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Information × Registration Number 0224U031491, 0122U001858 , R & D reports Title Modelling of functional and structural properties of shape memory alloys by machine learning methods popup.stage_title Head Yasnii Oleh P., Доктор технічних наук Registration Date 01-05-2024 Organization Ternopil National Technical University named after Ivan Puluj popup.description2 Shape memory alloys (SMAs) are widely used in medicine, motor engineering, civil and industrial construction. During operation, such structural elements are subjected to long-term cyclic loading, which can lead to the loss of functional properties, depletion of lifetime and their destruction. For such structural elements, it is important to ensure the necessary functional properties and durability during operation. Therefore, the development of methods for predicting the durability of SMA, that are based on the revealed patterns of pseudo-elastic behaviour and durability of these materials, considering the influence of stress ratio is also relevant. As a result of the implementation of the project stage, a methodology for predicting the fatigue life and functional properties of alloys with shape memory was developed, which is based on machine learning methods. There were obtained the main regularities of the influence of the stress ratio on the functional properties of the pseudo-elastic nickel-titanium shape memory alloy. The main regularities of the influence of the load cycle asymmetry on the fatigue life of pseudo-elastic nickel-titanium alloy with shape memory have been revealed. For the first time, generalized data on the change of functional properties and fatigue life, considering the influence of load cycle asymmetry, based on the use of strength, deformation and energy criteria of destruction, were obtained. In contrast to the existing methods for predicting the fatigue life of shape memory alloys, the models were built, and physically based methods were created using various machine learning methods for predicting the fatigue life of shape memory alloys based on the application of failure criteria, taking into account the influence of load cycle asymmetry. Expected scientific and practical value of the results: prevention of possible accidents and destruction of structural elements and buildings, loss of working capacity of humans. Product Description popup.authors Baran Denys Ya. Havrysh Roman M. Marushchak Olena V. Marchenko Liubov O. Myshkovych Olha V. Pasternak Yaroslav M. Sorochak Andrii P. Tsymbaliuk Liubov I. Chornomaz Nataliia Yu. Yarema Ihor T. Yasnii Oleh P. popup.nrat_date 2024-05-01 Close
R & D report
Head: Yasnii Oleh P.. Modelling of functional and structural properties of shape memory alloys by machine learning methods. (popup.stage: ). Ternopil National Technical University named after Ivan Puluj. № 0224U031491
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Updated: 2026-03-26
