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We consider a model problem of the scattering of linear acoustic waves in free homogeneous space by an elastic solid. The stress tensor in the solid combines the effect of a linear dependence of strains with the influence of an existing…

Numerical Analysis · Mathematics 2018-04-23 Thomas S. Brown , Tonatiuh Sánchez-Vizuet , Francisco-Javier Sayas

In this paper, we study dimension reduction techniques for large-scale controlled stochastic differential equations (SDEs). The drift of the considered SDEs contains a polynomial term satisfying a one-sided growth condition. Such…

Probability · Mathematics 2023-03-10 Martin Redmann

We consider a stochastic partial differential equation (SPDE) which describes the velocity field of a viscous, incompressible non-Newtonian fluid subject to a random force. Here, the extra stress tensor of the fluid is given by a polynomial…

Probability · Mathematics 2012-10-09 Nobuo Yoshida

We analyse a PDE system modelling poromechanical processes (formulated in mixed form using the solid deformation, fluid pressure, and total pressure) interacting with diffusing and reacting solutes in the medium. We investigate the…

In this work, we derive particle schemes, based on micro-macro decomposition, for linear kinetic equations in the diffusion limit. Due to the particle approximation of the micro part, a splitting between the transport and the collision part…

Numerical Analysis · Mathematics 2017-01-19 Anaïs Crestetto , Nicolas Crouseilles , Mohammed Lemou

Stochastic homogeneous hyperelastic solids are characterised by strain-energy densities where the parameters are random variables defined by probability density functions. These models allow for the propagation of uncertainties from input…

Classical Physics · Physics 2019-08-13 L. Angela Mihai , Danielle Fitt , Thomas E. Woolley , Alain Goriely

This paper is concerned with the PDE and numerical analysis of a modified one-dimensional intravascular stent model originally proposed in [4]. It is proved that the modified model has a unique weak solution using the Galerkin method…

Numerical Analysis · Mathematics 2024-04-23 Xiaobing Feng , Tingao Jiang

In this paper, we use a stochastic partial differential equation (SPDE) as a model for the density of a population under the influence of random external forces/stimuli given by the environment. We study statistical properties for two…

Probability · Mathematics 2023-12-21 Fernando Baltazar-Larios , Francisco Delgado-Vences , Liliana Peralta

This work aims at presenting a Discontinuous Galerkin (DG) formulation employing a spectral basis for two important models employed in cardiac electrophysiology, namely the monodomain and bidomain models. The use of DG methods is motivated…

Numerical Analysis · Mathematics 2025-03-24 Federica Botta , Matteo Calafà , Pasquale C. Africa , Christian Vergara , Paola F. Antonietti

We investigate a specific finite element model to study the thermoelastic behavior of an elastic body within the context of nonlinear strain-limiting constitutive relation. As a special subclass of implicit relations, the thermoelastic…

Numerical Analysis · Mathematics 2022-03-02 Hyun C. Yoon , Karthik K. Vasudeva , S. M. Mallikarjunaiah

We study fully nonlinear second-order (forward) stochastic partial differential equations (SPDEs). They can also be viewed as forward path-dependent PDEs (PPDEs) and will be treated as rough PDEs (RPDEs) under a unified framework. We…

Probability · Mathematics 2018-10-02 Rainer Buckdahn , Christian Keller , Jin Ma , Jianfeng Zhang

In this paper, we study a two-species model in the form of a coupled system of nonlinear stochastic differential equations (SDEs) that arises from a variety of applications such as aggregation of biological cells and pedestrian movements.…

Analysis of PDEs · Mathematics 2018-10-03 Manh Hong Duong , Julian Tugaut

Electrical conduction among cardiac tissue is commonly modeled with partial differential equations, i.e., reaction-diffusion equation, where the reaction term describes cellular stimulation and diffusion term describes electrical…

Machine Learning · Computer Science 2021-09-21 Xinyu Zhao , Hao Yan , Zhiyong Hu , Dongping Du

An important class of spatio-temporal models is constructed by leveraging the hierarchical structure of dynamical (or, state-space) models. This paper proposes a new statistical dynamical model for spatio-temporal processes motivated by…

Methodology · Statistics 2026-05-11 Yutong Zhang , Xiao Liu

This paper concerns with finite element approximations of a quasi-static poroelasticity model in displacement-pressure formulation which describes the dynamics of poro-elastic materials under an applied mechanical force on the boundary. To…

Numerical Analysis · Mathematics 2014-12-01 Xiaobing Feng , Zhihao Ge , Yukun Li

Models defined by stochastic differential equations (SDEs) allow for the representation of random variability in dynamical systems. The relevance of this class of models is growing in many applied research areas and is already a standard…

Methodology · Statistics 2014-08-06 Umberto Picchini

We propose a new method for spatio-temporal forecasting on arbitrarily distributed points. Assuming that the observed system follows an unknown partial differential equation, we derive a continuous-time model for the dynamics of the data…

Machine Learning · Computer Science 2022-03-18 Marten Lienen , Stephan Günnemann

We introduce and analyse a continuum model for an interacting particle system of Vicsek type. The model is given by a non-linear kinetic partial differential equation (PDE) describing the time-evolution of the density $f_t$, in the single…

Mathematical Physics · Physics 2022-04-11 Paolo Buttà , Franco Flandoli , Michela Ottobre , Boguslaw Zegarlinski

Scientific computing for large deformation of elastic-plastic solids is critical for numerous real-world applications. Classical numerical solvers rely primarily on local discrete linear approximation and are constrained by an inherent…

Machine Learning · Computer Science 2025-06-09 Shilong Tao , Zhe Feng , Haonan Sun , Zhanxing Zhu , Yunhuai Liu

Models incorporating uncertain inputs, such as random forces or material parameters, have been of increasing interest in PDE-constrained optimization. In this paper, we focus on the efficient numerical minimization of a convex and smooth…

Optimization and Control · Mathematics 2021-06-18 Caroline Geiersbach , Winnifried Wollner