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We derive optimal order a posteriori error estimates for fully discrete approximations of linear Schr\"odinger-type equations, in the $L^\infty(L^2)-$norm. For the discretization in time we use the Crank-Nicolson method, while for the space…

Numerical Analysis · Mathematics 2013-04-10 Theodoros Katsaounis , Irene Kyza

This paper is concerned with the adaptive numerical treatment of stochastic partial differential equations. Our method of choice is Rothe's method. We use the implicit Euler scheme for the time discretization. Consequently, in each step, an…

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

We present numerical experiments for geophysics electromagnetic (EM) modeling based upon high-order edge elements and supervised $h+p$ refinement approaches on massively parallel computers. Our high-order $h+p$ refinement strategy is based…

In this work, we consider unfitted finite element methods for the numerical approximation of the Stokes problem. It is well-known that this kind of methods lead to arbitrarily ill-conditioned systems. In order to solve this issue, we…

Numerical Analysis · Mathematics 2021-09-30 Santiago Badia , Alberto F. Martín , Francesc Verdugo

We consider an elliptic optimal control problem where the objective functional contains evaluations of the state at a finite number of points. In particular, we use a fidelity term that encourages the state to take certain values at these…

Numerical Analysis · Mathematics 2014-11-19 C. Brett , A. S. Dedner , C. M. Elliott

We propose an adaptive finite element method for the solution of a coefficient inverse problem of simultaneous reconstruction of the dielectric permittivity and magnetic permeability functions in the Maxwell's system using limited boundary…

Numerical Analysis · Mathematics 2016-01-26 Larisa Beilina , Samar Hosseinzadegan

Accurate triangulation of the domain plays a pivotal role in computing the numerical approximation of the differential operators. A good triangulation is the one which aids in reducing discretization errors. In a standard collocation…

Numerical Analysis · Mathematics 2024-02-22 Shylaja G. , Kesavulu Naidu V. , Venkatesh B. , S. M. Mallikarjunaiah

An adaptive finite element method is presented for the elastic scattering of a time-harmonic plane wave by a periodic surface. First, the unbounded physical domain is truncated into a bounded computational domain by introducing the…

Numerical Analysis · Mathematics 2016-05-30 Xue Jiang , Peijun Li , Junliang Lv , Weiying Zheng

In this paper we present a new H(div)-conforming unfitted finite element method for the mixed Poisson problem which is robust in the cut configuration and preserves conservation properties of body-fitted finite element methods. The key is…

Numerical Analysis · Mathematics 2024-09-04 Christoph Lehrenfeld , Tim van Beeck , Igor Voulis

In this paper, we examine a number of additive and multiplicative multilevel iterative methods and preconditioners in the setting of two-dimensional local mesh refinement. While standard multilevel methods are effective for uniform…

Numerical Analysis · Mathematics 2010-01-12 Burak Aksoylu , Stephen Bond , Michael Holst

This paper studies adaptive first-order least-squares finite element methods for second-order elliptic partial differential equations in non-divergence form. Unlike the classical finite element method which uses weak formulations of PDEs…

Numerical Analysis · Mathematics 2019-06-28 Weifeng Qiu , Shun Zhang

State-based peridynamic models provide an important extension of bond-based models that allow the description of general linearly elastic materials. Meshfree discretizations of these nonlocal models are attractive due to their ability to…

Numerical Analysis · Mathematics 2019-03-04 Nathaniel Trask , Benjamin Huntington , David Littlewood

While linear FETI-DP (Finite Element Tearing and Interconnecting - Dual Primal) is an efficient iterative domain decomposition solver for discretized linear PDEs (partial differential equations), nonlinear FETI-DP is its consequent…

Numerical Analysis · Mathematics 2023-12-25 Axel Klawonn , Martin Lanser , Janine Weber

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical…

Numerical Analysis · Computer Science 2015-06-22 John D. Jakeman , Timothy Wildey

This paper presents a density-based topology optimization method for designing 3D thin-walled structures with adaptive meshing. Uniform wall thickness is achieved by simultaneously constraining the minimum and maximum feature sizes using…

Computational Engineering, Finance, and Science · Computer Science 2019-08-29 Yuqing Zhou , Tsuyoshi Nomura , Ercan M. Dede , Kazuhiro Saitou

In this work, we illustrate the connection between adaptive mesh refinement for finite element discretized PDEs and the recently developed \emph{bi-level regularization algorithm}. By adaptive mesh refinement according to data noise,…

Numerical Analysis · Mathematics 2025-10-15 Christian Aarset , Tram Thi Ngoc Nguyen

Optimization problems with $L^1$-control cost functional subject to an elliptic partial differential equation (PDE) are considered. However, different from the finite dimensional $l^1$-regularization optimization, the resulting discretized…

Optimization and Control · Mathematics 2017-09-28 Xiaoliang Song , Bo Chen , Bo Yu

We develop two unfitted finite element methods for the Stokes equations using $H^{\text{div}}$-conforming finite elements. Both methods achieve optimal convergence for velocity, ensure pointwise divergence-free velocity fields, and produce…

Numerical Analysis · Mathematics 2024-09-04 Thomas Frachon , Erik Nilsson , Sara Zahedi

For low-dimensional data sets with a large amount of data points, standard kernel methods are usually not feasible for regression anymore. Besides simple linear models or involved heuristic deep learning models, grid-based discretizations…

Machine Learning · Computer Science 2019-03-01 Bastian Bohn , Michael Griebel , Jens Oettershagen
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