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Title: Evaluation of DNB Predictive Capability in Multiphase Boiling Model of STAR-CCM+

Abstract

The current milestone report is to evaluate the predictive capability of the existing boiling model in the commercial Computational Fluid Dynamics (CFD) package (so called, STARCCM+ 11.04.012), and validate the numerical calculation of a boiling curve with identification of departure from nucleate boiling (DNB) point by comparing with experimental measurements in the literatures. The current work directly demonstrates the DNB predictive capability in multiphase boiling model for nuclear reactor applications, which is tightly coupled with the CASL mission goal and evolving need from the nuclear industry. The boiling model tested here is based on the heat flux partitioning RPI approach (so called Generation-I boiling model in STAR-CCM+). A traditional experimental DNB test with a vertical pipe flow performed by Argonne National Laboratory (ANL), and a realistic 5x5-bundle fuel bundle with non-mixing vane DNB test conducted by Westinghouse Electric Company (WEC) are selected as reference experimental measurement. A baseline DNB simulation methodology is reported and its predictive capability is evaluated qualitatively as well as quantitatively with existing experiments. A parametric study of the microscopic boiling closure relations is investigated. For the pipe flow DNB validation study, the calculated DNB from the current study demonstrates good agreement with measured DNB data. Themore » maximum deviation is observed less than 20%. The trend behaviors of DNB in varying operating conditions are similar with the observation reported in the literature. In addition, a meshing strategy for 5x5 bundle case is reported, some challenges on 5x5 bundle DNB model are also discussed. The current study provide a fundamental insight on the usefulness and limitations of the generation-I boiling model approach and may contribute to an advanced boiling model development for a practical nuclear thermal hydraulic application.« less

Authors:
 [1];  [2];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Nuclear Science and Engineering
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE)
OSTI Identifier:
1435546
Report Number(s):
LA-UR-18-23703
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; 42 ENGINEERING; DNB; Multiphase boiling

Citation Formats

Kim, Seung Jun, Baglietto, Emilio, and Demarly, Etienne. Evaluation of DNB Predictive Capability in Multiphase Boiling Model of STAR-CCM+. United States: N. p., 2018. Web. doi:10.2172/1435546.
Kim, Seung Jun, Baglietto, Emilio, & Demarly, Etienne. Evaluation of DNB Predictive Capability in Multiphase Boiling Model of STAR-CCM+. United States. doi:10.2172/1435546.
Kim, Seung Jun, Baglietto, Emilio, and Demarly, Etienne. Mon . "Evaluation of DNB Predictive Capability in Multiphase Boiling Model of STAR-CCM+". United States. doi:10.2172/1435546. https://www.osti.gov/servlets/purl/1435546.
@article{osti_1435546,
title = {Evaluation of DNB Predictive Capability in Multiphase Boiling Model of STAR-CCM+},
author = {Kim, Seung Jun and Baglietto, Emilio and Demarly, Etienne},
abstractNote = {The current milestone report is to evaluate the predictive capability of the existing boiling model in the commercial Computational Fluid Dynamics (CFD) package (so called, STARCCM+ 11.04.012), and validate the numerical calculation of a boiling curve with identification of departure from nucleate boiling (DNB) point by comparing with experimental measurements in the literatures. The current work directly demonstrates the DNB predictive capability in multiphase boiling model for nuclear reactor applications, which is tightly coupled with the CASL mission goal and evolving need from the nuclear industry. The boiling model tested here is based on the heat flux partitioning RPI approach (so called Generation-I boiling model in STAR-CCM+). A traditional experimental DNB test with a vertical pipe flow performed by Argonne National Laboratory (ANL), and a realistic 5x5-bundle fuel bundle with non-mixing vane DNB test conducted by Westinghouse Electric Company (WEC) are selected as reference experimental measurement. A baseline DNB simulation methodology is reported and its predictive capability is evaluated qualitatively as well as quantitatively with existing experiments. A parametric study of the microscopic boiling closure relations is investigated. For the pipe flow DNB validation study, the calculated DNB from the current study demonstrates good agreement with measured DNB data. The maximum deviation is observed less than 20%. The trend behaviors of DNB in varying operating conditions are similar with the observation reported in the literature. In addition, a meshing strategy for 5x5 bundle case is reported, some challenges on 5x5 bundle DNB model are also discussed. The current study provide a fundamental insight on the usefulness and limitations of the generation-I boiling model approach and may contribute to an advanced boiling model development for a practical nuclear thermal hydraulic application.},
doi = {10.2172/1435546},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Apr 30 00:00:00 EDT 2018},
month = {Mon Apr 30 00:00:00 EDT 2018}
}

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