Recent interest in commercial supersonic flight has highlighted the need to accurately predict Effective Perceived Noise Levels (EPNL) for aircraft and, since the dominant noise source at takeoff will likely be jet noise, specifically jet noise contributions. The current study compares predictions from historical jet-noise models within NASA’s Aircraft Noise Prediction Program and scale-model data to measurements made in a Learjet 25 flight test. The noise levels from the predictions and scale-model data were below those for the flight data by 2.5 – 3.5, 1 – 2, and 3 – 5 EPNdB for the SAE model, the Stone Jet model, and the scale-model data, respectively. Tones and broadband haystacks were identified in the flight spectra that are not associated with jet noise which increased the flight EPNL by at least 0.5 EPNdB over that computed from spectra with the tones and haystacks removed. The study highlights the need for accurate exhaust temperature measurements, aircraft flight position information, and averaging data across a line of microphones in flight tests. For example, a 100° F to 200° F difference in jet exhaust temperature is enough to explain the differences between flight, model scale, and prediction comparisons.
Jet Noise Prediction Comparisons with Scale Model Tests and Learjet Flyover Data
2020
21 pages
Report
Keine Angabe
Englisch
Acoustics , Aeroacoustics , Aerodynamic noise , Shock waves , Subsonic speed , Supersonic jet flow , Test stands , Turbojet engines , Wind tunnels , Contamination , Effective perceived noise levels , Jet aircraft noise , Mathematical models , Noise generators , Noise prediction , Noise reduction , Scale models
JET NOISE PREDICTION COMPARISONS WITH SCALE MODEL TESTS AND LEARJET FLYOVER DATA
British Library Conference Proceedings | 2019
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