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This paper develops a new class of Rosenbrock-type integrators based on a Krylov space solution of the linear systems. The new family, called Rosenbrock-Krylov (Rosenbrock-K), is well suited for solving large scale systems of ODEs or…

Numerical Analysis · Mathematics 2015-01-30 Paul Tranquilli , Adrian Sandu

The Rosenbrock-Krylov family of time integration schemes is an extension of Rosenbrock-W methods that employs a specific Krylov based approximation of the linear system solutions arising within each stage of the integrator. This work…

Numerical Analysis · Mathematics 2019-10-08 Paul Tranquilli , Ross Glandon , Adrian Sandu

Systems driven by multiple physical processes are central to many areas of science and engineering. Time discretization of multiphysics systems is challenging, since different processes have different levels of stiffness and characteristic…

Numerical Analysis · Mathematics 2022-01-19 Adrian Sandu , Michael Günther , Steven Roberts

This work proposes novel techniques for the efficient numerical simulation of parameterized, unsteady partial differential equations. Projection-based reduced order models (ROMs) such as the reduced basis method employ a (Petrov-)Galerkin…

Numerical Analysis · Mathematics 2023-12-05 Nicholas Mueller , Santiago Badia

Many complex applications require the solution of initial-value problems where some components change fast, while others vary slowly. Multirate schemes apply different step sizes to resolve different components of the system, according to…

Numerical Analysis · Mathematics 2021-02-23 Michael Guenther , Adrian Sandu

Exponential integrators are special time discretization methods where the traditional linear system solves used by implicit schemes are replaced with computing the action of matrix exponential-like functions on a vector. A very general…

Numerical Analysis · Computer Science 2017-01-26 Mahesh Narayanamurthi , Paul Tranquilli , Adrian Sandu , Mayya Tokman

In this work, we propose a new method, termed as R-CORK, for the numerical solution of large-scale rational eigenvalue problems, which is based on a linearization and on a compact decomposition of the rational Krylov subspaces corresponding…

Numerical Analysis · Mathematics 2017-05-22 Froilán M. Dopico , Javier González-Pizarro

We present an overview of randomized orthogonalization techniques that construct a well-conditioned basis whose sketch is orthonormal. Randomized orthogonalization has recently emerged as a powerful paradigm for reducing the computational…

Numerical Analysis · Mathematics 2025-12-18 Jean-Guillaume de Damas , Laura Grigori , Igor Simunec , Edouard Timsit

This paper is concerned with the development and testing of advanced time-stepping methods suited for the integration of time-accurate, real-world applications of computational fluid dynamics (CFD). The performance of several time…

Computational Engineering, Finance, and Science · Computer Science 2017-10-03 Arash Sarshar , Paul Tranquilli , Brent Pickering , Andrew McCall , Adrian Sandu , Christopher J. Roy

A novel numerical approach to solving the shallow-water equations on the sphere using high-order numerical discretizations in both space and time is proposed. A space-time tensor formalism is used to express the equations of motion…

Numerical Analysis · Mathematics 2021-11-12 Stéphane Gaudreault , Martin Charron , Valentin Dallerit , Mayya Tokman

Simulation of geothermal systems is challenging due to coupled physical processes in highly heterogeneous media. Combining the exponential Rosenbrock--Euler and Rosenbrock-type methods with control-volume (two-point flux approximation)…

Numerical Analysis · Mathematics 2015-06-11 Antoine Tambue , Inga Berre , Jan M. Nordbotten

We propose a high order adaptive-rank implicit integrators for stiff time-dependent PDEs, leveraging extended Krylov subspaces to efficiently and adaptively populate low-rank solution bases. This allows for the accurate representation of…

Numerical Analysis · Mathematics 2024-04-05 Hamad El Kahza , William Taitano , Jing-Mei Qiu , Luis Chacón

Nonlinear and nonaffine terms in parametric partial differential equations can potentially lead to a computational cost of a reduced order model (ROM) that is comparable to the cost of the original full order model (FOM). To address this,…

Numerical Analysis · Mathematics 2024-12-04 Lijie Ji , Zhichao Peng , Yanlai Chen

In this paper, a novel augmented Lagrangian preconditioner based on global Arnoldi for accelerating the convergence of Krylov subspace methods applied to linear systems of equations with a block three-by-three structure, these systems…

Numerical Analysis · Mathematics 2024-09-10 A. Badahmane , A. Ratnani , H. Sadok

In this paper, we investigate the use of multilinear algebra for reducing the order of multidimensional linear time-invariant (MLTI) systems. Our main tools are tensor rational Krylov subspace methods, which enable us to approximate the…

Numerical Analysis · Mathematics 2024-11-28 Houda Barkouki , Khalide Jbilou

Non-hydrostatic atmospheric models often use semi-implicit temporal discretisations in order to negate the time step limitation of explicitly resolving the fast acoustic and gravity waves. Solving the resulting system to machine precision…

Atmospheric and Oceanic Physics · Physics 2023-09-04 David Lee

This work is on a user-friendly reduced basis method for solving a family of parametric PDEs by preconditioned Krylov subspace methods including the conjugate gradient method, generalized minimum residual method, and bi-conjugate gradient…

Numerical Analysis · Mathematics 2026-02-24 Yuwen Li , Ludmil T. Zikatanov , Cheng Zuo

A high order time stepping applied to spatial discretizations provided by the method of lines for hyperbolic conservations laws is presented. This procedure is related to the one proposed in Qiu and Shu (SIAM J Sci Comput 24(6):2185-2198,…

Numerical Analysis · Mathematics 2025-01-29 David Zorío , Antonio Baeza , Pep Mulet

Discrete updates of numerical partial differential equations (PDEs) rely on two branches of temporal integration. The first branch is the widely-adopted, traditionally popular approach of the method-of-lines (MOL) formulation, in which…

Computational Physics · Physics 2021-02-03 Youngjun Lee , Dongwook Lee

A novel theoretical convergence rate estimate for a Balancing Domain Decomposition by Constraints algorithm is proven for the solution of the cardiac Bidomain model, describing the propagation of the electric impulse in the cardiac tissue.…

Numerical Analysis · Mathematics 2022-12-26 Ngoc Mai Monica Huynh
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