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Phase-field models of fatigue are capable of reproducing the main phenomenology of fatigue behavior. However, phase-field computations in the high-cycle fatigue regime are prohibitively expensive, due to the need to resolve spatially the…

Computational Engineering, Finance, and Science · Computer Science 2024-12-17 Jonas Heinzmann , Pietro Carrara , Marreddy Ambati , Amir Mohammad Mirzaei , Laura De Lorenzis

Strong stability preserving (SSP) Runge-Kutta methods are often desired when evolving in time problems that have two components that have very different time scales. Where the SSP property is needed, it has been shown that implicit and…

Numerical Analysis · Mathematics 2018-08-15 Sigal Gottlieb , Zachary J. Grant , Leah Isherwood

The convergence of a family of AMF-Runge-Kutta methods (in short AMF-RK) for the time integration of evolutionary Partial Differential Equations (PDEs) of Advection Diffusion Reaction type semi-discretized in space is considered. The…

Numerical Analysis · Mathematics 2015-01-13 Severiano Gonzalez Pinto , Domingo Hernandez Abreu , Soledad Perez Rodriguez

We study step-wise time approximations of non-linear hyperbolic initial value problems. The technique used here is a generalization of the minimizing movements method, using two time-scales: one for velocity, the other (potentially much…

Numerical Analysis · Mathematics 2024-04-05 Antonín Češík , Sebastian Schwarzacher

Time series, as frequently the case in neuroscience, are rarely stationary, but often exhibit abrupt changes due to attractor transitions or bifurcations in the dynamical systems producing them. A plethora of methods for detecting such…

Methodology · Statistics 2018-10-05 Hazem Toutounji , Daniel Durstewitz

We present two types of meta-algorithm that can greatly improve the accuracy of existing algorithms for integrating the equations of motion of dynamical systems. The first meta-algorithm takes an integrator that is time-symmetric only for…

Astrophysics · Physics 2007-05-23 Piet Hut , Yoko Funato , Eiichiro Kokubo , Junichiro Makino , Steve McMillan

In this paper we demonstrate a simple heuristic adaptive restart technique that can dramatically improve the convergence rate of accelerated gradient schemes. The analysis of the technique relies on the observation that these schemes…

Optimization and Control · Mathematics 2012-04-19 Brendan O'Donoghue , Emmanuel Candes

Numerical solutions to fractional differential equations can be extremely computationally intensive due to the effect of non-local derivatives in which all previous time points contribute to the current iteration. In finite difference…

Mathematical Physics · Physics 2010-04-30 Brian P. Sprouse , Christopher L. MacDonald , Gabriel A. Silva

A coercivity property of temporal convolution operators is an essential tool in the analysis of time-dependent boundary integral equations and their space and time discretisations. It is known that this coercivity property is inherited by…

Numerical Analysis · Mathematics 2017-02-28 Lehel Banjai , Christian Lubich

A mixed accuracy framework for Runge--Kutta methods presented in [Grant, JSC 2022] has been shown to speed up the computation in diagonally implicit Runge--Kutta (DIRK) methods by using less expensive low accuracy approaches for the…

Numerical Analysis · Mathematics 2026-04-29 John Driscoll , Sigal Gottlieb , Zachary J. Grant , César Herrera , Tej Sai Kakumanu , Monica Stephens

In this paper, we present an efficient numerical method to address a thermodynamically consistent gas flow model in porous media involving compressible gas and deformable rock. The accurate modeling of gas flow in porous media often poses…

Numerical Analysis · Mathematics 2026-02-16 Huangxin Chen , Yuxiang Chen , Jisheng Kou , Shuyu Sun

This paper investigates the use of stratified sampling as a variance reduction technique for approximating integrals over large dimensional spaces. The accuracy of this method critically depends on the choice of the space partition, the…

Probability · Mathematics 2009-09-15 Pierre Etoré , Gersende Fort , Benjamin Jourdain , Eric Moulines

The growing share of intermittent renewable energy sources, storage technologies, and the increasing degree of so-called sector coupling necessitates optimization-based energy system models with high temporal and spatial resolutions, which…

Optimization and Control · Mathematics 2021-11-24 Maximilian Hoffmann , Leander Kotzur , Detlef Stolten

The present work provides a comprehensive study of symmetric-conjugate operator splitting methods in the context of linear parabolic problems and demonstrates their additional benefits compared to symmetric splitting methods. Relevant…

Numerical Analysis · Mathematics 2024-01-10 Sergio Blanes , Fernando Casas , Cesáreo González , Mechthild Thalhammer

Exponential Runge--Kutta methods have shown to be competitive for the time integration of stiff semilinear parabolic PDEs. The current construction of stiffly accurate exponential Runge--Kutta methods, however, relies on a convergence…

Numerical Analysis · Mathematics 2020-09-29 Vu Thai Luan

We study a discrete-time random feature method for nonlinear, time-dependent partial differential equations. In contrast to continuous-time formulations that treat time as an additional input variable, the method advances the solution step…

Numerical Analysis · Mathematics 2026-04-29 Haoran Zhou , Zhaohui Fu , Yangshuai Wang , Xinlong Feng

Time-fractional parabolic equations with a Caputo time derivative of order $\alpha\in(0,1)$ are discretised in time using collocation methods, which assume that the Caputo derivative of the computed solution is piecewise-polynomial. For…

Numerical Analysis · Mathematics 2026-02-23 Sebastian Franz , Natalia Kopteva

The computational effort for the evaluation of numerical simulations based on e.g. the finite-element method is high. Metamodels can be utilized to create a low-cost alternative. However the number of required samples for the creation of a…

Machine Learning · Statistics 2019-05-15 Jan N. Fuhg

We consider a generic convex-concave saddle point problem with separable structure, a form that covers a wide-ranged machine learning applications. Under this problem structure, we follow the framework of primal-dual updates for saddle…

Machine Learning · Statistics 2015-06-15 Zhanxing Zhu , Amos J. Storkey

We present the formulation and optimization of a Runge-Kutta-type time-stepping scheme for solving the shallow water equations, aimed at substantially increasing the effective allowable time-step over that of comparable methods. This…

Numerical Analysis · Mathematics 2023-12-27 Jeremy R. Lilly , Darren Engwirda , Giacomo Capodaglio , Robert L. Higdon , Mark R. Petersen