Discovering chiral auxetic structures with near-zero Poisson's ratio using an active learning strategy

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F24%3A00379362" target="_blank" >RIV/68407700:21260/24:00379362 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.matdes.2024.113133" target="_blank" >https://doi.org/10.1016/j.matdes.2024.113133</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.matdes.2024.113133" target="_blank" >10.1016/j.matdes.2024.113133</a>

Result language

angličtina

Original language name

Discovering chiral auxetic structures with near-zero Poisson's ratio using an active learning strategy

Original language description

In this paper, a set of hexachiral auxetic structural designs with near zero Poisson's ratio (ZPR) characteristics is discovered via the combination of machine learning and experimentally validated finite element simulation. An active learning-enhanced Gaussian process model is utilized to generate multiple designs with near-ZPR properties and discover the boundary of the positive and negative Poisson's ratio. The results show that active learning successfully constructs a probabilistic estimation of the ZPR boundary. A comprehensive analysis of the identified ZPR contour is performed to extract crucial design insights. The findings indicate that the near-ZPR characteristic can be attained through various combinations of geometric parameters. This offers users the flexibility to select the configuration that best aligns with their specific requirements. Additionally, an investigation of the various ZPR configurations that have been discovered is carried out to understand the mechanism that yields near-ZPR property. One discovered near-ZPR design was subsequently fabricated using 3D printing for validation purposes. The experimental outcomes demonstrated a good agreement with the numerical predictions, underscoring the effectiveness of the active learning strategy in uncovering designs that closely approach ZPR conditions.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20501 - Materials engineering

Project

<a href="/en/project/GM22-18033M" target="_blank" >GM22-18033M: High velocity impact dynamics with fast and flash X-ray radiography</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Materials & Design

ISSN

0264-1275

e-ISSN

1873-4197

Volume of the periodical

244

Issue of the periodical within the volume

08

Country of publishing house

GB - UNITED KINGDOM

Number of pages

13

Pages from-to

1-13

UT code for WoS article

001331575200001

EID of the result in the Scopus database

2-s2.0-85198014340