AI-assisted study of auxetic structures
dc.contributor.author | Grednev, Sergej | |
dc.contributor.author | Steude, Henrik S. | |
dc.contributor.author | Bronder, Stefan | |
dc.contributor.author | Niggemann, Oliver | |
dc.contributor.author | Jung, Anne | |
dc.date.accessioned | 2023-11-02T10:06:00Z | |
dc.date.available | 2023-11-02T10:06:00Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Acta Polytechnica. 2023, vol. 42, no. , p. 32-36. | |
dc.identifier.issn | 1210-2709 (print) | |
dc.identifier.issn | 1805-2363 (online) | |
dc.identifier.uri | http://hdl.handle.net/10467/112373 | |
dc.description.abstract | In this study, the viability of using machine learning models to predict stress-strain curves of auxetic structures based on geometry-describing parameters is explored. Given the computational cost and time associated with generating these curves through numerical simulations, a machine learning-based approach promises a more efficient alternative. A range of machine learning models, including Artificial Neural Networks, k-Nearest Neighbors Regression, Support Vector Regression, and XGBoost, is implemented and compared regarding the aptitude to predict stress-strain curves under quasi-static compressive loading. Training data is generated using validated finite element simulations. The performance of these models is rigorously tested on data not seen during training. The Feed-Forward Artificial Neural Network emerged as the most proficient model, achieving a Mean Absolute Percentage Error of 0.367 ± 0.230. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | České vysoké učení technické v Praze | cs |
dc.publisher | Czech Technical University in Prague | en |
dc.relation.ispartofseries | Acta Polytechnica | |
dc.relation.uri | https://ojs.cvut.cz/ojs/index.php/APP/article/view/9397 | |
dc.rights | Creative Commons Attribution 4.0 International License | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.title | AI-assisted study of auxetic structures | |
dc.type | article | en |
dc.date.updated | 2023-11-02T10:06:00Z | |
dc.identifier.doi | 10.14311/APP.2023.42.0032 | |
dc.rights.access | openAccess | |
dc.type.status | Peer-reviewed | |
dc.type.version | publishedVersion |
Soubory tohoto záznamu
Tento záznam se objevuje v následujících kolekcích
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je Creative Commons Attribution 4.0 International License