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In this paper, we develop an iterative scheme to construct multiscale basis functions within the framework of the Constraint Energy Minimizing Generalized Multiscale Finite Element Method (CEM-GMsFEM) for the mixed formulation. The…

Numerical Analysis · Mathematics 2020-12-04 Siu Wun Cheung , Eric Chung , Yalchin Efendiev , Wing Tat Leung , Sai-Mang Pun

Unfitted (also known as embedded or immersed) finite element approximations of partial differential equations are very attractive because they have much lower geometrical requirements than standard body-fitted formulations. These schemes do…

Numerical Analysis · Mathematics 2022-04-13 Santiago Badia , Pere A. Martorell , Francesc Verdugo

Motivated by problems where the response is needed at select localized regions in a large computational domain, we devise a novel finite element discretization that results in exponential convergence at pre-selected points. The two key…

Numerical Analysis · Mathematics 2016-08-03 Murthy N. Guddati , Vladimir Druskin , Ali Vaziri Astaneh

Embedding probability distributions into reproducing kernel Hilbert spaces (RKHS) has enabled powerful nonparametric methods such as the maximum mean discrepancy (MMD), a statistical distance with strong theoretical and computational…

Machine Learning · Statistics 2025-05-28 Masha Naslidnyk , Siu Lun Chau , François-Xavier Briol , Krikamol Muandet

Numerically solving high-dimensional random parametric PDEs poses a challenging computational problem. It is well-known that numerical methods can greatly benefit from adaptive refinement algorithms, in particular when functional…

Numerical Analysis · Mathematics 2024-07-29 Martin Eigel , Nando Hegemann

Deep learning and the collocation method are merged and used to solve partial differential equations describing structures' deformation. We have considered different types of materials: linear elasticity, hyperelasticity (neo-Hookean) with…

Machine Learning · Computer Science 2021-11-24 Diab W. Abueidda , Qiyue Lu , Seid Koric

In recent years, quantum computers have emerged as promising candidates for implementing kernels. Quantum Embedding Kernels embed data points into quantum states and calculate their inner product in a high-dimensional Hilbert Space by…

Quantum Physics · Physics 2025-02-13 Rodrigo Coelho , Georg Kruse , Andreas Rosskopf

The relativistic precession model (RPM) is widely-considered as a benchmark framework to interpret quasi-periodic oscillations (QPOs), albeit several observational inconsistencies suggest that the model remains incomplete. The RPM ensures…

General Relativity and Quantum Cosmology · Physics 2025-12-16 Gabriele Bianchini , Orlando Luongo , Marco Muccino

This research explored a novel explicit total Lagrangian Fragile Points Method (FPM) for finite deformation of hyperelastic materials. In contrast to mesh-based methods, where mesh distortion may pose numerical challenges, meshless methods…

It is well known that the quasi-optimality of the Galerkin finite element method for the Helmholtz equation is dependent on the mesh size and the wave-number. In the literature, different criteria have been proposed to ensure uniform…

Numerical Analysis · Mathematics 2024-12-31 Tim van Beeck , Umberto Zerbinati

Kernel power $k$-means (KPKM) leverages a family of means to mitigate local minima issues in kernel $k$-means. However, KPKM faces two key limitations: (1) the computational burden of the full kernel matrix restricts its use on extensive…

Machine Learning · Computer Science 2025-11-14 Yixi Chen , Weixuan Liang , Tianrui Liu , Jun-Jie Huang , Ao Li , Xueling Zhu , Xinwang Liu

A meshless Fragile Points Method (FPM) is presented for analyzing 2D flexoelectric problems. Local, simple, polynomial and discontinuous trial and test functions are generated with the help of a local meshless differential quadrature…

Computational Engineering, Finance, and Science · Computer Science 2020-05-19 Yue Guan , Leiting Dong , Satya N. Atluri

We introduce a meshless method for solving both continuous and discrete variational formulations of a volume constrained, nonlocal diffusion problem. We use the discrete solution to approximate the continuous solution. Our method is…

Numerical Analysis · Mathematics 2016-01-13 Richard B. Lehoucq , Francis J. Narcowich , Stephen T. Rowe , Joseph D. Ward

This paper applies the Recursive Projection Method (RPM) to the problem of finding the effective mechanical response of a periodic heterogeneous solid. Previous works apply the Fast Fourier Transform (FFT) in combination with various…

Computational Engineering, Finance, and Science · Computer Science 2020-03-18 Xiaoyao Peng , Dhriti Nepal , Kaushik Dayal

This is a survey on the theory of adaptive finite element methods (AFEMs), which are fundamental in modern computational science and engineering but whose mathematical assessment is a formidable challenge. We present a self-contained and…

Numerical Analysis · Mathematics 2024-11-20 Andrea Bonito , Claudio Canuto , Ricardo H. Nochetto , Andreas Veeser

Spacetime discontinuous Galerkin (SDG) finite element methods are used to solve such PDEs involving space and time variables arising from wave propagation phenomena in important applications in science and engineering. To support an…

Computational Geometry · Computer Science 2008-04-08 Shripad Thite

In this paper, the first large-scale application of multiscale-spectral generalized finite element methods (MS-GFEM) to composite aero-structures is presented. The crucial novelty lies in the introduction of A-harmonicity in the local…

Numerical Analysis · Mathematics 2023-03-03 Jean Bénézech , Linus Seelinger , Peter Bastian , Richard Butler , Timothy Dodwell , Chupeng Ma , Robert Scheichl

This article presents a comparison of various implementations of the Lattice Discrete Particle Model (LDPM) for the numerical simulation of concrete and other heterogeneous quasibrittle materials. The comparison involves the use of…

Numerical simulations of flow and transport in porous media usually rely on hybrid-dimensional models, i.e., the fracture is considered as objects of a lower dimension compared to the embedding matrix. Such models are usually combined with…

Numerical Analysis · Mathematics 2020-11-18 Maria Giuseppina Chiara Nestola , Marco Favino

This paper proposes a consensus-based distributed nonlinear filter with kernel mean embedding (KME). This fills with gap of posterior density approximation with KME for distributed nonlinear dynamic systems. To approximate the posterior…

Systems and Control · Electrical Eng. & Systems 2023-12-05 Liping Guo , Jimin Wang , Yanlong Zhao , Ji-Feng Zhang