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In this paper, we define new unfitted finite element methods for numerically approximating the solution of surface partial differential equations using bulk finite elements. The key idea is that the $n$-dimensional hypersurface, $\Gamma…

Numerical Analysis · Mathematics 2014-03-21 Klaus Deckelnick , Charles M. Elliott , Thomas Ranner

We propose an extension of the discretization approaches for multilayer shallow water models, aimed at making them more flexible and efficient for realistic applications to coastal flows. A novel discretization approach is proposed, in…

Numerical Analysis · Mathematics 2018-04-18 Luca Bonaventura , Enrique D. Fernández-Nieto , José Garres-Díaz , Gladys Narbona-Reina

In this paper, we propose a novel high order unfitted finite element method on Cartesian meshes for solving the acoustic wave equation with discontinuous coefficients having complex interface geometry. The unfitted finite element method…

Numerical Analysis · Mathematics 2023-02-06 Zhiming Chen , Yong Liu , Xueshuang Xiang

In this work, we bridge standard adaptive mesh refinement and coarsening on scalable octree background meshes and robust unfitted finite element formulations for the automatic and efficient solution of large-scale nonlinear solid mechanics…

Numerical Analysis · Mathematics 2021-09-01 Santiago Badia , Manuel Caicedo , Alberto F. Martín , Javier Principe

We introduce a new class of unfitted finite element methods with high order accurate numerical integration over curved surfaces and volumes which are only implicitly defined by level set functions. An unfitted finite element method which is…

Numerical Analysis · Mathematics 2015-12-10 Christoph Lehrenfeld

In [Heimann, Lehrenfeld, Preu{\ss}, SIAM J. Sci. Comp. 45(2), 2023, B139 - B165] new geometrically unfitted space-time Finite Element methods for partial differential equations posed on moving domains of higher-order accuracy in space and…

Numerical Analysis · Mathematics 2025-03-14 Fabian Heimann , Christoph Lehrenfeld

This paper proposes a novel paradigm for machine learning that moves beyond traditional parameter optimization. Unlike conventional approaches that search for optimal parameters within a fixed geometric space, our core idea is to treat the…

Machine Learning · Computer Science 2025-10-31 Di Zhang

We first propose a hybridizable discontinuous Galerkin (HDG) method to approximate the solution of a \emph{convection dominated} Dirichlet boundary control problem. Dirichlet boundary control problems and convection dominated problems are…

Numerical Analysis · Mathematics 2021-02-01 Gang Chen , John Richard Singler , Yangwen Zhang

In this chapter, we investigate recently proposed nonlinear conjugate gradient (NCG) methods for shape optimization problems. We briefly introduce the methods as well as the corresponding theoretical background and investigate their…

Optimization and Control · Mathematics 2025-10-14 Sebastian Blauth

Embedded, or immersed, approaches have the goal of reducing to the minimum the computational costs associated with the generation of body-fitted meshes by only employing fixed, possibly Cartesian, meshes over which complex boundaries can…

Numerical Analysis · Mathematics 2025-10-28 Mirco Ciallella

In this article we consider shape optimization problems as optimal control problems via the method of mappings. Instead of optimizing over a set of admissible shapes a reference domain is introduced and it is optimized over a set of…

Optimization and Control · Mathematics 2021-06-09 Johannes Haubner , Martin Siebenborn , Michael Ulbrich

One of the reasons for the success of the finite element method is its versatility to deal with different types of geometries. This is particularly true of problems posed in curved domains of arbitrary shape. In the case of second order…

Numerical Analysis · Mathematics 2020-03-24 Vitoriano Ruas

A grid-overlay finite difference method is proposed for the numerical approximation of the fractional Laplacian on arbitrary bounded domains. The method uses an unstructured simplicial mesh and an overlay uniform grid for the underlying…

Numerical Analysis · Mathematics 2024-04-08 Weizhang Huang , Jinye Shen

In this article we propose a scalable shape optimization algorithm which is tailored for large scale problems and geometries represented by hierarchically refined meshes. Weak scalability and grid independent convergence is achieved via a…

Optimization and Control · Mathematics 2022-05-09 Jose Pinzon , Martin Siebenborn

We consider the geometric optics problem of finding a system of two reflectors that transform a spherical wavefront into a beam of parallel rays with prescribed intensity distribution. Using techniques from optimal transportation theory, it…

Numerical Analysis · Mathematics 2011-11-08 Tilmann Glimm , Nick Henscheid

Diffusion models have demonstrated empirical successes in various applications and can be adapted to task-specific needs via guidance. This paper studies a form of gradient guidance for adapting a pre-trained diffusion model towards…

Machine Learning · Statistics 2024-10-17 Yingqing Guo , Hui Yuan , Yukang Yang , Minshuo Chen , Mengdi Wang

Due to the continuously improving capabilities of mobile edges, recommender systems start to deploy models on edges to alleviate network congestion caused by frequent mobile requests. Several studies have leveraged the proximity of…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-18 Kairui Fu , Shengyu Zhang , Zheqi Lv , Jingyuan Chen , Jiwei Li

This paper describes a node relocation algorithm based on nonlinear optimization which delivers excellent results for both unstructured and structured plane triangle meshes over convex as well as non-convex domains with high curvature. The…

Numerical Analysis · Computer Science 2014-10-23 Daniel Aubram

We consider numerical solution of elliptic problems with heterogeneous diffusion coefficients containing thin highly conductive structures. Such problems arise e.g. in fractured porous media, reinforced materials, and electric circuits. The…

Numerical Analysis · Mathematics 2020-07-22 Fredrik Hellman , Axel Målqvist , Siyang Wang

We detail how to use Newton's method for distortion-based curved $r$-adaption to a discrete high-order metric field while matching a target geometry. Specifically, we combine two terms: a distortion measuring the deviation from the target…

Computational Engineering, Finance, and Science · Computer Science 2023-03-22 Guillermo Aparicio-Estrems , Abel Gargallo-Peiró , Xevi Roca