Machine learning-powered modelling of creep strain in shape-memory Nitinol alloys at different combination points of stress and temperature
Published online on March 25, 2025
Abstract
Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, Ahead of Print.
An integrated machine learning system has been developed to make creep strain predictions on shape-memory Nitinol alloys subjected to different stress ranging from 0 to 500 MPa and temperature ranges from 25°C to 80°C. Our work used experimental data from ...
An integrated machine learning system has been developed to make creep strain predictions on shape-memory Nitinol alloys subjected to different stress ranging from 0 to 500 MPa and temperature ranges from 25°C to 80°C. Our work used experimental data from ...