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Title: Ambient and building condition effects modeling of air-cooled natural circulation systems

Abstract

Throughout the testing program at Natural convection Shutdown heat removal Test Facility (NSTF), strong influences of ambient conditions were observed in the experimental data when baseline tests were repeated under identical test procedures. Significant analysis efforts were conducted to gain understanding of these influences, and quantify the system response of the test facility. In this paper, an empirical model was developed based on theoretical considerations and using experimental data to correlate zero-power system flow rates with ambient meteorological conditions, including wind and temperatures. Coefficients in the model were determined based on best fitting of the experimental data set. The predictive capability of the empirical model was demonstrated by applying it to new sets of experimental data. Finally, after implementing the empirical model in both system-level thermal fluids and computational fluid dynamics modeling of the facility, simulations from both approaches resulted in accurate predictions in system natural circulation flow rates.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE), Nuclear Reactor Technologies (NE-7)
OSTI Identifier:
1461320
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Applied Thermal Engineering
Additional Journal Information:
Journal Volume: 137; Journal ID: ISSN 1359-4311
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; ambient condition effects; natural circulation; decay heat removal

Citation Formats

Hu, Rui, Lisowski, Darius D., Bucknor, Matthew D., Kraus, Adam R., and Lv, Qiuping. Ambient and building condition effects modeling of air-cooled natural circulation systems. United States: N. p., 2018. Web. doi:10.1016/j.applthermaleng.2018.03.046.
Hu, Rui, Lisowski, Darius D., Bucknor, Matthew D., Kraus, Adam R., & Lv, Qiuping. Ambient and building condition effects modeling of air-cooled natural circulation systems. United States. doi:10.1016/j.applthermaleng.2018.03.046.
Hu, Rui, Lisowski, Darius D., Bucknor, Matthew D., Kraus, Adam R., and Lv, Qiuping. Tue . "Ambient and building condition effects modeling of air-cooled natural circulation systems". United States. doi:10.1016/j.applthermaleng.2018.03.046. https://www.osti.gov/servlets/purl/1461320.
@article{osti_1461320,
title = {Ambient and building condition effects modeling of air-cooled natural circulation systems},
author = {Hu, Rui and Lisowski, Darius D. and Bucknor, Matthew D. and Kraus, Adam R. and Lv, Qiuping},
abstractNote = {Throughout the testing program at Natural convection Shutdown heat removal Test Facility (NSTF), strong influences of ambient conditions were observed in the experimental data when baseline tests were repeated under identical test procedures. Significant analysis efforts were conducted to gain understanding of these influences, and quantify the system response of the test facility. In this paper, an empirical model was developed based on theoretical considerations and using experimental data to correlate zero-power system flow rates with ambient meteorological conditions, including wind and temperatures. Coefficients in the model were determined based on best fitting of the experimental data set. The predictive capability of the empirical model was demonstrated by applying it to new sets of experimental data. Finally, after implementing the empirical model in both system-level thermal fluids and computational fluid dynamics modeling of the facility, simulations from both approaches resulted in accurate predictions in system natural circulation flow rates.},
doi = {10.1016/j.applthermaleng.2018.03.046},
journal = {Applied Thermal Engineering},
issn = {1359-4311},
number = ,
volume = 137,
place = {United States},
year = {2018},
month = {3}
}

Journal Article:
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