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E-Mail: liy59@sjtu.edu.cn
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深度学习方法在涡轮冷却中的应用综述.工程热物理学报.2022
Fast prediction and sensitivity analysis of gas turbine cooling performance using supervised learning approaches.ENERGY.2022
Enhanced thermal performance of a pin-fin cooling channel for gas turbine blade by density-based topology optimization.INTERNATIONAL JOURNAL OF THERMAL SCIENCES.2022
An Iterative Neural Operator to Predict the Thermo-Fluid Information in Internal Cooling Channels.Journal of Turbomachinery-Transactions of the Asme.2022
A machine learning approach to quantify the film cooling superposition effect for effusion cooling structures.INTERNATIONAL JOURNAL OF THERMAL SCIENCES.2021
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人工智能+教育专项基金,自然科学-2023-12-01
涡轮叶片冷却结构的自组织拓扑调控及流动传热机理研究-2027-12-01
基于数值仿真和数据分析的多场耦合作用下失控井周温度场机理研究委托技术开发合同-2023-09-01
基于可编程自组织几何体的高效散热机制研究-2025-03-01
先进冷却技术与燃气轮机性能中德合作研究小组-2023-09-01
