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아음속 기저면 압력 예측 개선을 위한 k-w SST 난류 모델상수의 Bayesian Optimization
BAYESIAN OPTIMIZATION OF k-w SST TURBULENCE MODEL CLOSURE COEFFICIENTS FOR IMPROVED PREDICTION OF SUBSONIC BASE PRESSURE
- 박재형;
- 김동욱;
- 이승수
초록
In this study, we present a set of the closure coefficients of the SST turbulence model for improved predictions of base pressure coefficient in subsonic speeds. To this end, Bayesian optimization over the closure coefficients of the turbulence model is performed for the average base pressure coefficient of Merz’s experiment. In addition, flow simulations of SOC and SOCBT projectile have been performed with the optimized turbulence model.
키워드
항력(Drag); RANS; Turbulence model; Base flow; Eddy Viscosity Model; Bayesian optimization
- 제목
- 아음속 기저면 압력 예측 개선을 위한 k-w SST 난류 모델상수의 Bayesian Optimization
- 제목 (타언어)
- BAYESIAN OPTIMIZATION OF k-w SST TURBULENCE MODEL CLOSURE COEFFICIENTS FOR IMPROVED PREDICTION OF SUBSONIC BASE PRESSURE
- 저자
- 박재형; 김동욱; 이승수
- 발행일
- 2022-03
- 유형
- Y
- 저널명
- 한국전산유체공학회지
- 권
- 27
- 호
- 1
- 페이지
- 45 ~ 53