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In this paper, we introduce a new approach based on distance fields to exactly impose boundary conditions in physics-informed deep neural networks. The challenges in satisfying Dirichlet boundary conditions in meshfree and particle methods…

Numerical Analysis · Mathematics 2022-02-02 N. Sukumar , Ankit Srivastava

In this paper, we present and compare four methods to enforce Dirichlet boundary conditions in Physics-Informed Neural Networks (PINNs) and Variational Physics-Informed Neural Networks (VPINNs). Such conditions are usually imposed by adding…

Numerical Analysis · Mathematics 2023-08-08 S. Berrone , C. Canuto , M. Pintore , N. Sukumar

We present a systematic method for exactly enforcing Dirichlet, Neumann, and Robin type conditions on general quadrilateral domains with arbitrary curved boundaries. Our method is built upon exact mappings between general quadrilateral…

Numerical Analysis · Mathematics 2026-03-24 Suchuan Dong , Yuchuan Zhang

In this work, we have applied physics-informed neural networks (PINN) for solving mesh deformation problems. We used the collocation PINN method to capture the new positions of the vertex nodes while preserving the connectivity information.…

Fluid Dynamics · Physics 2023-01-18 Atakan Aygun , Romit Maulik , Ali Karakus

Physics-informed neural networks offered an alternate way to solve several differential equations that govern complicated physics. However, their success in predicting the acoustic field is limited by the vanishing-gradient problem that…

Machine Learning · Computer Science 2025-03-27 D. Veerababu , Prasanta K. Ghosh

We derive upper and lower bounds on the gradients of Wachspress coordinates defined over any simple convex d-dimensional polytope P. The bounds are in terms of a single geometric quantity h_*, which denotes the minimum distance between a…

Numerical Analysis · Mathematics 2022-02-22 Michael Floater , Andrew Gillette , N. Sukumar

In this paper, we present a novel framework to solve differential equations based on multilayer feedforward network. Previous works indicate that solvers based on neural network have low accuracy due to that the boundary conditions are not…

Numerical Analysis · Mathematics 2019-04-16 Zeyu Liu , Yantao Yang , Qing-Dong Cai

The paper deals with finite element approximations of elliptic Dirichlet boundary control problems posed on two-dimensional polygonal domains. Error estimates are derived for the approximation of the control and the state variables. Special…

Numerical Analysis · Mathematics 2019-01-28 Thomas Apel , Mariano Mateos , Johannes Pfefferer , Arnd Rösch

Most multi-sided transfinite surfaces require cross-derivatives at the boundaries. Here we show a general $n$-sided patch that interpolates all boundaries based on only positional information. The surface is a weighted sum of $n$ Coons…

Graphics · Computer Science 2020-02-27 Péter Salvi

The diffuse-domain, or smoothed boundary, method is an attractive approach for solving partial differential equations in complex geometries because of its simplicity and flexibility. In this method the complex geometry is embedded into a…

Numerical Analysis · Mathematics 2019-12-02 Fei Yu , Zhenlin Guo , John Lowengrub

We present an approach for solving optimal Dirichlet boundary control problems of nonlinear optics by using deep learning. For computing high resolution approximations of the solution to the nonlinear wave model, we propose higher order…

Numerical Analysis · Mathematics 2023-12-27 Nils Margenberg , Franz X. Kärtner , Markus Bause

In this paper, we propose to use the eikonal equation as a boundary condition when advective or normal flow equations in the level set formulation are solved numerically on polyhedral meshes in the three-dimensional domain. Since the level…

Numerical Analysis · Mathematics 2025-04-09 Jooyoung Hahn , Karol Mikula , Peter Frolkovič

In this work we propose a simple but effective high order polynomial correction allowing to enhance the consistency of all kind of boundary conditions for the Euler equations (Dirichlet, characteristic far-field and slip-wall), both in 2D…

Numerical Analysis · Mathematics 2022-09-30 Mirco Ciallella , Elena Gaburro , Marco Lorini , Mario Ricchiuto

In this study, we propose a new numerical scheme for physics-informed neural networks (PINNs) that enables precise and inexpensive solution for partial differential equations (PDEs) in case of arbitrary geometries while strictly enforcing…

Numerical Analysis · Mathematics 2024-07-30 Hamed Saidaoui , Luis Espath , Rául Tempone

In this paper we prove convergence results for the homogenization of the Dirichlet problem with rapidly oscillating boundary data in convex polygonal domains. Our analysis is based on integral representation of solutions. Under a certain…

Analysis of PDEs · Mathematics 2015-06-16 Hayk Aleksanyan , Henrik Shahgholian , Per Sjölin

We present a novel approach that integrates unfitted finite element methods and neural networks to approximate partial differential equations on complex geometries. Easy-to-generate background meshes (e.g., a simple Cartesian mesh) that cut…

Numerical Analysis · Mathematics 2025-12-04 Wei Li , Alberto F. Martín , Santiago Badia

The gradient bounds of generalized barycentric coordinates play an essential role in the $H^1$ norm approximation error estimate of generalized barycentric interpolations. Similarly, the $H^k$ norm, $k>1$, estimate needs upper bounds of…

Numerical Analysis · Mathematics 2026-05-25 Pengjie Tian , Yanqiu Wang

We use a diffuse interface method for solving Poisson's equation with a Dirichlet condition on an embedded curved interface. The resulting diffuse interface problem is identified as a standard Dirichlet problem on approximating regular…

Numerical Analysis · Mathematics 2015-11-23 Matthias Schlottbom

In recent papers the author introduced a simple alternative to isoparametric finite elements of the n-simplex type, to enhance the accuracy of approximations of second-order boundary value problems with Dirichlet conditions, posed in smooth…

Numerical Analysis · Mathematics 2020-03-25 Vitoriano Ruas

Partial differential equations (PDEs) with Dirichlet boundary conditions defined on boundaries with simple geometry have been succesfuly treated using sigmoidal multilayer perceptrons in previous works. This article deals with the case of…

Neural and Evolutionary Computing · Computer Science 2007-05-23 I. E. Lagaris , A. Likas , D. G. Papageorgiou
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