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This paper develops numerical methods for optimal control of mechanical systems in the Lagrangian setting. It extends the theory of discrete mechanics to enable the solutions of optimal control problems through the discretization of…

Optimization and Control · Mathematics 2015-06-04 Fernando Jimenez , Marin Kobilarov , David Martin de Diego

In this paper, we propose and analyze a new semi-implicit stochastic multiscale method for the radiative heat transfer problem with additive noise fluctuation in composite materials. In the proposed method, the strong nonlinearity term…

Numerical Analysis · Mathematics 2026-05-12 Shan Zhang , Yajun Wang , Xiaofei Guan

The numerical approximation of 2D elasticity problems is considered, in the framework of the small strain theory and in connection with the mixed Hellinger-Reissner variational formulation. A low-order Virtual Element Method (VEM) with…

Numerical Analysis · Mathematics 2017-10-11 E. Artioli , S. de Miranda , C. Lovadina , L. Patruno

We describe a new model for image propagation through open air in the presence of changes in the index of refraction (e.g. due to turbulence) using the theory of optimal transport. We describe the relationship between photon density, or…

Understanding and accurately predicting hydrogen diffusion in materials is challenging due to the complex interactions between hydrogen defects and the crystal lattice. These interactions span large length and time scales, making them…

This work is devoted to the study of dissipative fluid systems, through the lens of a geometric variational formulation. Building upon previous works extending Hamilton's principle to non-equilibrium thermodynamics, the present method…

Mathematical Physics · Physics 2026-04-07 Bastien Manach-Pérennou , François Gay-Balmaz

Many important properties of granular fluids can be represented by a system of hard spheres with inelastic collisions. Traditional methods of nonequilibrium statistical mechanics are effective for analysis and description of the inelastic…

Soft Condensed Matter · Physics 2009-11-07 James W. Dufty , J. Javier Brey , James Lutsko

This article presents a priori error estimates of the miscible displacement of one incompressible fluid by another through a porous medium characterized by a coupled system of nonlinear elliptic and parabolic equations. The study utilizes…

Numerical Analysis · Mathematics 2024-01-04 Sarvesh Kumar , Devika Shylaja

Diffusion, a ubiquitous phenomenon in nature, is a consequence of particle number conservation and locality, in systems with sufficient damping. In this paper we consider diffusive processes in the bulk of Weyl semimetals, which are exotic…

Mesoscale and Nanoscale Physics · Physics 2014-02-05 Rudro R. Biswas , Shinsei Ryu

During the last decade, an increasing importance has been given to the feedback of mechanical stresses on the chemical diffusion and, further, on corrosion. Many works point the active role of stresses on the material ageing especially on…

Materials Science · Physics 2013-01-10 Virgil Optasanu , Laura Raceanu , Tony Montesin

Predictive simulations are crucial for the success of many subsurface applications, and it is highly desirable to obtain accurate non-negative solutions for transport equations in these numerical simulations. In this paper, we propose a…

Computational Engineering, Finance, and Science · Computer Science 2017-05-24 J. Chang , K. B. Nakshatrala

The variational theory of the perfect hypermomentum fluid is developed. The new type of the generalized Frenkel condition is considered. The Lagrangian density of such fluid is stated, and the equations of motion of the fluid and the…

General Relativity and Quantum Cosmology · Physics 2008-02-03 O. V. Babourova , B. N. Frolov

We develop an ultra-weak variational formulation of a fractional advection diffusion problem in one space dimension and prove its well-posedness. Based on this formulation, we define a DPG approximation with optimal test functions and show…

Numerical Analysis · Mathematics 2015-07-27 Vincent J. Ervin , Thomas Führer , Norbert Heuer , Michael Karkulik

We establish a novel convergent iteration framework for a weak approximation of general switching diffusion. The key theoretical basis of the proposed approach is a restriction of the maximum number of switching so as to untangle and…

Numerical Analysis · Mathematics 2023-07-06 Qinjing Qiu , Reiichiro Kawai

In this paper, we propose a robust low-order stabilization-free virtual element method on quadrilateral meshes for linear elasticity that is based on the stress-hybrid principle. We refer to this approach as the Stress-Hybrid Virtual…

Numerical Analysis · Mathematics 2023-11-28 Alvin Chen , N. Sukumar

The subject of this work is a new stochastic Galerkin method for second-order elliptic partial differential equations with random diffusion coefficients. It combines operator compression in the stochastic variables with tree-based spline…

Numerical Analysis · Mathematics 2022-06-02 Markus Bachmayr , Igor Voulis

We propose a new class of finite element approximations to ideal compressible magnetohydrodynamic equations in smooth regime. Following variational approximations developed for fluid models in the last decade, our discretizations are built…

Numerical Analysis · Mathematics 2024-02-29 Valentin Carlier , Martin Campos-Pinto

In this paper, we propose universal proximal mirror methods to solve the variational inequality problem with Holder continuous operators in both deterministic and stochastic settings. The proposed methods automatically adapt not only to the…

Optimization and Control · Mathematics 2024-10-07 Anton Klimza , Alexander Gasnikov , Fedor Stonyakin , Mohammad Alkousa

This thesis deals with the investigation of a H(div)-conforming hybrid discontinuous Galerkin discretization for incompressible turbulent flows. The discretization method provides many physical and solving-oriented properties, which may be…

Computational Engineering, Finance, and Science · Computer Science 2020-09-25 Xaver Mooslechner

We propose a method to approximate the distribution of robot configurations satisfying multiple objectives. Our approach uses variational inference, a popular method in Bayesian computation, which has several advantages over sampling-based…

Robotics · Computer Science 2019-11-25 Emmanuel Pignat , Teguh Lembono , Sylvain Calinon
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