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A methodology for determining the scattered Electromagnetic (EM) fields present for interconnected regions with common metasurface boundaries is presented. The method uses a Boundary Element Method (BEM) formulation of the frequency domain…

Computational Physics · Physics 2020-01-08 Scott A. Stewart , Sanam Moslemi-Tabrizi , Tom. J. Smy , Shulabh Gupta

The intersection of physics and machine learning has given rise to the physics-enhanced machine learning (PEML) paradigm, aiming to improve the capabilities and reduce the individual shortcomings of data- or physics-only methods. In this…

Machine Learning · Computer Science 2024-04-23 Marcus Haywood-Alexander , Wei Liu , Kiran Bacsa , Zhilu Lai , Eleni Chatzi

Many applications require that we learn the parameters of a model from data. EM is a method used to learn the parameters of probabilistic models for which the data for some of the variables in the models is either missing or hidden. There…

Machine Learning · Computer Science 2013-01-30 Luis E. Ortiz , Leslie Pack Kaelbling

The finite element method has become a preeminent simulation technique in electromagnetics. For problems involving anisotropic media and metamaterials, proper algorithms should be developed. It has been proved that discretizing in quadratic…

Mathematical Physics · Physics 2009-10-21 E. Cojocaru

The oversampling multiscale finite element method (MsFEM) is one of the most popular methods for simulating composite materials and flows in porous media which may have many scales. But the method may be inapplicable or inefficient in some…

Numerical Analysis · Mathematics 2012-11-16 Weibing Deng , Haijun Wu

The Matrix Element Method has proven to be a powerful method to optimally exploit the information available in detector data. Its widespread use is nevertheless impeded by its complexity and the associated computing time. MoMEMta, a C++…

This paper introduces an accurate edge-based smoothed finite element method (ES-FEM) for electromagnetic analysis for both two dimensional cylindrical and three dimensional cartesian systems, which shows much better performance in terms of…

Computational Engineering, Finance, and Science · Computer Science 2019-10-30 Yangfan Zhang , Pengfei Wang , Wenping Li , Shunchuan Yang

Discrete element modelling (DEM) is one of the most efficient computational approaches to the fracture processes of heterogeneous materials on mesoscopic scales. From the dynamics of single crack propagation through the statistics of crack…

Materials Science · Physics 2015-09-09 Humberto A. Carmona , Falk K. Wittel , Ferenc Kun

In this paper, we study applications of the virtual element method (VEM) for simulating the deformation of multiphase composites. The VEM is a Galerkin approach that is applicable to meshes that consist of arbitrarily-shaped polygonal and…

Numerical Analysis · Mathematics 2022-04-29 N. Sukumar , John E. Bolander

The Expectation--Maximization (EM) algorithm is a simple meta-algorithm that has been used for many years as a methodology for statistical inference when there are missing measurements in the observed data or when the data is composed of…

Machine Learning · Statistics 2022-11-15 Hideitsu Hino , Shotaro Akaho , Noboru Murata

A new field of numerical astrophysics is introduced which addresses the solution of large, multidimensional structural or slowly-evolving problems (rotating stars, interacting binaries, thick advective accretion disks, four dimensional…

Astrophysics · Physics 2009-10-30 David L. Meier

Random-effects meta-analyses are very commonly used in medical statistics. Recent methodological developments include multivariate (multiple outcomes) and network (multiple treatments) meta-analysis. Here we provide a new model and…

Methodology · Statistics 2017-08-16 Dan Jackson , Sylwia Bujkiewicz , Martin Law , Richard D Riley , Ian White

In this paper, we explore the discriminatory power of the matrix element method (MEM) in constraining the $L_\mu-L_\tau$ model at the LHC. The $Z'$ gauge boson associated with the spontaneously broken $U(1)_{L_\mu-L_\tau}$ symmetry only…

High Energy Physics - Phenomenology · Physics 2017-07-26 Fatemeh Elahi , Adam Martin

Boundary element methods (BEM) reduce a partial differential equation in a domain to an integral equation on the domain's boundary. They are particularly attractive for solving problems on unbounded domains, but handling the dense matrices…

Numerical Analysis · Mathematics 2020-06-30 Steffen Börm

A novel boundary element method (BEM) removes the classical dependence on explicit fundamental solutions and extends quasi-optimal BEM discretisations to strongly elliptic operators with variable coefficients. The approach constructs a…

Numerical Analysis · Mathematics 2026-05-22 Benedikt Gräßle , Stefan A. Sauter

An introductory exposition of the virtual element method (VEM) is provided. The intent is to make this method more accessible to those unfamiliar with VEM. Familiarity with the finite element method for solving 2D linear elasticity problems…

Numerical Analysis · Mathematics 2023-09-25 L. L. Yaw

The peridynamic theory brings advantages in dealing with discontinuities, dynamic loading, and non-locality. The integro-differential formulation of peridynamics poses challenges to numerical solutions of complicated and practical problems.…

Numerical Analysis · Mathematics 2021-06-01 Xue Liang , Linjuan Wang , Jifeng Xu , Jianxiang Wang

Electrical machines commonly consist of moving and stationary parts. The field simulation of such devices can be very demanding if the underlying numerical scheme is solely based on a domain discretization, such as in case of the Finite…

Computational Engineering, Finance, and Science · Computer Science 2017-09-18 Lars Kielhorn , Thomas Rüberg , Jürgen Zechner

This paper recalls the principles of the finite-element methods (FEM) theory and declines its application in the EN-MME group, for the numerical modelling and study of particle accelerator equipment. Implicit and explicit methods are…

The Maximum Entropy Method (MEM) is a popular data analysis technique based on Bayesian inference, which has found various applications in the research literature. While the MEM itself is well-grounded in statistics, I argue that its…

Data Analysis, Statistics and Probability · Physics 2020-11-03 Alexander Rothkopf