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A novel and efficient approach which is based on the framework of isogeometric analysis for elliptic homogenization problems is proposed. These problems possess highly oscillating coefficients leading to extremely high computational…

Numerical Analysis · Mathematics 2017-10-31 H. Nguyen-Xuan , T. Hoang , V. P. Nguyen

In the design of electromagnetic devices the accurate representation of the geometry plays a crucial role in determining the device performance. For accelerator cavities, in particular, controlling the frequencies of the eigenmodes is…

Computational Physics · Physics 2017-11-07 Jacopo Corno , Carlo de Falco , Herbert De Gersem , Sebastian Schöps

Design-space dimensionality reduction is essential to mitigate the cost of high-fidelity simulation-based optimization, especially when dealing with high-dimensional geometric parameterizations. Traditional linear techniques, such as…

Optimization and Control · Mathematics 2025-07-23 Andrea Serani , Giorgio Palma , Jeroen Wackers , Domenico Quagliarella , Stefano Gaggero , Matteo Diez

In high-dimensional and/or non-parametric regression problems, regularization (or penalization) is used to control model complexity and induce desired structure. Each penalty has a weight parameter that indicates how strongly the structure…

Machine Learning · Statistics 2017-03-30 Jean Feng , Noah Simon

This work deals with shape optimization of electric machines using isogeometric analysis. Isogeometric analysis is particularly well suited for shape optimization as it allows to easily modify the geometry without remeshing the domain. A…

Computational Engineering, Finance, and Science · Computer Science 2021-06-03 Melina Merkel , Peter Gangl , Sebastian Schöps

We propose and investigate a mesh deformation technique for PDE constrained shape optimization. Introducing a gradient penalization to the inner product for linearized shape spaces, mesh degeneration can be prevented within the optimization…

Optimization and Control · Mathematics 2021-06-09 Martin Siebenborn , Andreas Vogel

This work develops an algorithm for PDE-constrained shape optimization based on Lipschitz transformations. Building on previous work in this field, the $p$-Laplace operator is utilized to approximate a descent method for Lipschitz shapes.…

Optimization and Control · Mathematics 2023-04-24 Peter Marvin Müller , Jose Pinzon , Thomas Rung , Martin Siebenborn

This paper presents a spline-based parameterisation framework for plane graphs. The plane graph is characterised by a collection of curves forming closed loops that fence-off planar faces which have to be parameterised individually. Hereby,…

Numerical Analysis · Mathematics 2024-09-02 Jochen Hinz

Program behavior may depend on parameters, which are either configured before compilation time, or provided at run-time, e.g., by sensors or other input devices. Parametric program analysis explores how different parameter settings may…

Programming Languages · Computer Science 2014-06-23 Thomas M. Gawlitza , Martin D. Schwarz , Helmut Seidl

Ceramic is a material frequently used in industry because of its favorable properties. Common approaches in shape optimization for ceramic structures aim to minimize the tensile stress acting on the component, as it is the main driver for…

Optimization and Control · Mathematics 2017-05-17 Matthias Bolten , Hanno Gottschalk , Camilla Hahn , Mohamed Saadi

This work presents an efficient quadrature rule for shell analysis fully integrated in CAD by means of Isogeometric Analysis (IGA). General CAD-models may consist of trimmed parts such as holes, intersections, cut-offs etc. Therefore, IGA…

Computational Engineering, Finance, and Science · Computer Science 2023-08-09 Michael Loibl , Leonardo Leonetti , Alessandro Reali , Josef Kiendl

The Projected Gradient Descent (PGD) algorithm is a widely used and efficient first-order method for solving constrained optimization problems due to its simplicity and scalability in large design spaces. Building on recent advancements in…

Optimization and Control · Mathematics 2025-06-18 Lucka Barbeau , Marc-Étienne Lamarche-Gagnon , Florin Ilinca

Shell structures with a high stiffness-to-weight ratio are desirable in various engineering applications. In such scenarios, topology optimization serves as a popular and effective tool for shell structures design. Among the topology…

Optimization and Control · Mathematics 2023-12-12 Qiong Pan , Xiaoya Zhai , Falai Chen

We introduce a novel computational framework for the multiscale simulation of higher-order continua that allows for the consideration of first-, second- and third- order effects at both micro- and macro-level. In line with classical…

Computational Engineering, Finance, and Science · Computer Science 2022-03-08 Felix Schmidt , Melanie Krüger , Marc-Andre Keip , Christian Hesch

The optimization algorithms are crucial in training physics-informed neural networks (PINNs), as unsuitable methods may lead to poor solutions. Compared to the common gradient descent (GD) algorithm, implicit gradient descent (IGD)…

Machine Learning · Computer Science 2025-08-04 Xianliang Xu , Ting Du , Wang Kong , Bin Shan , Ye Li , Zhongyi Huang

We consider elliptic problems in multipatch isogeometric analysis (IGA) where the patch parameterizations may be singular. Specifically, we address cases where certain dimensions of the parametric geometry diminish as the singularity is…

Numerical Analysis · Mathematics 2025-07-30 Tobias Jonsson , Mats G. Larson , Karl Larsson

Partial Differential Equations (PDEs) underpin many scientific phenomena, yet traditional computational approaches often struggle with complex, nonlinear systems and irregular geometries. This paper introduces the AMG method, a Multi-Graph…

Machine Learning · Computer Science 2025-02-10 Zhihao Li , Haoze Song , Di Xiao , Zhilu Lai , Wei Wang

Geometric programming is an important class of optimization problems that enable practitioners to model a large variety of real-world applications, mostly in the field of engineering design. In many real life optimization problem…

Numerical Analysis · Computer Science 2011-02-19 A. K. Ojha , K. K. Biswal

We investigate an optimization problem governed by an elliptic partial differential equation with uncertain parameters. We introduce a robust optimization framework that accounts for uncertain model parameters. The resulting non-linear…

Optimization and Control · Mathematics 2019-09-24 Alessandro Alla , Michael Hinze , Philip Kolvenbach , Oliver Lass , Stefan Ulbrich

In this paper, we present the isogeometric least-squares collocation (IGA-L) method, which determines the numerical solution by making the approximate differential operator fit the real differential operator in a least-squares sense. The…

Numerical Analysis · Mathematics 2018-04-19 Hongwei Lin , Yunyang Xiong , Xiao Wang , Qianqian Hu
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