Title : ( Supersonic inlet buzz detection using pressure measurement on wind tunnel wall )
Authors: Mohammad Farahani , Abbas Daliri , Javad Sepahi-Younsi ,Access to full-text not allowed by authors
Abstract
Feasibility of an innovative buzz detection technique through measuring the static pressure outside a mixed-compression supersonic inlet is studied. The buzz is an instability phenomenon that occurs almost in all supersonic inlets. During the buzz, shock oscillation along with pressure and mass flow fluctuations affects the performance characteristics of the inlet. The main objective of this paper is to introduce a simple and easy-to-implement method for investigation of the buzz phenomenon in a supersonic inlet. The experimental data for far field-based are compared with those of the model-based one at free stream Mach numbers of 1.8, 2.0, and 2.2 and at zero degrees angle of attack for a mixed-compression inlet. The results show that this technique can measure exact value of buzz frequency as well as its onset. The present method uses pressure data obtained from the wind-tunnel wall instead of measuring the pressure inside or on the model surfaces which in most cases is very hard. However, to sense flow oscillations, caused by the buzz onset the sensors on the wind-tunnel wall must be located downstream of the point where the oblique shock from the spike impinges on the tunnel wall. The location of the measurement point as well as the distance between the sensor and the origin of the shock wave system are very important.
Keywords
Supersonic intake@article{paperid:1072940,
author = {محمد فراهانی and Daliri, Abbas and Sepahi-Younsi, Javad},
title = {Supersonic inlet buzz detection using pressure measurement on wind tunnel wall},
journal = {Aerospace Science and Technology},
year = {2019},
volume = {86},
month = {March},
issn = {1270-9638},
pages = {782--793},
numpages = {11},
keywords = {Supersonic intake},
}
%0 Journal Article
%T Supersonic inlet buzz detection using pressure measurement on wind tunnel wall
%A محمد فراهانی
%A Daliri, Abbas
%A Sepahi-Younsi, Javad
%J Aerospace Science and Technology
%@ 1270-9638
%D 2019