A data science approach for analysis and reconstruction of spinodal-like composition fields in irradiated FeCrAl alloys

Pachaury, Yash; Kumagai, Tomohisa; Wharry, Janelle P.; El-Azab, Anter

doi:10.1016/j.actamat.2022.118019

A data science approach for analysis and reconstruction of spinodal-like composition fields in irradiated FeCrAl alloys

Journal Article · Sat May 14 00:00:00 EDT 2022 · Acta Materialia

DOI:https://doi.org/10.1016/j.actamat.2022.118019· OSTI ID:1976790

^[1]; Kumagai, Tomohisa ^[2]; ^[3]; El-Azab, Anter ^[3]

Purdue University, West Lafayette, IN (United States); OSTI
Purdue University, West Lafayette, IN (United States); Central Research Institute of Electric Power Industry, Nagasaka (Japan)
Purdue University, West Lafayette, IN (United States)

A statistical method for the analysis of continuously distributed data representative of composition fluctuations in irradiated FeCrAl alloys acquired using Energy Dispersive X-ray Spectroscopy (EDS) method is presented. Using probability distribution functions, direct and cross-covariances between the elemental compositions, the effects of alloy composition and irradiation dose were investigated on the spatial distribution and length scale of composition fluctuations at the nanoscale. We have observed that, for neutron-irradiated FeCrAl alloys, the distribution of Fe and Cr followed a left-skewed and right-skewed distribution, respectively for all (average) alloy compositions and irradiation doses. The analysis also revealed enhanced spatial gradients in the elemental compositions at higher irradiation dose. Direct and cross-covariance estimates of the experimental data were also utilized for reconstruction of composition data through fitting it to a parametric form of the covariance functions. Linear Model of Coregionalization was used to determine the parameters of the covariance functions. Subsequently, a spectral method was utilized for simulating a realization of the alloy compositions. Close correspondence was observed between the experimental and the reconstructed data which was analyzed using probability distribution functions and covariance functions. Composition space of the experimental and reconstructed data and dislocation velocities as a function of applied stress and line directions over the entire composition maps were also examined.

View Accepted Manuscript (DOE)

Research Organization:: Purdue University, West Lafayette, IN (United States)

Sponsoring Organization:: USDOE Office of Nuclear Energy (NE), Nuclear Energy University Program (NEUP)

Grant/Contract Number:: NE0008758

OSTI ID:: 1976790

Alternate ID(s):: OSTI ID: 1870321

Journal Information:: Acta Materialia, Journal Name: Acta Materialia Journal Issue: C Vol. 234; ISSN 1359-6454

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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