dorsal/arxiv
View SchemaAutomated dimensional analysis for PDEs
| Authors | Michal Habera, Andreas Zilian |
|---|---|
| Categories | |
| ArXiv ID | 2601.06535vv1 |
| URL | https://arxiv.org/abs/2601.06535 |
| License | http://creativecommons.org/licenses/by/4.0/ |
Abstract
Physical units are fundamental to scientific computing. However, many finite element frameworks lack built-in support for dimensional analysis. In this work, we present a systematic framework for integrating physical units into the Unified Form Language (UFL). We implement a symbolic Quantity class to track units within variational forms. The implementation exploits the abelian group structure of physical dimensions. We represent them as vectors in $\mathbb{Q}^n$ to simplify operations and improve performance. A graph-based visitor pattern traverses the expression tree to automate consistency checks and factorization. We demonstrate that this automated nondimensionalization functions as the simplest form of Full Operator Preconditioning. It acts as a physics-aware diagonal preconditioner that equilibrates linear systems prior to assembly. Numerical experiments with the Navier--Stokes equations show that this improves the condition number of the saddle-point matrix. Analysis of Neo-Hooke hyperelasticity highlights the detection of floating-point cancellation errors in small deformation regimes. Finally, the Poisson--Nernst--Planck system example illustrates the handling of coupled multiphysics problems with derived scaling parameters. Although the implementation targets the FEniCSx framework, the concepts are general and easily adaptable to other finite element libraries using UFL, such as Firedrake or DUNE.
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"abstract": "Physical units are fundamental to scientific computing. However, many finite element frameworks lack built-in support for dimensional analysis. In this work, we present a systematic framework for integrating physical units into the Unified Form Language (UFL). We implement a symbolic Quantity class to track units within variational forms. The implementation exploits the abelian group structure of physical dimensions. We represent them as vectors in $\\mathbb{Q}^n$ to simplify operations and improve performance. A graph-based visitor pattern traverses the expression tree to automate consistency checks and factorization. We demonstrate that this automated nondimensionalization functions as the simplest form of Full Operator Preconditioning. It acts as a physics-aware diagonal preconditioner that equilibrates linear systems prior to assembly. Numerical experiments with the Navier--Stokes equations show that this improves the condition number of the saddle-point matrix. Analysis of Neo-Hooke hyperelasticity highlights the detection of floating-point cancellation errors in small deformation regimes. Finally, the Poisson--Nernst--Planck system example illustrates the handling of coupled multiphysics problems with derived scaling parameters. Although the implementation targets the FEniCSx framework, the concepts are general and easily adaptable to other finite element libraries using UFL, such as Firedrake or DUNE.",
"arxiv_id": "2601.06535",
"authors": [
"Michal Habera",
"Andreas Zilian"
],
"categories": [
"cs.MS",
"cs.NA",
"math.NA"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"title": "Automated dimensional analysis for PDEs",
"url": "https://arxiv.org/abs/2601.06535",
"version": "v1"
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