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In this paper, we first propose a filter-based continuous Ensemble Eddy Viscosity (EEV) model for stochastic turbulent flow problems. We then propose a generic algorithm for a family of fully discrete, grad-div regularized, efficient…

Numerical Analysis · Mathematics 2025-08-15 Brandiece N. Berry , Md Mahmudul Islam , Muhammad Mohebujjaman , Neethu Suma Raveendran

A constructive numerical approximation of the two-dimensional unsteady stochastic Navier-Stokes equations of an incompressible fluid is proposed via a pseudo-compressibility technique involving a parameter $\epsilon$. Space and time are…

Numerical Analysis · Mathematics 2022-05-02 Jad Doghman

Implicit solvers present strong limitations when used on supercomputing facilities and in particular for adaptive mesh-refinement codes. We present a new method for implicit adaptive time-stepping on adaptive mesh refinement-grids. We…

Instrumentation and Methods for Astrophysics · Physics 2014-03-05 Benoit Commercon , Vincent Debout , Romain Teyssier

We propose a fully practical numerical scheme for the simulation of the stochastic total variation flow (STFV). The approximation is based on a stable time-implicit finite element space-time approximation of a regularized STVF equation. The…

Numerical Analysis · Mathematics 2022-05-05 Ľubomír Baňas , Martin Ondreját

Shallow free surface flows are often characterized by both subdomains that require high modeling complexity and subdomains that can be sufficiently accurately modeled with low modeling complexity. Moreover, these subdomains may change in…

Fluid Dynamics · Physics 2025-11-04 Rik Verbiest , Julian Koellermeier

In the present study, the efficiency of preconditioners for solving linear systems associated with the discretized variable-density incompressible Navier-Stokes equations with semiimplicit second-order accuracy in time and spectral accuracy…

We present a new time-stepping algorithm for nonlinear PDEs that exhibit scale separation in time. Our scheme combines asymptotic techniques (which are inexpensive but can have insufficient accuracy) with parallel-in-time methods (which,…

Numerical Analysis · Mathematics 2014-02-24 Terry Haut , Beth Wingate

The convergence behavior of Stochastic Gradient Descent (SGD) crucially depends on the stepsize configuration. When using a constant stepsize, the SGD iterates form a Markov chain, enjoying fast convergence during the initial transient…

Machine Learning · Computer Science 2024-12-17 Xiang Li , Qiaomin Xie

We consider fully discrete numerical schemes for a downscaling data assimilation algorithm aimed at approximating the velocity field of the 2D Navier-Stokes equations corresponding to given coarse mesh observational measurements. The time…

Numerical Analysis · Mathematics 2018-05-07 Hussain A. Ibdah , Cecilia F. Mondaini , Edriss S. Titi

In recent literature, a general two step procedure has been formulated for solving the problem of phase retrieval. First, a spectral technique is used to obtain a constant-error initial estimate, following which, the estimate is refined to…

Machine Learning · Statistics 2023-07-10 Yan Shuo Tan , Roman Vershynin

Super-time-stepping (STS) methods provide an attractive approach for enabling explicit time integration of parabolic operators, particularly in large-scale, higher-dimensional kinetic simulations where fully implicit schemes are…

Numerical Analysis · Mathematics 2026-01-22 Mustafa Aggul , Manaure Francisquez , Daniel R. Reynolds , Sylvia Amihere

Implementing particle-interaction configuration and time integration are performance intensive essentials of particle-based methods. In this paper, a dual-criteria time-stepping method is proposed to improve the computational efficiency of…

Computational Physics · Physics 2020-02-28 Chi Zhang , Massoud Rezavand , Xiangyu Hu

There has been an increasing interest in developing efficient immersed boundary method (IBM) based on Cartesian grids, recently in the context of high-order methods. IBM based on volume penalization is a robust and easy to implement method…

Numerical Analysis · Mathematics 2021-07-22 Jiaqing Kou , Esteban Ferrer

Stochastic gradient descent (\textsc{Sgd}) methods are the most powerful optimization tools in training machine learning and deep learning models. Moreover, acceleration (a.k.a. momentum) methods and diagonal scaling (a.k.a. adaptive…

Machine Learning · Statistics 2018-10-02 Qi Deng , Yi Cheng , Guanghui Lan

This work introduces a novel adaptive central-upwind scheme designed for simulating compressible flows with discontinuities in the flow field. The proposed approach offers significant improvements in computational efficiency over the…

Fluid Dynamics · Physics 2024-09-05 Amareshwara Sainadh Chamarthi

Solving the reactive low-Mach Navier-Stokes equations with high-order adaptive methods in time is still a challenging problem, in particular due to the handling of the algebraic variables involved in the mass constraint. We focus on the…

Analysis of PDEs · Mathematics 2025-10-02 Laurent François , Joël Dupays , Dmitry Davidenko , Marc Massot

Purpose: This study aims to assess the accuracy of degree adaptive strategies in the context of incompressible Navier-Stokes flows using the high order hybridisable discontinuous Galerkin (HDG) method. Design/methodology/approach: The work…

Fluid Dynamics · Physics 2024-11-12 Agustina Felipe , Ruben Sevilla , Oubay Hassan

Simulating physical problems involving multi-time scale coupling is challenging due to the need of solving these multi-time scale processes simultaneously. In response to this challenge, this paper proposed an explicit multi-time step…

Computational Engineering, Finance, and Science · Computer Science 2023-09-11 Xiaojing Tang , Dong Wu , Zhengtong Wang , Oskar Haidn , Xiangyu Hu

Time-implicit schemes are attractive since they allow numerical time steps that are much larger than those permitted by the Courant-Friedrich-Lewy criterion characterizing time-explicit methods. This advantage comes, however, with a cost:…

Solar and Stellar Astrophysics · Physics 2015-06-16 Maxime Viallet , Isabelle Baraffe , Rolf Walder

We present multi-adaptive versions of the standard continuous and discontinuous Galerkin methods for ODEs. Taking adaptivity one step further, we allow for individual time-steps, order and quadrature, so that in particular each individual…

Numerical Analysis · Mathematics 2012-05-15 Anders Logg
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