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This content will become publicly available on October 26, 2018

Title: Automated X-Ray Diffraction of Irradiated Materials

Synchrotron-based X-ray diffraction (XRD) and small-angle Xray scattering (SAXS) characterization techniques used on unirradiated and irradiated reactor pressure vessel steels yield large amounts of data. Machine learning techniques, including PCA, offer a novel method of analyzing and visualizing these large data sets in order to determine the effects of chemistry and irradiation conditions on the formation of radiation induced precipitates. In order to run analysis on these data sets, preprocessing must be carried out to convert the data to a usable format and mask the 2-D detector images to account for experimental variations. Once the data has been preprocessed, it can be organized and visualized using principal component analysis (PCA), multi-dimensional scaling, and k-means clustering. In conclusion, from these techniques, it is shown that sample chemistry has a notable effect on the formation of the radiation induced precipitates in reactor pressure vessel steels.
Authors:
 [1] ;  [2] ;  [3] ;  [3] ;  [2]
  1. Syracuse Univ., NY (United States). College of Engineering and Computer Science
  2. Brookhaven National Lab. (BNL), Upton, NY (United States). Computational Science Initiative
  3. Brookhaven National Lab. (BNL), Upton, NY (United States). Nuclear Science and Technology Department
Publication Date:
Report Number(s):
BNL-203331-2018-JAAM
Grant/Contract Number:
SC0012704
Type:
Accepted Manuscript
Journal Name:
Scientific Data Summit (NYSDS), 2017 New York
Additional Journal Information:
Journal Name: Scientific Data Summit (NYSDS), 2017 New York; Conference: Scientific Data Summit (NYSDS), 2017 New York , New York, NY, USA, 6/6/2017 - 6/9/2017
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Nuclear Physics (NP) (SC-26); USDOE Office of Nuclear Energy (NE); USDOE Office of Science (SC), Workforce Development for Teachers and Scientists (WDTS) (SC-27)
Country of Publication:
United States
Language:
English
Subject:
73 NUCLEAR PHYSICS AND RADIATION PHYSICS; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
OSTI Identifier:
1426469