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We consider discretized two-dimensional PDE-constrained shape optimization problems, in which shapes are represented by triangular meshes. Given the connectivity, the space of admissible vertex positions was recently identified to be a…

Optimization and Control · Mathematics 2023-08-17 Roland Herzog , Estefanía Loayza-Romero

We construct over a given bilinear multi-patch domain a novel $C^s$-smooth mixed degree and regularity isogeometric spline space, which possesses the degree $p=2s+1$ and regularity $r=s$ in a small neighborhood around the edges and…

Numerical Analysis · Mathematics 2024-07-25 Mario Kapl , Aljaž Kosmač , Vito Vitrih

Complex geometries as common in industrial applications consist of multiple patches, if spline based parametrizations are used. The requirements for the generation of analysis-suitable models are increasing dramatically since isogeometric…

Computational Engineering, Finance, and Science · Computer Science 2020-10-30 Christian Hesch , Ustim Khristenko , Rolf Krause , Alexander Popp , Alexander Seitz , Wolfgang Wall , Barbara Wohlmuth

As a powerful statistical image modeling technique, sparse representation has been successfully used in various image restoration applications. The success of sparse representation owes to the development of l1-norm optimization techniques,…

Computer Vision and Pattern Recognition · Computer Science 2015-05-20 Weisheng Dong , Lei Zhang , Guangming Shi , Xiaolin Wu

Shape optimization models with one or more shapes are considered in this chapter. Of particular interest for applications are problems in which where a so-called shape functional is constrained by a partial differential equation (PDE)…

Optimization and Control · Mathematics 2021-07-19 Caroline Geiersbach , Estefania Loayza-Romero , Kathrin Welker

An adaptive direct collocation method is developed for solving optimal control problems constrained by parabolic partial differential equations. The partial differential equation is first reformulated in a variational setting, where the…

Optimization and Control · Mathematics 2026-03-18 Alexander M. Davies , Sara Pollock , Miriam E. Dennis , Anil V. Rao

Solving high dimensional partial differential equations (PDEs) has historically posed a considerable challenge when utilizing conventional numerical methods, such as those involving domain meshes. Recent advancements in the field have seen…

Numerical Analysis · Mathematics 2024-02-05 Xiaokai Huo , Hailiang Liu

Recently, the authors have proposed and analyzed isogeometric tearing and interconnecting (IETI-DP) solvers for multi-patch discretizations in Isogeometric Analysis. Conforming and discontinuous Galerkin settings have been considered. In…

Numerical Analysis · Mathematics 2021-03-04 Rainer Schneckenleitner , Stefan Takacs

The problem of developing an adaptive isogeometric method (AIGM) for solving elliptic second-order partial differential equations with truncated hierarchical B-splines of arbitrary degree and different order of continuity is addressed. The…

Numerical Analysis · Mathematics 2015-04-21 Annalisa Buffa , Carlotta Giannelli

Developing efficient numerical algorithms for the solution of high dimensional random Partial Differential Equations (PDEs) has been a challenging task due to the well-known curse of dimensionality. We present a new solution framework for…

Machine Learning · Computer Science 2019-10-17 Mohammad Amin Nabian , Hadi Meidani

The majority of methods used to compute approximations to the Hamilton-Jacobi-Isaacs partial differential equation (HJI PDE) rely on the discretization of the state space to perform dynamic programming updates. This type of approach is…

Machine Learning · Computer Science 2019-04-15 Vicenç Rubies-Royo , Claire Tomlin

This paper proposes a domain decomposition subspace neural network method for efficiently solving linear and nonlinear partial differential equations. By combining the principles of domain decomposition and subspace neural networks, the…

Numerical Analysis · Mathematics 2025-05-28 Zhenxing Fu , Hongliang Liu , Zhiqiang Sheng , Baixue Xing

We present an isogeometric analysis technique that builds on manifold-based smooth basis functions for geometric modelling and analysis. Manifold-based surface construction techniques are well known in geometric modelling and a number of…

Numerical Analysis · Computer Science 2017-04-05 Musabbir Majeed , Fehmi Cirak

An adaptive regularization strategy for stabilizing Newton-like iterations on a coarse mesh is developed in the context of adaptive finite element methods for nonlinear PDE. Existence, uniqueness and approximation properties are known for…

Numerical Analysis · Mathematics 2015-01-27 Sara Pollock

This work develops a numerical solver based on the combination of isogeometric analysis (IGA) and the tensor train (TT) decomposition for the approximation of partial differential equations (PDEs) on parameter-dependent geometries. First,…

Numerical Analysis · Mathematics 2022-10-05 Ion Gabriel Ion , Dimitrios Loukrezis , Herbert De Gersem

The Laplace eigenvalue problem on circular sectors has eigenfunctions with corner singularities. Standard methods may produce suboptimal approximation results. To address this issue, a novel numerical algorithm that enhances standard…

Numerical Analysis · Mathematics 2025-05-16 Thomas Apel , Philipp Zilk

Building on the successes of local kernel methods for approximating the solutions to partial differential equations (PDE) and the evaluation of definite integrals (quadrature/cubature), a local estimate of the error in such approximations…

Numerical Analysis · Mathematics 2023-08-30 Jonah A. Reeger

We introduce the isogeometric shape optimisation of thin shell structures using subdivision surfaces. Both triangular Loop and quadrilateral Catmull-Clark subdivision schemes are considered for geometry modelling and finite element…

Numerical Analysis · Mathematics 2019-05-21 Kosala Bandara , Fehmi Cirak

We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs and outputs. When just few training data are available, it is…

In the optimization of convex domains under a PDE constraint numerical difficulties arise in the approximation of convex domains in $\mathbb{R}^3$. Previous research used a restriction to rotationally symmetric domains to reduce shape…

Numerical Analysis · Mathematics 2023-11-23 Sören Bartels , Hedwig Keller , Gerd Wachsmuth
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