Applied research on simulation data of blade optimization designing based on data mining
Dan Wang · Computer Engineering and Applications Journal · 2013
A large amount of implicit discipline knowledge is embedded in the aerodynamic optimization simulation data. In order to acquire this knowledge, the data mining method of decision tree algorithm based on rough set is applied to extracting from the aerodynamic simulation data of the transonic rotor. Taking NASA Rotor37 as an example, using the improved K-Means algorithm for discretization of continuous attributes, the discretization attribute is reduced by using rough set theory. The decision tree is established by taking bending, circumferential stacking line control point offset as condition attributes, and the total pressure loss coefficient as decision attribute. The designing rule of the transonic rotor blade optimization designing is acquired. The results show that the method of knowledge extraction is feasible in the field of compressor optimization design.