PSI - Issue 66

Available online at www.sciencedirect.com Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2025) 000–000

www.elsevier.com/locate/procedia

ScienceDirect

Procedia Structural Integrity 66 (2024) 502–510

8th International Conference on Crack Paths Structural stability investigation in bioinspired metamaterials based on glass sponge microstructures Umberto De Maio a , Fabrizio Greco a , Francesco Fabbrocino b , Raimondo Luciano c , Paolo Nevone Blasi a , Andrea Pranno a *

a Department of Civil Engineering, University of Calabria, Via P. Bucci, Cubo 39B, 87036 Rende, Cosenza, Italy b Department of Civil Engineering, Digital University Pegaso,Centro Direzionale ISOLA F2, 80143, Napoli (NA), Italy c Department of Engineering, Parthenope University of Naples, Centro Direzionale Isola C4, 80133 Napoli, Italy

Abstract This work presents an innovative design for a lattice microstructure, drawing inspiration from the deep-sea glass sponge Euplectella aspergillum. The computational framework developed enables real-time synchronization between COMSOL Multiphysics and MATLAB, utilizing a genetic algorithm and artificial neural networks to optimize the microstructure. During the optimization procedure, key geometric parameters were adjusted while keeping the representative volume element's fraction constant to maximize the critical load factor under uniaxial vertical compression. The genetic algorithm evaluated numerous parameter combinations, while neural networks predicted the occurrence of either local or global instability for each configuration. Designs lying to global instability were penalized, favoring local instability in the final optimized structure. The results indicated a 65% enhancement in ultimate buckling deformation and a 34% increase in buckling load compared to the unoptimized design. © 2025 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 CP 2024 Organizers Keywords: Lattice microstructure optimization; Genetic algorithm; Buckling instability; Artificial neural networks; 1. Introduction Recently, due to their ability to replicate the multifunctional qualities of nature, bioinspired materials have become the focus of study in several sectors (Wang et al., 2020). These materials have led to innovations in mechanical © 2025 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 CP 2024 Organizers

* Corresponding author. E-mail address: andrea.pranno@unical.it

2452-3216 © 2025 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 CP 2024 Organizers

2452-3216 © 2025 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 CP 2024 Organizers 10.1016/j.prostr.2024.11.103