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The main computational cost of algorithms for computing reduced-order models of parametric dynamical systems is in solving sequences of very large and sparse linear systems. We focus on efficiently solving these linear systems, arising…

Numerical Analysis · Mathematics 2018-09-19 Navneet Pratap Singh , Kapil Ahuja

Topology optimization (TopOpt) is a mathematical-driven design procedure to realize optimal material architectures. This procedure is often used to automate the design of devices involving flow through porous media, such as micro-fluidic…

Numerical Analysis · Mathematics 2021-06-01 T. Phatak , K. B. Nakshatrala

We consider the simulation of electromagnetic scattering by single and multiple isotropic homogeneous dielectric particles using boundary integral equations. Galerkin discretizations of the classical Poggio-Miller-Chang-Harrington-Wu-Tsai…

Numerical Analysis · Mathematics 2020-05-14 Antigoni Kleanthous , Timo Betcke , David P. Hewett , Matthew W. Scroggs , Anthony J. Baran

PDE-constrained optimization aims at finding optimal setups for partial differential equations so that relevant quantities are minimized. Including sparsity promoting terms in the formulation of such problems results in more practically…

Numerical Analysis · Mathematics 2016-11-23 Margherita Porcelli , Valeria Simoncini , Martin Stoll

The paper considers grad-div stabilized equal-order finite elements (FE) methods for the linearized Navier-Stokes equations. A block triangular preconditioner for the resulting system of algebraic equations is proposed which is closely…

Numerical Analysis · Mathematics 2024-11-12 Yunhui He , Maxim Olshanskii

We develop a linearly-scaling variant of the Force Coupling Method [K. Yeo and M. R. Maxey, J. Fluid Mech. 649, 205-231 (2010)] for computing hydrodynamic interactions among particles confined to a doubly-periodic geometry with either a…

Computational Physics · Physics 2023-05-03 Aref Hashemi , Raul P. Pelaez , Sachin Natesh , Brennan Sprinkle , Ondrej Maxian , Zecheng Gan , Aleksandar Donev

Porous membranes are thin solid structures that allow the flow to pass through their tiny openings, called pores. Flow inertia may play a significant role in several filtration flows of natural and engineering interest. Here, we develop a…

We introduce and analyze a continuous primal-dual dynamical system in the context of the minimization problem $f(x)+g(Ax)$, where $f$ and $g$ are convex functions and $A$ is a linear operator. In this setting, the trajectories of the…

Optimization and Control · Mathematics 2025-06-03 Vassilis Apidopoulos , Cesare Molinari , Juan Peypouquet , Silvia Villa

In the presence of strong heterogeneities, it is well known that the use of explicit schemes for the transport of species in a porous medium suffers from severe restrictions on the time step. This has led to the development of implicit…

Numerical Analysis · Mathematics 2023-04-10 Franciane F. Rocha , Fabricio S. Sousa , Roberto F. Ausas , Gustavo C. Buscaglia , Felipe Pereira

Motivated by the need for efficient and accurate simulation of the dynamics of the polar ice sheets, we design high-order finite element discretizations and scalable solvers for the solution of nonlinear incompressible Stokes equations. We…

Numerical Analysis · Computer Science 2015-11-05 Tobin Isaac , Georg Stadler , Omar Ghattas

A non-conventional shape optimization approach is introduced to address the identification of an obstacle immersed in a fluid described by the Stokes equation within a larger bounded domain, relying on boundary measurements on the…

Optimization and Control · Mathematics 2024-03-19 Julius Fergy Tiongson Rabago , Lekbir Afraites , Hirofumi Notsu

In this paper we consider multiple saddle point problems with block tridiagonal Hessian in a Hilbert space setting. Well-posedness and the related issue of preconditioning are discussed. We give a characterization of all block structured…

Numerical Analysis · Mathematics 2019-12-23 Alexander Beigl , Jarle Sogn , Walter Zulehner

We consider convex-concave saddle point problems with a separable structure and non-strongly convex functions. We propose an efficient stochastic block coordinate descent method using adaptive primal-dual updates, which enables flexible…

Machine Learning · Statistics 2015-11-24 Zhanxing Zhu , Amos J. Storkey

We propose an explicit partitioned (loosely coupled) scheme for fluid structure interaction (FSI) problems, specifically designed to achieve high computational efficiency in modern engineering simulations. The FSI problem under…

Numerical Analysis · Mathematics 2025-10-16 Shihan Guo , Ping Lin , Yifan Wang , Xiaohe Yue , Haibiao Zheng

We develop a simple algorithmic framework to solve large-scale symmetric positive definite linear systems. At its core, the framework relies on two components: (1) a norm-convergent iterative method (i.e. smoother) and (2) a preconditioner.…

Numerical Analysis · Mathematics 2013-02-18 Xiaozhe Hu , Shuhong Wu , Xiao-Hui Wu , Jinchao Xu , Chen-Song Zhang , Shiquan Zhang , Ludmil Zikatanov

We are studying the efficient solution of the system of linear equation stemming from the mass conserving mixed stress (MCS) method discretization of the Stokes equations. To that end we perform static condensation to arrive at a system for…

Numerical Analysis · Mathematics 2022-07-19 Lukas Kogler , Philip L. Lederer , Joachim Schöberl

In this work we construct and analyze a nonconforming high-order discretization method for the quasi-static single-phase nonlinear poroelasticity problem describing Darcean flow in a deformable porous medium saturated by a slightly…

Numerical Analysis · Mathematics 2024-09-23 Michele Botti , Daniele A. Di Pietro , Pierre Sochala

This work introduces nodal auxiliary space preconditioners for discretizations of mixed-dimensional partial differential equations. We first consider the continuous setting and generalize the regular decomposition to this setting. With the…

Numerical Analysis · Mathematics 2019-10-15 Ana Budisa , Wietse Boon , Xiaozhe Hu

We propose an alternative implementation of preconditioning techniques for the solution of non-linear problems. Within the framework of Newton-Krylov methods, preconditioning techniques are needed to improve the performance of the solvers.…

Computational Physics · Physics 2008-04-02 G. Lapenta , S. Ju

This note is concerned with the problem of minimizing a separable, convex, composite (smooth and nonsmooth) function subject to linear constraints. We study a randomized block-coordinate interpretation of the Chambolle-Pock primal-dual…

Optimization and Control · Mathematics 2024-08-30 Olivier Bilenne
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