An improvement in data interpretation to estimate residual stresses and mechanical properties using instrumented indentation: A comparison between machine learning and Kriging model
(2022)
Journal Article
Salmani Ghanbari, S., & Mahmoudi, A. H. (2022). An improvement in data interpretation to estimate residual stresses and mechanical properties using instrumented indentation: A comparison between machine learning and Kriging model. Engineering Applications of Artificial Intelligence, 114, Article 105186. https://doi.org/10.1016/j.engappai.2022.105186
The instrumented indentation method has been introduced as an effective means of estimating surface residual stresses. This technique has also been widely utilized to measure mechanical properties of the materials. Most studies in recent years have b... Read More about An improvement in data interpretation to estimate residual stresses and mechanical properties using instrumented indentation: A comparison between machine learning and Kriging model.