Available Frameworks

MOOSE Framework

  • Full multi-physics support
  • Finite element based
  • Parallel execution
  • Advanced solvers

ENRICO

  • OpenMC + Nek5000/NekRS
  • High-fidelity CFD
  • MPI parallelization
  • Automated coupling

Note: The choice of coupling framework depends on your specific needs:

  • Computational requirements
  • Physics fidelity needs
  • Available computing resources
  • Development time constraints

Additional Resources

Related Topics

❮ DepletionParallel Computing ❯