Analysis of Transonic Buffet with Evolutionary Rule-based Learning

Abstract

The transonic buffet is a phenomenon of aerodynamic instability due to the oscillation of a shock wave; its generating mechanism has not been fully solved. This paper introduces an analysis of the transonic buffet with an Evolutionary Rule-based Learning (ERL) approach. ERL can extract generalized knowledge as a set of rules while solving a given machine learning problem. In the presented analysis, ERL is used to extract essential features likely provoking turbulent separated flow. Further, the impulse response analysis is applied to extracted features to investigate how those features affect the temporal propagations of pressures towards the shock-wave oscillation.