Non-probabilistic robust continuum topology optimization with stress constraints
2018 (English)In: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 59, no 4, p. 1181-1197Article in journal (Refereed) Published
Abstract [en]
This paper proposes a non-probabilistic robust design approach, based on optimization with anti-optimization, to handle unknown-but-bounded loading uncertainties in stress-constrained topology optimization. The objective of the proposed topology optimization problem is to find the lightest structure that respects the worst possible scenario of local stress constraints, given predefined bounds on magnitudes and directions of applied loads. A solution procedure based on the augmented Lagrangian method is proposed, where worst-case local stress constraints are handled without employing aggregation techniques. Results are post-processed, demonstrating that maximum stress of robust solutions is almost insensitive with respect to changes in loading scenarios. Numerical examples also demonstrate that obtained robust solutions satisfy the stress failure criterion for any load condition inside the predefined range of unknown-but-bounded uncertainties in applied loads.
Place, publisher, year, edition, pages
Berlin: Springer, 2018. Vol. 59, no 4, p. 1181-1197
Keywords [en]
Topology optimization, Stress constraints, Uncertainties, Non-probabilistic, Robust, Worst case
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:oru:diva-115981DOI: 10.1007/s00158-018-2122-0ISI: 000465527100009Scopus ID: 2-s2.0-85055949996OAI: oai:DiVA.org:oru-115981DiVA, id: diva2:1897491
Note
The authors received financial support from CNPq (National Council for Research and Development), grant number 306373/2016-5, FAPESP (Sao Paulo Research Foundation), grant number 2015/25199-0, and FAPESC, grant numbers 2017TR1747 and 2017TR784. This study was financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nível Superior - Brasil (CAPES) -Finance Code 001.
2024-09-132024-09-132024-09-30Bibliographically approved