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Atomistic-continuum multiscale modelling is becoming an increasingly popular tool for simulating the behaviour of materials due to its computational efficiency and reliable accuracy. In the case of ferromagnetic materials, the atomistic…

Computational Physics · Physics 2019-02-01 Doghonay Arjmand , Mikhail Poluektov , Gunilla Kreiss

In this work, we have developed a multiscale computational algorithm to couple finite element method with an open source molecular dynamics code --- the Large scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) --- to perform…

Soft Condensed Matter · Physics 2019-09-17 Takahiro Murashima , Shingo Urata , Shaofan Li

The Multiscale Finite Element Method (MsFEM) is developed in the vein of Crouzeix-Raviart element for solving viscous incompressible flows in genuine heterogeneous media. Such flows are relevant in many branches of engineering, often at…

Numerical Analysis · Mathematics 2014-04-11 Bagus Putra Muljadi , Jacek Narski , Alexei Lozinski , Pierre Degond

We propose a Machine Learning (ML) non-Markovian closure modeling framework for accurate predictions of statistical responses of turbulent dynamical systems subjected to external forcings. One of the difficulties in this statistical closure…

Computational Physics · Physics 2022-10-12 Di Qi , John Harlim

In this paper, we consider a class of convection-diffusion equations with memory effects. These equations arise as a result of homogenization or upscaling of linear transport equations in heterogeneous media and play an important role in…

Numerical Analysis · Mathematics 2022-04-04 Yalchin Efendiev , Wing Tat Leung , Wenyuan Li , Sai-Mang Pun , Petr N. Vabishchevich

In this paper, we propose a computational framework,which is based on a domain decomposition technique, to employ both finite element method (which is a popular continuum modeling approach) and lattice Boltzmann method (which is a popular…

Computational Engineering, Finance, and Science · Computer Science 2017-08-02 S. Karimi , K. B. Nakshatrala

As CMOS scaling reaches its technological limits, a radical departure from traditional von Neumann systems, which involve separate processing and memory units, is needed in order to significantly extend the performance of today's computers.…

In this work, we introduce a Variational Multi-Scale (VMS) method for the numerical approximation of parabolic problems, where sub-grid scales are approximated from the eigenpairs of associated elliptic operator. The abstract method is…

This paper reviews the status of molecular dynamics as a method in describing solid-solid phase transitions, and its relationship to continuum approaches. Simulation work done in NiTi and Zr using first principles and semi-empirical…

Materials Science · Physics 2007-05-23 G. J. Ackland

Simulations of condensed matter systems often focus on the dynamics of a few distinguished components but require integrating the dynamics of the full system. A prime example is a molecular dynamics simulation of a (macro)molecule in…

Computational Physics · Physics 2024-03-12 Mauricio J. del Razo , Daan Crommelin , Peter G. Bolhuis

Numerical simulations for flow and transport in subsurface porous media often prove computationally prohibitive due to property data availability at multiple spatial scales that can vary by orders of magnitude. A number of model order…

Numerical Analysis · Mathematics 2018-03-13 Gurpreet Singh , Wingtat Leung , Mary F. Wheeler

Variational methods are highly valuable computational tools for solving high-dimensional quantum systems. In this paper, we explore the effectiveness of three variational methods: the density matrix renormalization group (DMRG), Boltzmann…

Quantum Physics · Physics 2024-04-18 Daming Li

In this work, we introduce a unifying Bregman-based majorization-minimization (MM) framework for solving nonconvex nonsmooth optimization problems. The proposed approach leverages Bregman divergences, possibly varying across iterations, to…

Optimization and Control · Mathematics 2026-04-15 Maxence Adly , Alix Chazottes , Emilie Chouzenoux , Jean-Christophe Pesquet , Florent Sureau

A multiscale QM/classical approach is presented, that is able to model the optical properties of complex nanostructures composed of a molecular system adsorbed on metal nanoparticles. The latter are described by a combined…

Chemical Physics · Physics 2024-10-29 Pablo Grobas Illobre , Piero Lafiosca , Luca Bonatti , Tommaso Giovannini , Chiara Cappelli

We propose a computational framework for vascular fluid-structure interaction (FSI), focusing on biomechanical modeling, geometric modeling, and solver technology. The biomechanical model is constructed based on the unified continuum…

Fluid Dynamics · Physics 2022-06-27 Ju Liu , Jiayi Huang , Qingshuang Lu , Yujie Sun

This work presents a hybrid modeling approach to data-driven learning and representation of unknown physical processes and closure parameterizations. These hybrid models are suitable for situations where the mechanistic description of…

Computational Physics · Physics 2021-08-17 Suraj Pawar , Omer San , Adil Rasheed , Ionel M. Navon

Multi-modal learning has achieved remarkable success by integrating information from various modalities, achieving superior performance in tasks like recognition and retrieval compared to uni-modal approaches. However, real-world scenarios…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Xiaohao Liu , Xiaobo Xia , Zhuo Huang , See-Kiong Ng , Tat-Seng Chua

In this paper, we propose a multiscale method for the Darcy-Forchheimer model in highly heterogeneous porous media. The problem is solved in the framework of generalized multiscale finite element methods (GMsFEM) combined with a multipoint…

Numerical Analysis · Mathematics 2020-07-20 Zhengkang He , Eric T. Chung , Jie Chen , Zhangxin Chen

In this paper, the finite volume method is developed to analyze coupled dynamic problems of nonlinear thermoelasticity. The major focus is given to the description of martensitic phase transformations essential in the modelling of shape…

Computational Engineering, Finance, and Science · Computer Science 2025-10-20 Linxiang X. Wang , Roderick V. N. Melnik

Modal decomposition techniques are important tools for the analysis of unsteady flows and, in order to provide meaningful insights with respect to coherent structures and their characteristic frequencies, the modes must possess a robust…

Fluid Dynamics · Physics 2023-08-24 Lucas F. de Souza , Renato F. Miotto , William R. Wolf