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Related papers: Substepping the Material Point Method

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In simulations of fluid motion time accuracy has proven to be elusive. We seek highly accurate methods with strong enough stability properties to deal with the richness of scales of many flows. These methods must also be easy to implement…

Numerical Analysis · Mathematics 2020-10-14 Victor DeCaria , Sigal Gottlieb , Zachary J. Grant , William J. Layton

Electro-quasistatic field problems involving nonlinear materials are commonly discretized in space using finite elements. In this paper, it is proposed to solve the resulting system of ordinary differential equations by an explicit…

Computational Engineering, Finance, and Science · Computer Science 2017-09-26 Christian Richter , Sebastian Schöps , Markus Clemens

In this paper we generalize the polynomial time integration framework to additively partitioned initial value problems. The framework we present is general and enables the construction of many new families of additive integrators with…

Numerical Analysis · Mathematics 2023-01-02 Tommaso Buvoli , Ben S. Southworth

In this paper, we investigate the use of a mass lumped fully explicit time stepping scheme for the discretisation of the wave equation with underlying material parameters that vary at arbitrarily fine scales. We combine the leapfrog scheme…

Numerical Analysis · Mathematics 2021-09-08 Sjoerd Geevers , Roland Maier

Multiphysics problems involving two or more coupled physical phenomena are ubiquitous in science and engineering. This work develops a new partitioned exponential approach for the time integration of multiphysics problems. After a possible…

Numerical Analysis · Mathematics 2019-09-09 Mahesh Narayanamurthi , Adrian Sandu

Magnetic quadrupoles are essential components of particle accelerators like the Large Hadron Collider. In order to study numerically the stability of the particle beam crossing a quadrupole, a large number of particle revolutions in the…

Computational Engineering, Finance, and Science · Computer Science 2019-06-26 Abele Simona , Luca Bonaventura , Thomas Pugnat , Barbara Dalena

Nonlinear differential equations rarely admit closed-form solutions, thus requiring numerical time-stepping algorithms to approximate solutions. Further, many systems characterized by multiscale physics exhibit dynamics over a vast range of…

Machine Learning · Computer Science 2020-08-26 Yuying Liu , J. Nathan Kutz , Steven L. Brunton

Particle MCMC involves using a particle filter within an MCMC algorithm. For inference of a model which involves an unobserved stochastic process, the standard implementation uses the particle filter to propose new values for the stochastic…

Computation · Statistics 2016-09-26 Paul Fearnhead , Loukia Meligkotsidou

Factored Markov decision processes (MDPs) are a prominent paradigm within the artificial intelligence community for modeling and solving large-scale MDPs whose rewards and dynamics decompose into smaller, loosely interacting components.…

Optimization and Control · Mathematics 2024-04-03 Huikang Liu , Wolfram Wiesemann , Man-Chung Yue

We present in this paper algorithms for solving stiff PDEs on the unit sphere with spectral accuracy in space and fourth-order accuracy in time. These are based on a variant of the double Fourier sphere method in coefficient space with…

Numerical Analysis · Mathematics 2017-12-27 Hadrien Montanelli , Yuji Nakatsukasa

The development and implementation of increasingly accurate methods for electronic structure calculations mean that, for many atomistic simulation problems, treating light nuclei as classical particles is now one of the most serious…

Materials Science · Physics 2016-02-12 Venkat Kapil , Joost VandeVondele , Michele Ceriotti

Solving semidefinite programs (SDP) in a short time is the key to managing various mathematical optimization problems. The matrix-completion primal-dual interior-point method (MC-PDIPM) extracts a sparse structure of input SDP by…

Optimization and Control · Mathematics 2014-05-27 Makoto Yamashita , Kazuhide Nakata

In this work we present a new simple but efficient scheme - Subsquares approach - for development of algorithms for enclosing the solution set of overdetermined interval linear systems. We are going to show two algorithms based on this…

Numerical Analysis · Computer Science 2013-05-07 Jaroslav Horáček , Milan Hladík

The matrix element method utilizes ab initio calculations of probability densities as powerful discriminants for processes of interest in experimental particle physics. The method has already been used successfully at previous and current…

Computational Physics · Physics 2015-05-20 Doug Schouten , Adam DeAbreu , Bernd Stelzer

Multi-stage (designed) procedures, obtained by splitting the sampling budget suitably across stages, and designing the sampling at a particular stage based on information about the parameter obtained from previous stages, are often…

Methodology · Statistics 2014-01-08 Atul Mallik , Moulinath Banerjee , George Michailidis

In the framework of a Particle-In-Cell scheme for some 1D Vlasov-Poisson system depending on a small parameter, we propose a time-stepping method which is numerically uniformly accurate when the parameter goes to zero. Based on an…

Numerical Analysis · Mathematics 2013-06-14 Emmanuel Frenod , Sever Adrian Hirstoaga , Eric Sonnendrücker

Extracting maximum power available from photovoltaic arrays requires the system operating at the maximum power point (MPP). Therefore, finding the MPP is necessary for efficient operation of PV arrays. The MPP changes with multiple…

Systems and Control · Electrical Eng. & Systems 2020-11-17 Eungkyun Kim , Morgan Warner , Indranil Bhattacharya

Approximate full mass matrix methods for the material point method, known as FMPM(k) of order k, can improve the calculation of grid velocities from grid momentum. It can be implemented in any MPM code by inserting a new calculation task…

Computational Engineering, Finance, and Science · Computer Science 2026-04-09 John A. Nairn

This paper develops an approach for multi-step forecasting of dynamical systems by integrating probabilistic input forecasting with physics-informed output prediction. Accurate multi-step forecasting of time series systems is important for…

Machine Learning · Statistics 2026-01-13 Mahdi Nasiri , Johanna Kortelainen , Simo Särkkä

Large-scale optimization problems that seek sparse solutions have become ubiquitous. They are routinely solved with various specialized first-order methods. Although such methods are often fast, they usually struggle with not-so-well…

Optimization and Control · Mathematics 2021-11-29 Valentina De Simone , Daniela di Serafino , Jacek Gondzio , Spyridon Pougkakiotis , Marco Viola