Estimating Failure in Brittle Materials using Graph Theory

no code implementations • 30 Jul 2018 • M. K. Mudunuru, N. Panda, S. Karra, G. Srinivasan, V. T. Chau, E. Rougier, A. Hunter, H. S. Viswanathan

In brittle fracture applications, failure paths, regions where the failure occurs and damage statistics, are some of the key quantities of interest (QoI).

Uncertainty Quantification

Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications

no code implementations • 5 Jun 2018 • A. Hunter, B. A. Moore, M. K. Mudunuru, V. T. Chau, R. L. Miller, R. B. Tchoua, C. Nyshadham, S. Karra, D. O. Malley, E. Rougier, H. S. Viswanathan, G. Srinivasan

In this paper, five different approaches for reduced-order modeling of brittle fracture in geomaterials, specifically concrete, are presented and compared.

BIG-bench Machine Learning