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Related papers: A ROM-based BDDC solver for unfitted p-FEM level-s…

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Computational modeling of multicellular systems may aid in untangling cellular dynamics and emergent properties of biological cell populations. A key challenge is to balance the level of model detail and the computational efficiency, while…

Quantitative Methods · Quantitative Biology 2026-04-22 Erik Blom , Stefan Engblom

Reduced order modeling (ROM) techniques are numerical methods that approximate the solution of parametric partial differential equation (PDE) by properly combining the high-fidelity solutions of the problem obtained for several…

Numerical Analysis · Mathematics 2023-08-08 M. Girfoglio , L. Scandurra , F. Ballarin , G. Infantino , F. Nicolò , A. Montalto , G. Rozza , R. Scrofani , M. Comisso , F. Musumeci

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations, in which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space has a small Kolmogorov…

Numerical Analysis · Mathematics 2020-11-17 Youngkyu Kim , Youngsoo Choi , David Widemann , Tarek Zohdi

We present an efficient B-spline finite element method (FEM) for cloth simulation. While higher-order FEM has long promised higher accuracy, its adoption in cloth simulators has been limited by its larger computational costs while…

Graphics · Computer Science 2026-05-05 Yuqi Meng , Yihao Shi , Kemeng Huang , Zixuan Lu , Ning Guo , Taku Komura , Yin Yang , Minchen Li

A dynamic mode decomposition (DMD) based reduced-order model (ROM) is developed for tracking, detection, and prediction of kinetic plasma behavior. DMD is applied to the high-fidelity kinetic plasma model based on the electromagnetic…

Plasma Physics · Physics 2021-09-16 Indranil Nayak , Mrinal Kumar , Fernando L. Teixeira

An FFT framework which preserves a good numerical performance in the case of domains with large regions of empty space is proposed and analyzed for its application to lattice based materials. Two spectral solvers specially suited to resolve…

Materials Science · Physics 2021-11-10 S. Lucarini , L. Cobian , A. Voitus , J. Segurado

We present a new discretization method for homogeneous convection-diffusion-reaction boundary value problems in 3D that is a non-standard finite element method with PDE-harmonic shape functions on polyhedral elements. The element stiffness…

Numerical Analysis · Mathematics 2017-08-29 Clemens Hofreither , Ulrich Langer , Steffen Weißer

The paper is concerned with the derivation and analysis of nonoverlapping domain decomposition for heterogeneous, anisotropic diffusion problems discretized by the finite element cell-centered (FECC) scheme. Differently from the standard…

Numerical Analysis · Mathematics 2019-05-24 Thanh Hai Ong , Duc Cam Hai Vo , Thi-Thao-Phuong Hoang

Pavarino proved that the additive Schwarz method with vertex patches and a low-order coarse space gives a $p$-robust solver for symmetric and coercive problems. However, for very high polynomial degree it is not feasible to assemble or…

Numerical Analysis · Mathematics 2024-01-09 Pablo D. Brubeck , Patrick E. Farrell

Surrogate neural network-based partial differential equation (PDE) solvers have the potential to solve PDEs in an accelerated manner, but they are largely limited to systems featuring fixed domain sizes, geometric layouts, and boundary…

Machine Learning · Computer Science 2025-01-10 Chenkai Mao , Robert Lupoiu , Tianxiang Dai , Mingkun Chen , Jonathan A. Fan

A balancing domain decomposition by constraints (BDDC) algorithm with adaptive primal constraints in variational form is introduced and analyzed for high-order mortar discretization of two-dimensional elliptic problems with high varying and…

Numerical Analysis · Mathematics 2017-04-26 Jie Peng , Shi Shu , Junxian Wang

The paper studies several approaches to numerical integration over a domain defined implicitly by an indicator function such as the level set function. The integration methods are based on subdivision, moment--fitting, local…

Numerical Analysis · Mathematics 2016-01-26 Maxim Olshanskii , Danil Safin

Deep learning-based reduced order models (DL-ROMs) have been recently proposed to overcome common limitations shared by conventional ROMs - built, e.g., exclusively through proper orthogonal decomposition (POD) - when applied to nonlinear…

Numerical Analysis · Mathematics 2022-01-26 Federico Fatone , Stefania Fresca , Andrea Manzoni

In this paper, we propose a novel unfitted finite element method for the simulation of multiple body contact. The computational mesh is generated independently of the geometry of the interacting solids, which can be arbitrarily complex. The…

Numerical Analysis · Computer Science 2017-04-10 Susanne Claus , Pierre Kerfriden

Reduced-order models (ROMs) are essential for rapid simulation of complex biomechanical systems and for bridging the gap between high fidelity models and clinical application. However, ROMs for tissue growth and remodeling (G&R) remain…

Computational Engineering, Finance, and Science · Computer Science 2026-04-16 Joel Laudo , Adrian Buganza Tepole

The investigation of fluid-solid systems is very important in a lot of industrial processes. From a computational point of view, the simulation of such systems is very expensive, especially when a huge number of parametric configurations…

The use of model-based numerical simulation of wave propagation in rooms for engineering applications requires that acoustic conditions for multiple parameters are evaluated iteratively and this is computationally expensive. We present a…

In this paper, we develop an adaptive high-order surface finite element method (FEM) incorporating the spectral deferred correction method for chain contour discretization to solve polymeric self-consistent field equations on general curved…

Numerical Analysis · Mathematics 2021-08-03 Kai Jiang , Xin Wang , Jianggang Liu , Huayi Wei

Solving complex partial differential equations is vital in the physical sciences, but often requires computationally expensive numerical methods. Reduced-order models (ROMs) address this by exploiting dimensionality reduction to create fast…

Machine Learning · Computer Science 2026-05-19 Robert Stephany , William Michael Anderson , Youngsoo Choi

In this paper we propose to use model reduction techniques for speeding up the diagonalization-based parallel-in-time (ParaDIAG) preconditioner, for iteratively solving all-at-once systems from evolutionary PDEs. In particular, we use the…

Numerical Analysis · Mathematics 2020-12-17 Jun Liu , Zhu Wang
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