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(Partial) differential equations (PDEs) are fundamental tools for describing natural phenomena, making their solution crucial in science and engineering. While traditional methods, such as the finite element method, provide reliable…

Machine Learning · Computer Science 2025-03-11 Viggo Moro , Luiz F. O. Chamon

This work considers multirate generalized-structure additively partitioned Runge-Kutta (MrGARK) methods for solving stiff systems of ordinary differential equations (ODEs) with multiple time scales. These methods treat different partitions…

Numerical Analysis · Mathematics 2022-01-19 Steven Roberts , John Loffeld , Arash Sarshar , Carol S. Woodward , Adrian Sandu

We present an arbitrary order discontinuous Galerkin finite element method for solving the fourth-order curl problem using a reconstructed discontinuous approximation method. It is based on an arbitrarily high-order approximation space with…

Numerical Analysis · Mathematics 2024-06-11 Ruo Li , Qicheng Liu , Shuhai Zhao

When applied to stiff, linear differential equations with time-dependent forcing, Runge-Kutta methods can exhibit convergence rates lower than predicted by the classical order condition theory. Commonly, this order reduction phenomenon is…

Numerical Analysis · Mathematics 2022-02-15 Steven Roberts , Adrian Sandu

Scheduling the maintenance based on the condition, respectively the degradation level of the system leads to improved system's reliability while minimizing the maintenance cost. Since the degradation level changes dynamically during the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-11-30 Pegah Rokhforoz , Olga Fink

This paper presents a high-order deferred correction algorithm combined with penalty iteration for solving free and moving boundary problems, using a fourth-order finite difference method. Typically, when free boundary problems are solved…

Numerical Analysis · Mathematics 2023-01-20 Dawei Wang , Kirill Serkh , Christina Christara

Probabilistic solvers for ordinary differential equations assign a posterior measure to the solution of an initial value problem. The joint covariance of this distribution provides an estimate of the (global) approximation error. The…

Numerical Analysis · Mathematics 2021-02-23 Nathanael Bosch , Philipp Hennig , Filip Tronarp

Many applications involve partial differential equations which admits nontrivial steady state solutions. The design of schemes which are able to describe correctly these equilibrium states may be challenging for numerical methods, in…

Analysis of PDEs · Mathematics 2016-02-09 Lorenzo Pareschi , Thomas Rey

In this paper we investigate the existence, uniqueness and approximation of solutions of delay differential equations (DDEs) with the right-hand side functions $f=f(t,x,z)$ that are Lipschitz continuous with respect to $x$ but only H\"older…

Numerical Analysis · Mathematics 2024-01-23 Fabio V. Difonzo , Paweł Przybyłowicz , Yue Wu , Xinheng Xie

Semi-Lagrangian schemes with various splitting methods, and with different reconstruction/interpolation strategies have been applied to kinetic simulations. For example, the order of spatial accuracy of the algorithms proposed in {[Qiu and…

Numerical Analysis · Mathematics 2015-06-17 Andrew Christlieb , Wei Guo , Maureen Morton , Jing-Mei Qiu

In distributed model predictive control (DMPC), where a centralized optimization problem is solved in distributed fashion using dual decomposition, it is important to keep the number of iterations in the solution algorithm, i.e. the amount…

Optimization and Control · Mathematics 2013-07-11 Pontus Giselsson , Anders Rantzer

We propose and analyze a novel approach to construct structure preserving approximations for the Poisson-Nernst-Planck equations, focusing on the positivity preserving and mass conservation properties. The strategy consists of a standard…

Numerical Analysis · Mathematics 2024-03-08 Fenghua Tong , Yongyong Cai

A numerical search approach is used to design high-order diagonally implicit Runge-Kutta (DIRK) schemes equipped with embedded error estimators, some of which have identical diagonal elements (SDIRK) and explicit first stage (ESDIRK). In…

Numerical Analysis · Mathematics 2023-09-12 Yousef Alamri , David I. Ketcheson

Mixed-precision algorithms combine low- and high-precision computations in order to benefit from the performance gains of reduced-precision without sacrificing accuracy. In this work, we design mixed-precision Runge-Kutta-Chebyshev (RKC)…

Numerical Analysis · Mathematics 2023-01-10 Matteo Croci , Giacomo Rosilho de Souza

Parallel-across-the method time integration can provide small scale parallelism when solving initial value problems. Spectral deferred corrections (SDC) with a diagonal sweeper, which is closely related to iterated Runge-Kutta methods…

Numerical Analysis · Mathematics 2025-02-12 Gayatri Čaklović , Thibaut Lunet , Sebastian Götschel , Daniel Ruprecht

Constrained dynamical systems are systems such that, by some means, the state stays within a given set. Two such systems are the (perturbed) Moreau sweeping process and the recently proposed extended Projected Dynamical System (ePDS). We…

Optimization and Control · Mathematics 2024-12-17 Anton Pozharskiy , Armin Nurkanović , Moritz Diehl

We present the two-dimensional unstructured grids extension of the a posteriori local subcell correction of discontinuous Galerkin (DG) schemes introduced in [52]. The technique is based on the reformulation of DG scheme as a finite volume…

Numerical Analysis · Mathematics 2022-12-23 François Vilar , Rémi Abgrall

We propose a new reduced order modeling strategy for tackling parametrized Partial Differential Equations (PDEs) with linear constraints, in particular Darcy flow systems in which the constraint is given by mass conservation. Our approach…

Numerical Analysis · Mathematics 2023-11-27 Wietse M. Boon , Nicola R. Franco , Alessio Fumagalli , Paolo Zunino

Distributed Constraint Optimization Problems (DCOPs) are an important subclass of combinatorial optimization problems, where information and controls are distributed among multiple autonomous agents. Previously, Machine Learning (ML) has…

Artificial Intelligence · Computer Science 2021-12-16 Yanchen Deng , Shufeng Kong , Bo An

Periodic operation often emerges as the economically optimal mode in industrial processes, particularly under varying economic or environmental conditions. This paper proposes a robust model predictive control (MPC) framework for uncertain…

Systems and Control · Electrical Eng. & Systems 2025-12-23 Filippo Badalamenti , Jose A. Borja-Conde , Sampath Kumar Mulagaleti , Boris Houska , Alberto Bemporad , Mario Eduardo Villanueva