Generative artificial intelligence (AI) technology has driven research progress in complex engineering fields through its applications in industries such as energy and electronics. In the field of aero-engines, the application of generative AI mainly focuses on the scheme design and simulation analysis, significantly improving the efficiency of both design and simulation. By integrating prior design model libraries, intelligent fusion generation algorithms, and AI-based rapid prediction of physical performance, generative design has been achieved to output design solutions that meet predetermined performance indicators, providing a new research paradigm for the design of aero-engines. The practical applications of generative AI technology in the design and simulation of aero-engines were elaborated. The challenges faced in applying generative AI technology to aero-engines development were discussed, including model generalization, small-sample learning, and modal imbalance, along with corresponding solutions and methods. Furthermore, potential future trends in generative AI technology were explored. The ideas and methods were proposed to support the intelligent transformation of aero-engines design.
SHANG et al. (Sun,) studied this question.