Stochastic virtual tests for high-temperature ceramic matrix composites

Brian N. Cox, Hrishikesh A. Bale, Matthew Begley, Matthew Blacklock, Bao Chan Do, Tony Fast, Mehdi Naderi, Mark Novak, Varun P. Rajan, Renaud G. Rinaldi, Robert O. Ritchie, Michael N. Rossol, John H. Shaw, Olivier Sudre, Qingda Yang, Frank W. Zok, David B. Marshall

Research output: Contribution to journalArticlepeer-review

70 Citations (Scopus)


We review the development of virtual tests for high-temperature ceramic matrix composites with textile reinforcement. Success hinges on understanding the relationship between the microstructure of continuous-fiber composites, including its stochastic variability, and the evolution of damage events leading to failure. The virtual tests combine advanced experiments and theories to address physical, mathematical, and engineering aspects of material definition and failure prediction. Key new experiments include surface image correlation methods and synchrotron-based, micrometer-resolution 3D imaging, both executed at temperatures exceeding 1,500°C. Computational methods include new probabilistic algorithms for generating stochastic virtual specimens, as well as a new augmented finite element method that deals efficiently with arbitrary systems of crack initiation, bifurcation, and coalescence in heterogeneous materials. Conceptual advances include the use of topology to characterize stochastic microstructures. We discuss the challenge of predicting the probability of an extreme failure event in a computationally tractable manner while retaining the necessary physical detail.

Original languageEnglish
Pages (from-to)479-529
Number of pages51
JournalAnnual Review of Materials Research
Early online date7 May 2014
Publication statusPublished - Jul 2014
Externally publishedYes


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