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清华大学学报(自然科学版)  2023, Vol. 63 Issue (4): 633-641    DOI: 10.16511/j.cnki.qhdxxb.2023.25.030
  论文 本期目录 | 过刊浏览 | 高级检索 |
燃烧室流动混合过程的代理模型
耿俊杰1, 王兴建1, 李嘉璐2, 费腾1, 祁海鹰1
1. 清华大学 能源与动力工程系, 北京 100084;
2. 山东科技大学 土木工程与建筑学院, 青岛 266590
Surrogate model of combustor flow mixing process
GENG Junjie1, WANG Xingjian1, LI Jialu2, FEI Teng1, QI Haiying1
1. Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China;
2. College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China
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摘要 为了构建适用于燃烧室冷态流动混合过程的代理模型(surrogate model,SM)的方法,该文研究了构建过程中的关键步骤,通过使用Latin超立方抽样(Latin hypercube sampling,LHS)方法进行样本选取,在完成数值模拟后使用本征正交分解提取样本间的主要特征进行降维,再通过Kriging插值法完成工况插值。结果表明:该构建方法能够处理冷态高速、高湍流度、强旋流动和燃料/空气掺混,精度高于国际平均水平。同时,该文提出了构建方法的应用准则,为后续更复杂、包含燃烧反应过程以及结构变化的燃烧室SM构建奠定基础。
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耿俊杰
王兴建
李嘉璐
费腾
祁海鹰
关键词 燃烧室代理模型Latin超立方抽样本征正交分解Kriging插值    
Abstract:[Objective] Numerical simulation of a gas turbine combustor is an important step in its design process. Due to the complexity of the physical and chemical processes, the calculation cost is high. The calculation cost can be reduced by constructing surrogate model of combustor. This paper focuses on the key steps in the construction of a surrogate model suitable for cold gas flow and the mixing process of combustor. Furthermore, this paper proposes a surrogate model for the central nozzle and the subsequent combustor space of a heavy-duty gas turbine. [Methods] The construction of the surrogate model includes several key steps: design of experiments (DOE), numerical simulation, dimensionality reduction, and an interpolation process. Two parameters are selected as the input parameters for the surrogate model: The fuel mass flow rate Gf and the combustor inlet air pressure p2. Latin hypercube sampling is used in the DOE to determine 12 operating conditions for computational fluid dynamics (CFD) simulations, and the results are used to build the surrogate model. Proper orthogonal decomposition is used for dimensionality reduction, wherein a set of basis functions and corresponding coefficients are extracted. The basis functions reflects the main characteristics of the combustor flow field. Moreover, the data dimensionality is reduced from the number of grid nodes of the combustor to the number of basis functions, which do not exceed the number of operating conditions. The Kriging model is used to interpolate the coefficients of the basis function with the input parameters of the surrogate model. Four verification conditions are set up to determine the accuracy of the surrogate model through a comparison of the surrogate model results with the CFD simulation results. The outlet cross section of the central nozzle and the longitudinal section of the combustor are selected to compare multiple key parameter distributions, including axial velocity, radial velocity, tangential velocity, CH4 concentration, turbulent kinetic energy, and pressure. The vector operations are used to compare the distributions of various parameters, which can simultaneously reflect the differences in the numerical and spatial distributions of various parameters. [Results] The results showed that the error in most parameters was ~1%. The results also revealed that the construction method of the surrogate model could be applied to cold high-speed and high-turbulence strong rotational flow and fuel/air mixing. The accuracy was higher than the international average level, and the application criteria of the construction method were proposed. The influences of interpolation methods, sample numbers, and basis function numbers on the accuracy of the surrogate model were analyzed. The accuracy of SM was higher than extrapolation. Increasing the number of sample operations and basis functions could improve the accuracy of the surrogate model, but also increased the computational cost. [Conclusions] The SM construction method (POD & Kriging) is suitable for the cold gas flow and mixing process in the combustor. The paper lays the foundation for subsequent research on the construction method of combustor SM, which includes combustion reactions and geometric structure changes.
Key wordssurrogate model of combustor    Latin hypercube sampling    proper orthogonal decomposition    Kriging interpolation
收稿日期: 2023-02-20      出版日期: 2023-04-22
基金资助:国家科技重大专项(Y2019-I-0022-0021)
通讯作者: 祁海鹰,教授,E-mail:hyqi@tsinghua.edu.cn     E-mail: hyqi@tsinghua.edu.cn
作者简介: 耿俊杰(1998-),男,博士研究生。
引用本文:   
耿俊杰, 王兴建, 李嘉璐, 费腾, 祁海鹰. 燃烧室流动混合过程的代理模型[J]. 清华大学学报(自然科学版), 2023, 63(4): 633-641.
GENG Junjie, WANG Xingjian, LI Jialu, FEI Teng, QI Haiying. Surrogate model of combustor flow mixing process. Journal of Tsinghua University(Science and Technology), 2023, 63(4): 633-641.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2023.25.030  或          http://jst.tsinghuajournals.com/CN/Y2023/V63/I4/633
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
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