Discovering chiral auxetic structures with near-zero Poisson's ratio using an active learning strategy
Identifikátory výsledku
Kód výsledku v 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>
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Discovering chiral auxetic structures with near-zero Poisson's ratio using an active learning strategy
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Discovering chiral auxetic structures with near-zero Poisson's ratio using an active learning strategy
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20501 - Materials engineering
Návaznosti výsledku
Projekt
<a href="/cs/project/GM22-18033M" target="_blank" >GM22-18033M: Dynamika rázů s využitím rychlé rentgenové radiografie a zábleskového rentgenového zdroje</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Materials & Design
ISSN
0264-1275
e-ISSN
1873-4197
Svazek periodika
244
Číslo periodika v rámci svazku
08
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
13
Strana od-do
1-13
Kód UT WoS článku
001331575200001
EID výsledku v databázi Scopus
2-s2.0-85198014340