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Related papers: Conservative data-driven finite element framework

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Conservation laws are an inherent feature in many systems modeling real world phenomena, in particular, those modeling biological and chemical systems. If the form of the underlying dynamical system is known, linear algebra and algebraic…

Numerical Analysis · Mathematics 2024-03-11 Tracey Oellerich , Maria Emelianenko

This paper is concerned with the finite element discretization of the data driven approach according to arXiv:1510.04232 for the solution of PDEs with a material law arising from measurement data. To simplify the setting, we focus on a…

Numerical Analysis · Mathematics 2023-03-13 Christian Meyer , Annika Müller

We present a framework for constructing real-time digital twins based on structure-preserving reduced finite element models conditioned on a latent variable Z. The approach uses conditional attention mechanisms to learn both a reduced…

Machine Learning · Computer Science 2025-08-12 Brooks Kinch , Benjamin Shaffer , Elizabeth Armstrong , Michael Meehan , John Hewson , Nathaniel Trask

This paper presents a model-free data-driven strategy for linear and non-linear finite element computations of open-cell foam. Employing sets of material data, the data-driven problem is formulated as the minimization of a distance function…

Computational Engineering, Finance, and Science · Computer Science 2021-12-22 Tim Fabian Korzeniowski , Kerstin Weinberg

This work presents a data-driven magnetostatic finite-element solver that is specifically well-suited to cope with strongly nonlinear material responses. The data-driven computing framework is essentially a multiobjective optimization…

Computational Physics · Physics 2020-12-24 Armin Galetzka , Dimitrios Loukrezis , Herbert De Gersem

We develop a new computing paradigm, which we refer to as data-driven computing, according to which calculations are carried out directly from experimental material data and pertinent constraints and conservation laws, such as compatibility…

Computational Physics · Physics 2016-04-20 Trenton Kirchdoerfer , Michael Ortiz

Despite the successful implementations of physics-informed neural networks in different scientific domains, it has been shown that for complex nonlinear systems, achieving an accurate model requires extensive hyperparameter tuning, network…

Computational Engineering, Finance, and Science · Computer Science 2022-11-30 Milad Ramezankhani , Amir Nazemi , Apurva Narayan , Heinz Voggenreiter , Mehrtash Harandi , Rudolf Seethaler , Abbas S. Milani

We consider a finite element discretization for the reconstruction of the final state of the heat equation, when the initial data is unknown, but additional data is given in a sub domain in the space time. For the discretization in space we…

Numerical Analysis · Mathematics 2017-07-24 Erik Burman , Jonathan Ish-Horowicz , Lauri Oksanen

We design a primal-dual stabilized finite element method for the numerical approximation of a data assimilation problem subject to the acoustic wave equation. For the forward problem, piecewise affine, continuous, finite element functions…

Numerical Analysis · Mathematics 2023-05-10 Erik Burman , Ali Feizmohammadi , Lauri Oksanen

Atmospheric systems incorporating thermal dynamics must be stable with respect to both energy and entropy. While energy conservation can be enforced via the preservation of the skew-symmetric structure of the Hamiltonian form of the…

Numerical Analysis · Mathematics 2023-10-31 Kieran Ricardo , David Lee , Kenneth Duru

We consider data assimilation for the heat equation using a finite element space semi-discretization. The approach is optimization based, but the design of regularization operators and parameters rely on techniques from the theory of…

Numerical Analysis · Mathematics 2016-09-19 Erik Burman , Lauri Oksanen

Data-Driven Computational Mechanics is a novel computing paradigm that enables the transition from standard data-starved approaches to modern data-rich approaches. At this early stage of development, one can distinguish two mainstream…

Numerical Analysis · Mathematics 2019-10-29 Cristian Guillermo Gebhardt , Dominik Schillinger , Marc Christian Steinbach , Raimund Rolfes

In this article, we present an extension of the formulation recently developed by the authors (A Framework for Data-Driven Computational Mechanics Based on Nonlinear Optimization, arXiv:1910.12736 [math.NA]) to the structural dynamics…

Numerical Analysis · Mathematics 2019-12-25 Cristian Guillermo Gebhardt , Marc Christian Steinbach , Dominik Schillinger , Raimund Rolfes

The finite element simulation of dynamic wetting phenomena, requiring the computation of flow in a domain confined by intersecting a liquid-fluid free surface and a liquid-solid interface, with the three-phase contact line moving across the…

Computational Physics · Physics 2012-02-20 J. E. Sprittles , Y. D. Shikhmurzaev

In this paper, we consider numerical approximation of an electrically conductive ferrofluid model, which consists of Navier-Stokes equations, magnetization equation, and magnetic induction equation. To solve this highly coupled, nonlinear,…

Numerical Analysis · Mathematics 2025-04-02 Jialin Xie , Xiaodi Zhang

In a landscape where scientific discovery is increasingly driven by data, the integration of machine learning (ML) with traditional scientific methodologies has emerged as a transformative approach. This paper introduces a novel,…

Machine Learning · Computer Science 2024-06-26 Yunjin Tong

This article presents a new finite element method for convection-diffusion equations by enhancing the continuous finite element space with a flux space for flux approximations that preserve the important mass conservation locally on each…

Numerical Analysis · Mathematics 2017-10-24 Yujie Liu , Junping Wang , Qingsong Zou

The development of accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions…

Machine Learning · Computer Science 2023-02-22 Jan N. Fuhg , Craig M. Hamel , Kyle Johnson , Reese Jones , Nikolaos Bouklas

The conformal formulation of the Einstein constraint equations is first reviewed, and we then consider the design, analysis, and implementation of adaptive multilevel finite element-type numerical methods for the resulting coupled nonlinear…

General Relativity and Quantum Cosmology · Physics 2009-04-07 Burak Aksoylu , David Bernstein , Stephen Bond , Michael Holst

Model-free data-driven computational mechanics replaces phenomenological constitutive functions by numerical simulations based on data sets of representative samples in stress-strain space. The distance of strain and stress pairs from the…

Computational Engineering, Finance, and Science · Computer Science 2021-11-29 Kerem Ciftci , Klaus Hackl
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