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In this paper we propose a nonlinear elasticity model of macromolecular conformational change (deformation) induced by electrostatic forces generated by an implicit solvation model. The Poisson-Boltzmann equation for the electrostatic…

Analysis of PDEs · Mathematics 2010-01-12 Yongcheng Zhou , Michael Holst , James Andrew McCammon

We consider an elastic/viscoelastic transmission problem for the Bresse system with fully Dirichlet or Dirichlet-Neumann-Neumann boundary conditions. The physical model consists of three wave equations coupled in certain pattern. The system…

Analysis of PDEs · Mathematics 2022-02-23 Stéphane Gerbi , Chiraz Kassem , Ali Wehbe

This paper investigates a class of controlled stochastic partial differential equations (SPDEs) arising in the modeling of composite materials with spatially varying properties. The state equation describes the evolution of a material…

Optimization and Control · Mathematics 2025-02-24 Nacira Agram , Isabelle Turpin , Eya Zougar

A robust nonconforming mixed finite element method is developed for a strain gradient elasticity (SGE) model. In two and three dimensional cases, a lower order $C^0$-continuous $H^2$-nonconforming finite element is constructed for the…

Numerical Analysis · Mathematics 2023-09-25 Mingqing Chen , Jianguo Huang , Xuehai Huang

Numerical resolution of high-dimensional nonlinear PDEs remains a huge challenge due to the curse of dimensionality. Starting from the weak formulation of the Lawson-Euler scheme, this paper proposes a stochastic particle method (SPM) by…

Numerical Analysis · Mathematics 2025-02-11 Zhengyang Lei , Sihong Shao , Yunfeng Xiong

We study the ergodic properties of finite-dimensional systems of SDEs driven by non-degenerate additive fractional Brownian motion with arbitrary Hurst parameter $H\in(0,1)$. A general framework is constructed to make precise the notions of…

Probability · Mathematics 2007-05-23 Martin Hairer

Stochastic partial differential equations (SPDEs) are the mathematical tool of choice for modelling spatiotemporal PDE-dynamics under the influence of randomness. Based on the notion of mild solution of an SPDE, we introduce a novel neural…

Machine Learning · Computer Science 2022-09-27 Cristopher Salvi , Maud Lemercier , Andris Gerasimovics

Near-optimal computational complexity of an adaptive stochastic Galerkin method with independently refined spatial meshes for elliptic partial differential equations is shown. The method takes advantage of multilevel structure in expansions…

Numerical Analysis · Mathematics 2025-03-25 Markus Bachmayr , Henrik Eisenmann , Igor Voulis

We present a novel approach for solving steady-state stochastic partial differential equations (PDEs) with high-dimensional random parameter space. The proposed approach combines spatial domain decomposition with basis adaptation for each…

Numerical Analysis · Mathematics 2017-10-25 Ramkrishna Tipireddy , Panos Stinis , Alexandre Tartakovsky

This paper is concerned with fully discrete finite element methods for approximating variational solutions of nonlinear stochastic elastic wave equations with multiplicative noise. A detailed analysis of the properties of the weak solution…

Numerical Analysis · Mathematics 2022-10-04 Xiaobing Feng , Yukun Li , Yujian Lin

This paper is devoted to the study of hyperbolic systems of linear partial differential equations perturbed by a Brownian motion. The existence and uniqueness of solutions are proved by an energy method. The specific features of this class…

Probability · Mathematics 2021-09-29 Adnan Aboulalaa

Stochastic differential equations (SDEs) are one of the most important representations of dynamical systems. They are notable for the ability to include a deterministic component of the system and a stochastic one to represent random…

Machine Learning · Computer Science 2021-05-19 Noura Dridi , Lucas Drumetz , Ronan Fablet

We are interested in stochastic control problems coming from mathematical finance and, in particular, related to model uncertainty, where the uncertainty affects both volatility and intensity. This kind of stochastic control problems is…

Probability · Mathematics 2014-05-15 Sébastien Choukroun , Andrea Cosso

This paper aims at developing a systematic study for the weak rate of convergence of the Euler-Maruyama scheme for stochastic differential equations with very irregular drift and constant diffusion coefficients. We apply our method to…

Probability · Mathematics 2017-04-27 Hoang-Long Ngo , Dai Taguchi

As a concrete setting where stochastic partial differential equations (SPDEs) are able to model real phenomena, we propose a stochastic Meinhardt model for cell repolarisation and study how parameter estimation techniques developed for…

Statistics Theory · Mathematics 2021-08-17 Randolf Altmeyer , Till Bretschneider , Josef Janák , Markus Reiß

Motivated by the modeling of three-dimensional fluid turbulence, we define and study a class of stochastic partial differential equations (SPDEs) that are randomly stirred by a spatially smooth and uncorrelated in time forcing term. To…

Probability · Mathematics 2021-12-24 Gabriel B. Apolinário , Laurent Chevillard , Jean-Christophe Mourrat

Many systems in physics, engineering, and biology exhibit multiscale stochastic dynamics, where low-dimensional slow variables evolve under the influence of high-dimensional fast processes. In practice, observations are often limited to a…

Machine Learning · Statistics 2026-05-12 Anan Saha , Arnab Ganguly

Inhomogeneities in the aortic wall can lead to localized stress accumulations, possibly initiating dissection. In many cases, a dissection results from pathological changes such as fragmentation or loss of elastic fibers. But it has been…

In this paper, we propose a dynamically low-dimensional approximation method to solve a class of time-dependent multiscale stochastic diffusion equations. A dynamically bi-orthogonal (DyBO) method was developed to explore low-dimensional…

Numerical Analysis · Mathematics 2019-02-05 Eric T. Chung , Sai-Mang Pun , Zhiwen Zhang

We examine nonlinear dynamical systems of ordinary differential equations or differential algebraic equations. In an uncertainty quantification, physical parameters are replaced by random variables. The inner variables as well as a quantity…

Numerical Analysis · Mathematics 2019-04-15 Roland Pulch