A 140 line MATLAB code for topology optimization problems with probabilistic parameters

Uihlein A, Sigmund O, Stingl M (2026)

Publication Type: Journal article

Publication year: 2026

Journal

Structural and Multidisciplinary Optimization Springer Verlag (Germany)

Book Volume: 69

Article Number: 7

Journal Issue: 1

DOI: 10.1007/s00158-025-04167-9

Abstract

We present an efficient 140 line MATLAB code for topology optimization problems that include probabilistic parameters. It is built from the top99neo code by Ferrari and Sigmund and incorporates a stochastic sample-based approach. Old gradient samples are adaptively recombined during the optimization process to obtain a gradient approximation with vanishing approximation error. The method’s performance is thoroughly analyzed for several numerical examples. While we focus on applications in which stochastic parameters describe local material failure, we also present extensions of the code to other settings, such as uncertain load positions or dynamic forces of unknown frequency. The complete code is included in the Appendix and can be downloaded from www.topopt.dtu.dk.

Authors with CRIS profile

Andrian Uihlein Lehrstuhl für Angewandte Mathematik (Kontinuierliche Optimierung) Michael Stingl Lehrstuhl für Angewandte Mathematik (Kontinuierliche Optimierung)

Involved external institutions

Technical University of Denmark / Danmarks Tekniske Universitet (DTU) DK Denmark (DK)

How to cite

APA:

Uihlein, A., Sigmund, O., & Stingl, M. (2026). A 140 line MATLAB code for topology optimization problems with probabilistic parameters. Structural and Multidisciplinary Optimization, 69(1). https://doi.org/10.1007/s00158-025-04167-9

MLA:

Uihlein, Andrian, Ole Sigmund, and Michael Stingl. "A 140 line MATLAB code for topology optimization problems with probabilistic parameters." Structural and Multidisciplinary Optimization 69.1 (2026).

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