Application of variable turbulent Prandtl number model in numerical simulation of supercritical water heat transfer in vertical upward tubes

ZHOU Xihong; ZHU Chao; WU Pengju; DONG Le; YANG Dong

doi:10.19666/j.rlfd.201909216

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Application of variable turbulent Prandtl number model in numerical simulation of supercritical water heat transfer in vertical upward tubes

Thermal Power Generation Vol. 49, Issue 7, Pages: 98-105(2020)

更新时间：2025-09-28

- Application of variable turbulent Prandtl number model in numerical simulation of supercritical water heat transfer in vertical upward tubes
- 作者机构：
  
  1. 国网陕西省电力公司电力科学研究院
  2. 西安交通大学动力工程多相流国家重点实验室
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.201909216
  CLC： TK124
- Published Online：27 June 2020，
  
  Published：2020
- 稿件说明：
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ZHOU Xihong, ZHU Chao, WU Pengju, et al. Application of variable turbulent Prandtl number model in numerical simulation of supercritical water heat transfer in vertical upward tubes[J]. Thermal Power Generation, 2020, 49(7): 98-105.
DOI：

ZHOU Xihong, ZHU Chao, WU Pengju, et al. Application of variable turbulent Prandtl number model in numerical simulation of supercritical water heat transfer in vertical upward tubes[J]. Thermal Power Generation, 2020, 49(7): 98-105. DOI： 10.19666/j.rlfd.201909216.

摘要

为了准确地预测超临界压力水的传热恶化(HTD)

本文分析了湍流Prandtl数(Pr_t)对超临界压力水传热的影响。在理论研究的基础上

提出了一种与物理性质相关的可变Pr_t模型。利用所提出的Pr_t模型以及其他2个先前的Pr_t模型和2个常数Pr_t模型对垂直上升加热管内超临界水传热进行了数值模拟

通过与文献中的2组传热恶化工况下的实验数据进行对比评估

发现本文所提出模型能更准确地预测壁温。

Abstract

In order to accurately predict the heat transfer deterioration(HTD) of supercritical pressure water

the influence of turbulent Prandtl number(Pr_t) on the heat transfer of supercritical pressure water was analyzed. Based on theoretical research

a variable Pr_t model related to physical properties was proposed. The proposed Pr_t model and two other previous Pr_t models as well as two constant Pr_t models were used to numerically simulate the heat transfer of supercritical water in the vertical upward heating tube. The data are compared and evaluated

and it is found that the model proposed in this paper can predict the wall temperature more accurately.

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Related Author

QING Hao

ZHOU Yanjun

SONG Yuanyuan

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HUANG Zhong

LYU Junfu

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GUO Feng

Related Institution

Key Laboratory of Thermal Science and Power Engineering, Department of Energy and Power Engineering, Tsinghua University, Ministry of Education

National Nuclear Power Planning and Design Institute Co., Ltd

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Nanjing University of Technology

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