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We present a finite element approach for diffusion problems with thermal fluctuations based on a fluctuating hydrodynamics model. The governing transport equations are stochastic partial differential equations with a fluctuating forcing…

Numerical Analysis · Mathematics 2024-03-21 P. Martínez-Lera , M. De Corato

Surface meltwater from glaciers and ice sheets contributes significantly to sea-level rise, yet the processes governing its transport and retention within cold firn remain poorly constrained, particularly in multiple dimensions. Here we…

Fluid Dynamics · Physics 2026-04-01 Mohammad Afzal Shadab , Howard A. Stone , Reed M. Maxwell

In climate science, models for global warming and weather prediction face significant challenges due to the limited availability of high-quality data and the difficulty in obtaining it, making data efficiency crucial. In the past few years,…

Machine Learning · Computer Science 2024-10-10 Sameera S Kashyap , Raj Abhijit Dandekar , Rajat Dandekar , Sreedath Panat

The Finite Element Method (FEM) is a powerful computational tool for solving partial differential equations (PDEs). Although commercial and open-source FEM software packages are widely available, an independent implementation of FEM…

Numerical Analysis · Mathematics 2025-02-06 Victor Dominguez , Alejandro Duque

We present the W-SLDA Toolkit, a general-purpose software package for simulating ultracold Fermi gases within the framework of density functional theory and its time-dependent extensions. The toolkit enables fully microscopic studies of…

Quantum Gases · Physics 2026-02-10 Gabriel Wlazłowski , Piotr Magierski , Michael McNeil Forbes , Aurel Bulgac

A CFD-driven deterministic symbolic identification algorithm for learning explicit algebraic Reynolds-stress models (EARSM) from high-fidelity data is developed building on the frozen-training SpaRTA algorithm of [1]. Corrections for the…

Fluid Dynamics · Physics 2022-03-14 I. Ben Hassan SaÏdi , M. Schmelzer , P. Cinnella , F. Grasso

Numerical models are widely used to simulate the earth system, but they are computationally expensive and often depend on many uncertain input parameters. Their effective use requires calibration and uncertainty quantification, which…

Methodology · Statistics 2026-03-06 Tristan Contant , Yawen Guan , Ander Wilson , Adrian K. Turner , Deborah Sulsky

Addressing complex meteorological processes at a fine spatial resolution requires substantial computational resources. To accelerate meteorological simulations, researchers have utilized neural networks to downscale meteorological variables…

Atmospheric and Oceanic Physics · Physics 2024-04-30 Jing Hu , Honghu Zhang , Peng Zheng , Jialin Mu , Xiaomeng Huang , Xi Wu

Though machine learning has achieved notable success in modeling sequential and spatial data for speech recognition and in computer vision, applications to remote sensing and climate science problems are seldom considered. In this paper, we…

Machine Learning · Computer Science 2019-10-22 Yimeng Min , S. Karthik Mukkavilli , Yoshua Bengio

Accurate, high-resolution projections of the Greenland ice sheet's surface mass balance (SMB) and surface temperature are essential for understanding future sea-level rise, yet current approaches are either computationally demanding or…

Geophysics · Physics 2026-04-15 Nils Bochow , Philipp Hess , Alexander Robinson

Multiscale Finite Element Methods (MsFEMs) are now well-established finite element type approaches dedicated to multiscale problems. They first compute local, oscillatory, problem-dependent basis functions that generate a suitable…

Numerical Analysis · Mathematics 2023-08-03 Rutger A. Biezemans , Claude Le Bris , Frédéric Legoll , Alexei Lozinski

For most finite element simulations, boundary-conforming meshes have significant advantages in terms of accuracy or efficiency. This is particularly true for complex domains. However, with increased complexity of the domain, generating a…

Numerical Analysis · Mathematics 2021-04-07 Jan Helmig , Fabian Key , Marek Behr , Stefanie Elgeti

T-IFISS is a finite element software package for studying finite element solution algorithms for deterministic and parametric elliptic partial differential equations. The emphasis is on self-adaptive algorithms with rigorous error control…

Numerical Analysis · Mathematics 2020-03-11 Alex Bespalov , Leonardo Rocchi , David Silvester

This article's main scope is the presentation of a computational method for the simulation of contact problems within the finite element method involving complex and rough surfaces. The approach relies on the MPJR (eMbedded Profile for…

Soft Condensed Matter · Physics 2025-04-03 Jacopo Bonari , Marco Paggi , Daniele Dini

Within the landscape of modified theories of gravity, progress in understanding the behaviour of, and developing tests for, screening mechanisms has been hindered by the complexity of the field equations involved, which are nonlinear in…

General Relativity and Quantum Cosmology · Physics 2021-03-31 Jonathan Braden , Clare Burrage , Benjamin Elder , Daniela Saadeh

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

Differentiable physical simulators are proving to be valuable tools for developing data-driven models for computational fluid dynamics (CFD). In particular, these simulators enable end-to-end training of machine learning (ML) models…

Fluid Dynamics · Physics 2025-11-12 Hojin Kim , Varun Shankar , Venkatasubramanian Viswanathan , Romit Maulik

AFSI is a novel, open-source fluid-structure interaction (FSI) solver that extends the capabilities of the FEniCS finite element library through an immersed boundary (IB) framework. Designed to simulate large deformations in hyperelastic…

Computational Physics · Physics 2025-09-03 Pengfei Ma , Li Cai , Xuan Wang , Hao Gao

The variational multiscale (VMS) formulation formally segregates the evolution of the coarse-scales from the fine-scales. VMS modeling requires the approximation of the impact of the fine scales in terms of the coarse scales. In linear…

Computational Physics · Physics 2021-11-16 Aniruddhe Pradhan , Karthik Duraisamy

This paper presents an educational code written using FEniCS, based on the level set method, to perform compliance minimization in structural optimization. We use the concept of distributed shape derivative to compute a descent direction…

Optimization and Control · Mathematics 2018-01-30 Laurain Antoine
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