Adaptive immersed isogeometric level-set topology optimization

Journal Article (2025)
Author(s)

Mathias R. Schmidt (Lawrence Livermore National Laboratory)

L.F.P. Noel (TU Delft - Computational Design and Mechanics)

Nils Wunsch (University of Colorado - Boulder)

Keenan Doble (University of Colorado - Boulder)

John A. Evans (University of Colorado - Boulder)

Kurt Maute (University of Colorado - Boulder)

Research Group
Computational Design and Mechanics
DOI related publication
https://doi.org/10.1007/s00158-024-03921-9
More Info
expand_more
Publication Year
2025
Language
English
Research Group
Computational Design and Mechanics
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
1
Volume number
68
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

This paper presents for the first time an adaptive immersed approach for level-set topology optimization using higher-order truncated hierarchical B-spline discretizations for design and state variable fields. Boundaries and interfaces are represented implicitly by the iso-contour of one or multiple level-set functions. An immersed finite element method, the eXtended IsoGeometric Analysis, is used to predict the physical response. The proposed optimization framework affords different adaptively refined higher-order B-spline discretizations for individual design and state variable fields. The increased continuity of higher-order B-spline discretizations together with local refinement enables direct control over the accuracy of the representation of each field while simultaneously reducing computational cost compared to uniformly refined discretizations. A flexible mesh adaptation strategy enables local refinement based on geometric measures or physics-based error indicators. These adaptive discretization and analysis approaches are integrated into gradient-based optimization schemes, evaluating the design sensitivities using the adjoint method. Numerical studies illustrate the features of the proposed framework with static, linear elastic, multi-material, two- and three-dimensional problems. The examples provide insight into the effect of refining the design variable field on the optimization result and the convergence rate of the optimization process. Using coarse higher-order B-spline discretizations for level-set fields promotes the development of smooth designs and suppresses the emergence of small features. Moreover, adaptive mesh refinement for state variable fields results in a reduction of overall computational cost. Higher-order B-spline discretizations are especially interesting when evaluating gradients of state variable fields due to their higher inter-element continuity.

Files

S00158-024-03921-9.pdf
(pdf | 4.55 Mb)
- Embargo expired in 27-06-2025
License info not available