Petro-chemical Equipment Technology ›› 2026, Vol. 47 ›› Issue (4): 13-18,56.doi: 10.3969/j.issn.1006-8805.2026.04.003

• STATIC EQUIPMENT • Previous Articles     Next Articles

Design Optimization of CW-Type Plain Surface Heat Transfer Channel Based on Cross-Validation Gaussian Surrogate Model

Wang Haibo1, Ma Yiming1, Sun Haisheng1, Ma Jinwei1, Zhan Yong2, Song Hao2, Guo Kaigang2, Wei Liping2,3   

  1. 1. Shanghai Lanbin Petrochemical Equipment Co., Ltd., Shanghai, 201500;
    2. School of Chemical Engineering, Northwest University, Xi'an, Shaanxi, 710069;
    3. Ministry of Education Engineering Research Center for Shaanbei Energy Advanced Chemical Utilization Technology, Northwest University, Xi'an, Shaanxi, 710069
  • Received:2025-02-27 Revised:2026-04-26 Accepted:2026-06-28 Online:2026-07-17 Published:2026-07-17
  • Contact: Wei Liping E-mail:wanghaibo@lanpec.com

Abstract: Cross-wavy channel (CW-type) flow geometry optimization in plain surface heat exchangers plays a critical role in enhancing heat transfer performance while reducing flow resistance. However, traditional design methods struggle to comprehensively account for the integrated effects of high-dimensional structural and operational parameters; therefore, there is an urgent need to develop a novel optimization methodology. A comprehensive database was constructed, integrating the influences of structural and operational parameters, and a high-precision, cross-validation Gaussian surrogate model was developed to enable optimization design via a multi-objective optimization genetic algorithm. The method can effectively identify channel geometries and operational parameters featuring high heat transfer coefficients and low friction coefficients, providing a critical theoretical basis for the design and operation of CW-type plain surface heat exchangers.

Key words: Gaussian process regression (GPR), genetic algorithm, bi-objective optimization, plain surface heat exchanger, database