PSI - Issue 33

Available online at www.sciencedirect.com Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2019) 000–000

www.elsevier.com/locate/procedia

ScienceDirect

Procedia Structural Integrity 33 (2021) 1095–1102

IGF26 - 26th International Conference on Fracture and Structural Integrity Defect-Driven Topology Optimisation: TopFat algorithm extended to commercial software for wide-ranging applications Riccardo Caivano a, * , Andrea Tridello a , Davide Paolino a , Filippo Berto b a, * a a to b

a Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy b Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the IGF ExCo Abstract Topology Optimisation (TO) is one of the most popular design tools for additive manufacturing (AM) technologies. Indeed, AM allows creating the complex geometries provided by TO algorithms. However, AM processes such as Selective Laser Melting (SLM) or Electron Beam Melting (EBM) suffer from local slight fluctuations of the process parameters during the building phase, leading to the formation of defects, like pores, clusters of pores, lack of fusion defects, that drive the fatigue response of the material. For this reason, the TO algorithm must consider the presence of the defect population to reliably design the optimised component in the fatigue regime. Recently, the Authors developed a defect-driven TO algorithm with proprietary code, named TopFat, that exploits the Murakami fatigue model to safely design the AM optimised components. In the present paper, the TopFat methodology is extended to the HyperWorks commercial software to unlock a wide-ranging set of industrial and academic applications. This extension allows including the defect population within the TO algorithm without the need for a specific complex code. © 2021 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review Statement: Peer-review under responsibility of the scientific committee of the IGF ExCo Keywords: Topology Optimisation; Fatigue; Defect population, Murakami fatigue limit; Hypermesh an open access ar

* Corresponding author. Tel.: +39 333 262 5290 E-mail address: riccardo.caivano@polito.it

2452-3216 © 2021 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review Statement: Peer-review under responsibility of the scientific committee of the IGF ExCo

2452-3216 © 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the IGF ExCo 10.1016/j.prostr.2021.10.122