Technology¶
μfem is built around a high–performance finite element core with a strong focus on scalability, automation, and reproducibility. The architecture is designed for large-scale simulation campaigns, research workflows, and industrial engineering applications.
Core Discretization Engine¶
μfem uses MFEM as its computational backbone.
- High-order finite elements on unstructured meshes
- Native support for H¹, H(curl), H(div), and L² spaces
- Parallel domain decomposition with MPI
- Algebraic multigrid and advanced preconditioners
This enables accurate large-scale simulations for electromagnetics and multi-physics problems.
High-Order Accuracy¶
μfem supports true high-order methods:
- Curved (isoparametric) higher-order geometry
- High-order basis functions
- Consistent integration for nonlinear material models
This allows:
- Reduced numerical dispersion
- Improved convergence rates
- Fewer elements for equivalent accuracy
High-order geometry is especially important for electromagnetic simulations with curved domains and rotating machinery.
Adaptive Mesh Refinement¶
μfem supports adaptive mesh refinement (AMR):
- Local h-refinement
- Hanging-node support
- Parallel refinement workflows
This allows accurate resolution of:
- Singular fields
- Skin effects
- Boundary layers
- Localized nonlinearities
Native Python Interface¶
μfem provides a Python-first workflow:
- Problem definition in Python
- Direct access to model parameters
- Seamless scripting and automation
- Integration with NumPy and scientific Python ecosystem
This makes μfem suitable for:
- Parameter sweeps
- Optimization loops
- Machine learning integration
- AI-driven simulation pipelines
Performance Portability¶
μfem is designed for heterogeneous compute environments:
- Multi-core CPUs
- Distributed-memory clusters (MPI)
- GPU-ready backend through MFEM
This enables scaling from:
- Laptop prototyping
- Workstation engineering studies
- HPC cluster simulations
Cartesian Meshes & Implicit Geometry¶
μfem supports structured Cartesian meshes combined with implicit geometry descriptions.
- Hex-dominant discretizations
- Cut-cell integration workflows
- Level-set driven material definitions
- Efficient geometry parameterization
This is particularly powerful for:
- Parametric studies
- Topology variations
- Optimization workflows
- Geometry-driven automation