Similarity control in topology optimization under static and crash loading scenarios

Muhammad Salman Yousaf, Mariusz Bujny, Nathan Zurbrugg, Duane Detwiler, Fabian Duddeck

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Topology Optimization (TO) redistributes the material within a design space to optimize certain objective functions under given constraints. Currently available TO methods do not consider the designer's preferences about the final material layout in the optimized design. Contrarily, often an improved design similar to a reference design is required because of the economic, manufacturing or assembly restrictions. In this article, the proposed heuristic similarity control methods like the Energy Scaling Method (ESM), weak passive material method, and an intuitive method of modified design domain are compared with the formal mathematical method of Optimality Criteria (OC)-based Solid Isotropic Material with Penalization (SIMP) with a similarity constraint. Initially, the methods are coupled with Hybrid Cellular Automata (HCA) and OC-based SIMP for the TO of a cantilever beam under a static point load. The ESM is found to be the most effective and further tested for similarity-based TO with HCA in crash loading scenarios. The results show that ESM can be used to control the TO process effectively.

Original languageEnglish
Pages (from-to)1523-1538
Number of pages16
JournalEngineering Optimization
Volume53
Issue number9
DOIs
StatePublished - 2021

Keywords

  • Energy Scaling Method (ESM)
  • Hybrid Cellular Automata (HCA)
  • Optimality Criteria (OC)-based SIMP
  • Similarity-Based Topology Optimization (TO)

Fingerprint

Dive into the research topics of 'Similarity control in topology optimization under static and crash loading scenarios'. Together they form a unique fingerprint.

Cite this