Modeling of structural failure of Zircaloy claddings induced by multiple hydride cracks

Liu, Ruijie; Mostafa, Ahmed; Liu, Zhijun

doi:10.1007/s10704-018-0312-9

Cited by 9 publications

(1 citation statement)

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“…At larger length scales, finite element method (FEM) models are used from microstructural to the macro. Liu et al examined a component level model informed by grain-scale simulations of hydrides and found that a linking effect between individual hydrides influenced fracture crack paths and material failure 16 . Therefore, it is necessary to examine populations of hydrides to fully understand how larger scale systems are affected.…”

Section: Introductionmentioning

confidence: 99%

Predictive machine learning approaches for the microstructural behavior of multiphase zirconium alloys

Hasan

Capolungo

Zikry

2023

Sci Rep

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Zirconium alloys are widely used in harsh environments characterized by high temperatures, corrosivity, and radiation exposure. These alloys, which have a hexagonal closed packed (h.c.p.) structure thermo-mechanically degrade, when exposed to severe operating environments due to hydride formation. These hydrides have a different crystalline structure, than the matrix, which results in a multiphase alloy. To accurately model these materials at the relevant physical scale, it is necessary to fully characterize them based on a microstructural fingerprint, which is defined here as a combination of features that include hydride geometry, parent and hydride texture and crystalline structure of these multiphase alloys. Hence, this investigation will develop a reduced order modeling approach, where this microstructural fingerprint is used to predict critical fracture stress levels that are physically consistent with microstructural deformation and fracture modes. Machine Learning (ML) methodologies based on Gaussian Process Regression, random forests, and multilayer perceptrons (MLP) were used to predict material fracture critical stress states. MLPs, or neural networks, had the highest accuracy on held-out test sets across three predetermined strain levels of interest. Hydride orientation, grain orientation or texture, and hydride volume fraction had the greatest effect on critical fracture stress levels and had partial dependencies that were highly significant, and in comparison hydride length and hydride spacing have less effects on fracture stresses. Furthermore, these models were also used accurately predicted material response to nominal applied strains as a function of the microstructural fingerprint.

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Section: Introductionmentioning

confidence: 99%