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Title: Validation and uncertainty quantification of multiphase-CFD solvers: A data-driven Bayesian framework supported by high-resolution experiments

Authors:
ORCiD logo; ORCiD logo;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1557879
Grant/Contract Number:  
NE0008530
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Nuclear Engineering and Design
Additional Journal Information:
Journal Name: Nuclear Engineering and Design Journal Volume: 354 Journal Issue: C; Journal ID: ISSN 0029-5493
Publisher:
Elsevier
Country of Publication:
Netherlands
Language:
English

Citation Formats

Liu, Yang, Sun, Xiaodong, and Dinh, Nam T. Validation and uncertainty quantification of multiphase-CFD solvers: A data-driven Bayesian framework supported by high-resolution experiments. Netherlands: N. p., 2019. Web. doi:10.1016/j.nucengdes.2019.110200.
Liu, Yang, Sun, Xiaodong, & Dinh, Nam T. Validation and uncertainty quantification of multiphase-CFD solvers: A data-driven Bayesian framework supported by high-resolution experiments. Netherlands. doi:10.1016/j.nucengdes.2019.110200.
Liu, Yang, Sun, Xiaodong, and Dinh, Nam T. Sun . "Validation and uncertainty quantification of multiphase-CFD solvers: A data-driven Bayesian framework supported by high-resolution experiments". Netherlands. doi:10.1016/j.nucengdes.2019.110200.
@article{osti_1557879,
title = {Validation and uncertainty quantification of multiphase-CFD solvers: A data-driven Bayesian framework supported by high-resolution experiments},
author = {Liu, Yang and Sun, Xiaodong and Dinh, Nam T.},
abstractNote = {},
doi = {10.1016/j.nucengdes.2019.110200},
journal = {Nuclear Engineering and Design},
number = C,
volume = 354,
place = {Netherlands},
year = {2019},
month = {12}
}

Journal Article:
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This content will become publicly available on August 19, 2020
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