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

Unsupervised Machine Learning Based on Non-Negative Tensor Factorization for Analyzing Reactive-Mixing

no code implementations • 16 May 2018 • V. V. Vesselinov, M. K. Mudunuru, S. Karra, D. O. Malley, B. S. Alexandrov

An attractive aspect of the proposed ML method is that it ensures the extracted features are non-negative, which are important to obtain a meaningful deconstruction of the mixing processes.

BIG-bench Machine Learning Clustering