Extraction of mechanical properties of materials through deep learning from instrumented indentation.

ABSTRACT: Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress-strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three-dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are

SUBMITTER: Lu L 

PROVIDER: S-EPMC7132259 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature