Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail projektu
Období řešení: 1.1.2024 — 31.12.2026
Zdroje financování
Grantová agentura České republiky - Standardní projekty
O projektu
Numerical simulations of inelastic mechanical behavior of heterogeneous quasibrittle material are essential in a number of engineering areas. Specifically in civil engineering they are applied in assessment of critical buildings and infrastructure made of concrete. Robust high-fidelity models require detailed information about material composition which makes them computationally prohibitive. The projects solves this burden by state of the art techniques using machine learning combined with homogenization and domain decomposition. The heart of the project is advanced physically constrained machine learning surrogate capable to locally replace material response. Such artificial intelligence will be used to emulate behavior of (i) spherical representative volume element in the asymptotic expansion homogenization and (ii) regions tiling the decomposed domain. For such goal the homogenization will be equipped with auxiliary modes accounting for strain localization and the domain decomposition will be improved by reduced order modeling of the communication between individual regions.
Klíčová slova mechanical behavior;heterogeneity;fracture;strain localization;homogenization;domain decomposition;surrogate;machine learning
Klíčová slova českymechanické chování;heterogenita;lom;lokalizace deformace;homogenizace;doménová dekompozice;náhradní model;strojové učení
Označení
24-11845S
Originální jazyk
angličtina
Řešitelé
Eliáš Jan, prof. Ing., Ph.D. - hlavní řešitelNovák Lukáš, doc. Ing., Ph.D. - spoluřešitel
Útvary
Ústav stavební mechaniky- odpovědné pracoviště (27.3.2023 - nezadáno)Fakulta stavební- spolupříjemce (1.1.2024 - 31.12.2026)Ústav stavební mechaniky- příjemce (1.1.2023 - 31.12.2026)
Výsledky
NOVÁK, L.; LU, Q.; SHARMA, H.; ROY SARKAR, D.; GOSWAMI, S.; SHIELDS, M. Physics-Informed Polynomial Chaos Expansions: Recent Developments and Comparisons. 14th International Conference on Structural Safety and Reliability. CIMNE, 2025. s. 1-9. Detail
RAISINGER, J.; ZHANG, Q.; BOLANDER, J.; ELIÁŠ, J. Exploring Induced Heterogeneity in Elastic Discrete Mechanical Models. IA-FraMCoS, 2025. p. 1-7. Detail
ELIÁŠ, J.; MARTINÁSEK, J.; LE, J. Application of J-Integral to a Random Elastic Medium. JOURNAL OF ENGINEERING MECHANICS, 2025, vol. 92, no. 3, p. 031006-1 (031006-6 p.)Detail
ELIÁŠ, J.; CUSATIS, G. Do discrete fine-scale mechanical models with rotational degrees of freedom homogenize into a Cosserat or a Cauchy continuum?. Journal of the Mechanics and Physics of Solids, 2026, vol. 207, no. 1, p. 1-22. Detail
ELIÁŠ, J.; CUSATIS, G. Asymptotic Homogenization of Discrete Models With Rotational Degrees of Freedom. IA-FraMCoS, 2025. p. 1-6. Detail
RAISINGER, J.; NOVÁK, L.; ELIÁŠ, J. Data-Driven Prediction of Stress Response for Inelastic Discrete RVE. 2025. p. 169-172. ISBN: 978-80-86246-96-3.Detail
Odpovědnost: Eliáš Jan, prof. Ing., Ph.D.