湍流普朗特数识别的随机抽样算法

长江科学院院报 ›› 2011, Vol. 28 ›› Issue (6): 16-19.

湍流普朗特数识别的随机抽样算法

朱嵩¹ ，刘国华² ，程伟平² ，黄跃飞³

1. 广东省电力设计研究院水务部，广州 510663 ； 2. 浙江大学建筑工程学院，杭州 310058 ； 3. 清华大学水沙科学与水利水电工程国家重点实验室，北京 100084

出版日期:2011-06-01 发布日期:2012-11-08

A Random Sampling Algorithm for Identification of Turbulent Prandtl Number

ZHU Song¹ ， LIU Guo-hua² ， CHENG Wei-ping² ， HUANG Yue-fei³

1.Water Engineering Department, Guangdong Electric Power Design Institute, Guangzhou 510663, China ； 2.College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China ； 3.State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China

Online:2011-06-01 Published:2012-11-08

摘要/Abstract

摘要： 在温排水等涉及热交换的环境水力学研究中，湍流普朗特（Prandtl, 简称 Pr）数是控制温度的主要参数。对于一个特定的问题，传统湍流 Pr数的确定方法主要采用经验法或试错法，因而具有一定盲目性和低效性。为了提高湍流Pr数确定的可靠性，采用马尔科夫链蒙特卡罗（Markov Chain Monte Carlo, 简称 MCMC）随机抽样的方法（Metropolis-Hastings 算法）来对湍流Pr数进行识别，其中湍流场计算采用了稳态标准 k-ε模型，温度场计算采用非稳态热传导方程。算例计算结果表明，MCMC方法对湍流Pr数的识别具有良好的适用性和较高的识别精度。

关键词: 湍流Prandtl数 , 参数识别 , 湍流传热 , Metropolis-Hastings 算法 , MCMC随机抽样

Abstract: Turbulent Prandtl number (Pr) is a key parameter for controlling the temperature distribution in the research of thermal discharge water and other environmental hydraulics involving heat transfer. For a given problem, turbulent  Pr  number generally comes from previous experiences or trial-and-error method, which is blindfold and inefficient. To increase the reliability of turbulent  Pr  number for a given problem, Metropolis-Hastings algorithm, a Markov Chain Monte Carlo (MCMC) random sampling method was employed in this paper to identify turbulent Pr number. In the numerical simulation, steady standard k- ε model was used for turbulence flow field computation, while unsteady heat transfer equation was adopted for computing the temperature field. The computation results manifested that MCMC method is suitable and can offer precise results for the identification of turbulent Pr number.

Key words: turbulent Prandtl number , parameter identification , turbulent heat transfer , Metropolis-Hastings algorithm , MCMC random sampling

中图分类号:

O242.28 ， O357.53

朱嵩，刘国华，程伟平，黄跃飞. 湍流普朗特数识别的随机抽样算法[J]. 长江科学院院报, 2011, 28(6): 16-19.

ZHU Song ， LIU Guo-hua ， CHENG Wei-ping ， HUANG Yue-fei. A Random Sampling Algorithm for Identification of Turbulent Prandtl Number [J]. JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI, 2011, 28(6): 16-19.