A review of the application of machine learning and data mining approaches in continuum materials mechanics

Frederic E. Bock, Roland C. Aydin, Christian J. Cyron, Norbert Huber, Surya R. Kalidindi & Benjamin Klusemann
Machine learning tools represent key enablers for empowering material scientists and engineers to accelerate the development of novel materials, processes and techniques. One of the aims of using such approaches in the field of materials science is to achieve high-throughput identification and quantification of essential features along the process-structure-property-performance chain. In this contribution, machine learning and statistical learning approaches are reviewed in terms of their successful application to specific problems in the field of continuum...
This data repository is not currently reporting usage information. For information on how your repository can submit usage information, please see our documentation.