Project detail
Active Machine Learning for Identification of Characteristic Fatigue Curve
Duration: 1.1.2024 — 31.12.2025
Funding resources
Ministerstvo školství, mládeže a tělovýchovy ČR - Mobility - ČR - Německo (období realizace projektů 2024-2025)
On the project
Projekt je zaměřen na tvorbu obecného algoritmu pro identifikaci únavové křivky s využitím adaptivního statistického vzorkování a metody rozvoje polynomiálního chaosu. V průběhu projektu bude na české straně vyvinut numerický algortimus a na německé straně budou provedeny laboratorní experimenty pro validaci matematických modelů.
Description in English
During the proposed project, a novel methodology for the adaptive sequential construction of characteristic
fatigue curve of material or product, reflecting uncertainties affecting the experimental program. The proposed
method will be based on the theory of probability and polynomial chaos expansion. The developed theoretical
method will be further implemented into a Python numerical algorithm. The numerical algorithm will serve for
the identification of optimal experimental design for sequential improvement of the accuracy of identified fatigue
curve, leading to a significant reduction of the number of laboratory experiments while maintaining the accuracy
of identification. Laboratory experiments for the construction and verification of the proposed algorithm will be
conducted by German team members, who have rich experience in this topic. Initially, the optimal number and
design of initial laboratory experiments will be determined in cooperation with Czech team, reflecting specific
conditions of experiments and variability of material parameters of specimens leading to uncertainty in the
fatigue curve. The obtained results together with data from the literature will be utilized for the development of
the method by Czech team. Once available, the algorithm will be verified using laboratory experiments for the
identification of a fatigue curve and results will be compared to the existing approach.The theoretical
background of the developed method and its implementation to the numerical algorithm will be presented in
2024 at international conference and published in conference proceedings indexed by Scopus/WoS – a result
type D according to IS VaVAI – RIV. Experimental applications and verification of the method will be presented
similarly in 2025 – a result type D
Keywords
aktivní učení, rozvoj polynomiálního chaosu, únava materiálu, kvantifikace nejistot
Key words in English
active learning, polynomial chaos expansion, material fatigue, Uncertainty Quantification
Mark
8J24DE002
Default language
Czech
People responsible
Novák Lukáš, doc. Ing., Ph.D. - principal person responsible
Units
Institute of Structural Mechanics
- responsible department (6.6.2023 - not assigned)
Institute of Structural Mechanics
- beneficiary (6.6.2023 - not assigned)
Results
NOVÁK, L.; GAKIS, A.; KŘÍŽEK, M.; NOVÁK, D.; SPYRIDIS, P. Uncertainty Quantification of Soil-Structure Interaction in Tunnel Linings by Polynomial Chaos Expansion. In 20th International Probabilistic Workshop. Springer Science and Business Media Deutschland GmbH, 2024. p. 512-519. ISBN: 9783031602702.
Detail
Responsibility: Novák Lukáš, doc. Ing., Ph.D.