为缩短燃气轮机低压压气机的设计周期，获取一维设计中各关键设计参数分布规律，同时得到最优的一维设计参数选取方案，采用基于HARIKA算法的压气机一维设计与分析程序对某型船用低压压气机流量系数、载荷系数和反动度的轴向布局方法进行了研究并提炼了各参数分布的数学模型。其中，流量系数和载荷系数沿级分布为近似单峰值的三次多项式曲线，反动度分布为“二段式”，通过改变流量系数和载荷系数的峰值点坐标和改变特定级反动度和反动度变化步长的方法，研究了不同布局方式对效率、喘振裕度以及压比的影响，最后结合优化算法得到了最优参数分布方案。结果发现：流量系数峰值位置在第6级，载荷系数在第5级或第6级时效率和喘振裕度性能较好；第四级反动度取值0.5~0.52时效率较高；相比载荷系数和反动度，流量系数对非设计工况性能影响更为显著，优化后的参数分布方案在各转速下喘振裕度均有所提高。

In order to shorten the design cycle of gas turbine low pressure compressor, obtain the distribution rule of key design parameters in onedimensional design, and achieve the optimal onedimensional design parameter selection scheme, the axial layout method for the flow coefficient, load coefficient and reaction degree of a certain marine low pressure compressor is studied and the mathematical model of each parameter distribution is refined by use of the compressor onedimensional design and analytical procedure based on HARIKA algorithm. Among them, the flow coefficient and load coefficient are approximately cubic polynomial curves with single peak along the level distribution, and the reaction degree distribution is twostage partition function. By changing the peak point coordinates of flow coefficient and load coefficient, and changing the reaction degree and reaction degree variable step of specific level, the effects of different layout modes on the efficiency, surge margin and pressure ratio are studied. Finally, the optimal parameter distribution scheme is obtained by combining the optimization algorithm. The results show that the peak position of the flow coefficient is at the sixth level, and the efficiency and surge margin are better when the load coefficient is at the fifth or sixth level, and the efficiency is higher when the reaction degree of the fourth stage is 0.5 to 0.52. Compared with the load coefficient and reaction degree, the flow coefficient has a more significant impact on the performance of offdesign conditions, and the optimized parameter distribution scheme has improved the surge margin at each rotational speed.

TK474.8

国家自然科学基金区域创新发展联合基金（U20A20298）；国家科技重大专项（2017-II-0006-0019，2017-I-0009-0010）