Searcharxiv⌕ Search

arXiv · 2610.03317

Fully mixed finite element methods for the coupling of viscoelasticity and reaction-diffusion models

Abstract

We propose and analyse a fully mixed finite element method for a two-way coupled mechanochemical model of calcium signalling in viscoelastic tissue. The mechanical response follows a Kelvin--Voigt law, with the elastic and viscous stresses, velocity, and spin tensor as unknowns, and the symmetry of the total stress imposed weakly. The reaction-diffusion system for calcium and inactivated inositol triphosphate is also formulated in mixed form, introducing the diffusive flux as an additional unknown. The coupling is bidirectional: calcium generates an active stress, while local dilation feeds back into the calcium dynamics. We establish global existence and uniqueness by reducing the coupled system to an integro-differential problem and subsequently recovering the mixed variables. The semidiscrete scheme is formulated for general conforming finite element spaces and shown to be well posed under a single inf-sup condition. An interpolation operator that commutes with the divergence and preserves the weak symmetry pairing yields optimal a priori error estimates. We specialise the analysis to three families of weakly symmetric finite elements, deriving explicit convergence rates and, for one family, a superconvergent local post-processing of the displacement. Numerical tests in two and three dimensions confirm the predicted convergence rates and illustrate the method through viscoelastic benchmarks and mechanically driven calcium wavetrains.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Alonso J. Bustos, Jeonghun J. Lee, Ricardo Ruiz-Baier. 2026-10-02. Fully mixed finite element methods for the coupling of viscoelasticity and reaction-diffusion models. https://arxiv.org/abs/2610.03317

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Hybrid-Precision Block-Jacobi Preconditioned GMRES Solver for Linear System in Circuit Simulation

As integrated circuits become increasingly complex, the demand for efficient and accurate simulation solvers continues to rise. Traditional solvers often struggle with large-scale sparse systems, leading to prolonged simulation times and reduced accuracy. In this paper, a hybrid-precision block-Jacobi preconditioned GMRES solver is proposed to solve the large sparse system in circuit simulation. The proposed method capitalizes on the structural sparsity and block properties of circuit matrices, employing a novel hybrid-precision strategy that applies single-precision arithmetic for computationally intensive tasks and double-precision arithmetic for critical accuracy-sensitive computations. Additionally, we use the graph partitioning tools to assist in generating preconditioners, ensuring an optimized preconditioning process. For large-scale problems, we adopt the restart strategy to increase the computational efficiency. Through rigorous mathematical reasoning, the convergence and error analysis of the proposed method are carried out. Numerical experiments on various benchmark matrices demonstrate that our approach significantly outperforms existing solvers, including SuperLU, KLU, and SFLU, in terms of both preconditioning and GMRES runtime. The proposed hybrid-precision preconditioner effectively improves spectral clustering, leading to faster solutions.

math.NA↗

Entropy stable finite difference schemes for One-Fluid Two-Temperature Euler Non-equilibrium Hydrodynamics

One-Fluid Two-Temperature Euler (OFTT-Euler) equations are used for modeling non-equilibrium hydrodynamics and form a system of nonlinear hyperbolic partial differential equations with non-conservative products. The model decomposed the total pressure into two scalar components: one for electrons and one for ions. In this work, we design entropy-stable finite difference numerical schemes for the model. This is achieved by introducing a novel reformulation of the equations, ensuring that the new non-conservative terms do not contribute to the entropy evolution. For this novel reformulation of the equations, we design higher-order entropy-conservative numerical schemes by using Tadmor's relation for the conservative part and higher-order central differences for the non-conservative parts. Finally, we design the entropy-dissipation terms using the entropy-scaled right eigenvectors of the conservative part, thereby ensuring entropy stability for the entire system at the semi-discrete level. We present several test cases in one and two dimensions to demonstrate the accuracy and entropy stability of the proposed schemes.

math.NA↗

Direct reconstruction for acoustic inverse Born scattering

We consider the inverse medium scattering problem for the Helmholtz equation in two dimensions, i.e., the task to recover a compactly supported penetrable two-dimensional scatterer from full knowledge of the associated far field data or, equivalently, the far field operator. Although this problem is uniquely solvable, it is severely ill-posed and nonlinear. In the regime of weak scattering, the Born approximation yields a linearized relation between the contrast and the far field data, thus overcoming the second difficulty. This linear setting allows to build on recent work on linearized electrical impedance tomography, which relies on triangular Zernike decompositions, to derive an explicit reconstruction formula that expresses the expansion coefficients of the contrast in terms of those of the far field data. By choosing the expansion functions appropriately, the resulting system matrix decouples into separate (infinite) triangular systems for the spatial angular frequencies in the contrast. Consequently, each of these systems can be solved independently by performing forward substitutions. Our numerical experiments indicate that this approach, combined with an adequate regularization method, remains effective even when applied to full nonlinear far field data beyond the Born regime.

math.NA↗