Review

Optimization research on laminated cooling structure for gas turbines: A review

  • Received: 28 October 2024 Revised: 05 March 2025 Accepted: 20 March 2025 Published: 28 March 2025
  • Against the background of increasing gas turbine inlet temperature and decreasing amount of cooling air, laminated cooling structure (LCS) is a highly efficient composite cooling structure with the advantages of lower cooling air consumption and higher cooling efficiency, which is a promising development direction for future wall cooling technology. In this review, we provide an overview of LCS's structural optimization research. The experimental and simulation studies therein were reviewed, and the major influencing parameters in the structure were analyzed in detail. The characteristics of various optimization methods were investigated, and the research methodology and optimization process of multi-objective optimization of laminated cooling structure were summarized. The review shows that laminated cooling structure, as a kind of composite cooling structure, has numerous geometrical and flow factors affecting its cooling efficiency. Multi-objective optimization techniques have effective application prospects in this field. In the future, researchers should focus on enhancing the efficiency and accuracy of multi-objective optimization algorithms. They should also explore the application of machine learning and artificial intelligence in LCS optimization, thereby promoting the intelligence and automation of design optimization.

    Citation: Xiaojing Tian, Weiqi Ye, Liang Xu, Anjian Yang, Langming Huang, Shenglong Jin. Optimization research on laminated cooling structure for gas turbines: A review[J]. AIMS Energy, 2025, 13(2): 354-401. doi: 10.3934/energy.2025014

    Related Papers:

  • Against the background of increasing gas turbine inlet temperature and decreasing amount of cooling air, laminated cooling structure (LCS) is a highly efficient composite cooling structure with the advantages of lower cooling air consumption and higher cooling efficiency, which is a promising development direction for future wall cooling technology. In this review, we provide an overview of LCS's structural optimization research. The experimental and simulation studies therein were reviewed, and the major influencing parameters in the structure were analyzed in detail. The characteristics of various optimization methods were investigated, and the research methodology and optimization process of multi-objective optimization of laminated cooling structure were summarized. The review shows that laminated cooling structure, as a kind of composite cooling structure, has numerous geometrical and flow factors affecting its cooling efficiency. Multi-objective optimization techniques have effective application prospects in this field. In the future, researchers should focus on enhancing the efficiency and accuracy of multi-objective optimization algorithms. They should also explore the application of machine learning and artificial intelligence in LCS optimization, thereby promoting the intelligence and automation of design optimization.



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