1-2 of 2
Machine learning
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Journal Articles

Reduced and All-at-Once Approaches for Model Calibration and Discovery in Computational Solid Mechanics

Accepted Manuscript
Ulrich Römer, Stefan Hartmann, Jendrik-Alexander Tröger, David Anton, Henning Wessels, Moritz Flaschel, Laura De Lorenzis
Journal: Applied Mechanics Reviews
Publisher: ASME
Article Type: Review Articles
Appl. Mech. Rev.
Paper No: AMR-24-1052
https://doi.org/10.1115/1.4066118
Published Online: August 2, 2024
View Article titled, Reduced and All-at-Once Approaches for Model Calibration and Discovery in Computational Solid Mechanics
Open the PDF for Reduced and All-at-Once Approaches for Model Calibration and Discovery in Computational Solid Mechanics in another window
Topics: Calibration, Solid mechanics, Parameter estimation, Artificial neural networks, Computational mechanics, Inverse problems, Machine learning, Physics, Uncertainty
Journal Articles

Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review

Hanxun Jin, Enrui Zhang, Horacio D. Espinosa
Journal: Applied Mechanics Reviews
Publisher: ASME
Article Type: Research-Article
Appl. Mech. Rev. November 2023, 75(6): 061001.
Paper No: AMR-23-1014
https://doi.org/10.1115/1.4062966
Published Online: July 28, 2023
View Article titled, Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
Open the PDF for Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review in another window
Topics: Artificial neural networks, Machine learning, Solid mechanics, Algorithms, Physics, Design, Biomechanics