초록
본 연구에서는 실험데이터와 유전자 알고리즘으로 압축기 성능선도를 생성하는 방법을 제안하였다. 다수의 실험을 통해 엔진의 성능 데이터를 획득하고 회전수에 따른 유량함수, 압력비, 효율의 함수관계를 3차 방정식으로 유도한 후 유전자 알고리즘을 이용하여 미계수를 구하여 압축기 성능선도를 생성하였다. 새롭게 생성한 압축기 성능선도를 이용하여 상용 성능해석 프로그램인 GASTURB로 정상상태 성능해석을 수행하여 검증데이터와 비교하였다.
In this study, a component map generation method using experimental data and the genetic algorithms are newly proposed. In order to generate the performance map for components of this engine, after obtaining engine performance data through many experimental tests, and then the third order equations which have relationships the mass flow function the pressure ratio and the isentropic efficiency as to the engine rotational speed were derived by using the genetic algorithms. A steady-state performance analysis was performed with the generated maps of the compressor by the commercial gas turbine performance analysis program GASTURB. In comparison, it was found that the component maps can be generated from the experimental test data by using the genetic algorithms, and it was confirmed that the analysis results using the generated maps were very similar to those using the scaled maps from the GASTURB.