Empirical method for the prediction of business executive jet cabin noise levels

AppliedACOltSli(~14 11981) 33 42

EMPIRICAL METHOD BUSINESS EXECUTIVE

FOR THE PREDICTION OF JET CABIN NOISE LEVELS

N. M. MOSESand TANYAROXNER

Acoustics Department, Israel Aircraft Industries Ltd, Ben-Gurion Airport (Israel) (Received: 3 April, 1980)

SUMMARY

As a result of flight noise measurements made at various locations in the cabin of the standard lined/no interior Westwind model 1124 business executive jet, it was possible to develop an empirical method for predicting the overall sound pressure level (OASPL) at any required location in the cabin. The cabin overall sound level in decibels (linear) may be found from homographs related to aircraft altitude, roach number or velocity. The noise spectrum at any location may be found from a reference spectrum shape corrected for local parameters. The accuracy of the prediction method, verified by additional tests, was found to be +_1 dB.

INTRODUCTION

Noise reduction inside the cabin of a business jet is one of the most important requirements for public acceptance of the aircraft. For the purposes of proper acoustic treatment, providing good passenger comfort, it is desirable to obtain full information on the noise characteristics of the aircraft being investigated. Generally, however, the number of experiments carried out for different flight conditions has to be limited because of the high cost. Often, a few results of noise level measurements at different altitudes and flight speeds are obtained which do not give an opportunity to determine the influence of altitude and/or flight mach changes on the overall SPL or on the spectrum shape. A useful approach in this situation ofinsuflicient experimental data is to try to find some correlation between the experimental conditions and measured values of noise. In the case of a strong correlation it is possible to predict values of a particular parameter of interest for experimental conditions varied over a wide range. This work presents a simple empirical method of predicting the OASPL values and spectrum shapes based on the correlation of OASPL and one-third octave band SPL values with the conditions of the test flight. 33 Applied Acoustics 0003-682X/81/0014-0033/$02.50 © Applied Science Publishers Ltd, England, 1981 Printed in Great Britain

34

N. M. MOSES, TANYA ROXNER EXPERIMENTAL CONDITIONS AND DATA RECEIVED

The noise measurements of Experiments 1 and 2 were made along the inside of a bare cabin of a WW-1124 executive jet at the locations shown in Figs 1 and 2. The test flight conditions are presented in the Figures. The results show a dependence of the O A S P L upon the location of point of measurement similar to a slowly fading sinusoidal oscillation. OASPL L+ 20

1

II

I

I

I

"1 [

l

l

l

16

21

26

I I

Fig. 1,

OASP dB' L +20

I

I

[

l

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- ~ - I

-1

1 - 0.76 mech, 20 K ft K = 10 - - 2 - 0 . 8 0 ~- 0 7 6 moch, 3 6 + 3 4 K ft 3 - 0 . 7 8 mach, 37 Kfl

-

4-0.75 mech, 3Z2 K ft

27

28

29..

O A S P L distribution along the axis of the cabin (Experiment 1).

,.----- < L 2 .~---------~ ---.._

"

L+IG

1- 0 7 0 roach, 14Kft 2 - 0 . 7 2 rnech,20 Kfl :5-081 melch, 3 5 K f t

I

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~ K=I~) 3

-

4-074moch,29Kft

/ - - - - - Q - -

Fig. 2.

I-----

-----o

O A S P L distribution along the axis of the cabin (Experiment 2).

EMPIRICAL METHOD FOR PREDICTION OF JET CABIN NOISE LEVELS

t6 ¢

--'

21 •

26 "e

27 ¢

35

28 t--.--

local O.8

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~

o.~1 /

.-///

,"

/ /

F

<~~

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_.___

/ Q6

1

9

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21

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27

28

point number

Fig. 3. Distribution of local mach along the axis of the cabin. Figure 3 shows local mach as a function of point location along the centre line of the aircraft cabin. Comparing Figs t, 2 and 3, one sees that there is a similarity between the distribution of the O A S P L and local mach along the aircraft's centre line. However, attempts to find a statistical correlation between local mach and O A S P L were limited. The probable reason is that the local mach is a secondary variable obtained from calculations based upon wind tunnel tests and not a primary parameter of the test in question. Hence, an attempt was made to develop a prediction procedure for the noise level based upon the primary parameters of the test (altitude, H, and flight mach, M~). It was found that the best correlation with the O A S P L was obtained with the derived parameter of H ( ! - M~o ). The absolute value of the correlation coefficient for the points of interest (points 1, 8, 16, 21, 26

36

N. M. MOSES, TANYA ROXNER

and 27) was greater than 97 per cent and for point 28 was 91 per cent. On the basis of OASPL values measured in Experiment 1, it was possible to predict OASPL values measured in the conditions of Experiment 2 with an accuracy of + 1 dB. Further, it was possible to predict spectrum levels and spectrum shape with an accuracy of + 1"5 dB except at those frequencies at which the engine noise is a main contributing factor.

PREDICTION RESULTS AND ANALYSIS

Figures 4, 5, 6 and 7 present, in the form of nomographs, the results of the development of the prediction procedure for the OASPL. The entries of a nomograph are altitude, H, flight mach, M~, and flight speed, V~(in knots). It may be seen that for the same mach number, 0.9, and altitude, 44. l 0 3 It, the levels of corresponding isophonic curves for different points of measurement are: L~ dB for point 1, L~ - 5.5 dB for point 8, L~ + 5 dB for point 16 and L~ + 2 dB for point 27. These predicted values are in accordance with the experimental curves shown in Figs 1 and 2.

"t' 44.103

OASPLdlfference for two adjacent curves is ldB L 1- reference OASPL L L+I dB

~

80knots

2OO

220

240

>60

r//./f/ /,'l ~1/t 14>111 i

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Fig. 4.

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[ 0.9

M~ roach

Nomograph of OASPL values for point 1.

EMPIRICAL METHOD FOR PREDICTION OF JET CABIN NOISE LEVELS

OASPL difference for two adjacent curves is 1 dB L 1- reference OASPL L L+I dB ~LI-5.5 ~ H ~ ft

Vc = 18Oknots

200

2

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~400

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24 16 0.6

0.7

Fig. 5.

36

i

~32 0l

2s

0.9

MQ0 mach

Nomograph of OASPL values for point 8.

OASPL difference for two adjacent curves is ldB L1- reference OASPL L+I dB Vc = l ~ l ~ p o t s

H ft

40

0.8

260

/,'X tl T l/'~,r/ I, '~ f-j'l l j fZl i l.~11 / ~ Z / I Z ~ / , / I f '//¢ Z /.< ~ /, ,'/ /.;, f / /

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, i 280

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i

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360 400

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// 1" 0.6

0.7

Fig. 6.

0.8

0.9

Mm roach

Nomograph of OASPL values for point 16.

37

38

N. M. MOSES, TANYA ROXNER OASPL difference for t w o adjacent curves is 1 dB k L÷I dB L I - reference OASPL

Vc = 180 knots

200

220

/

260

J 44.1( .~Z'/.// T / / L ' f l l i~'4"rl / 280 I/'/,//,~¢~ /'}%y/ h 'Z/4 7 /l/
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".d./ 0.7

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Fig. 7.

0.8

0.9 M ~ mach

Nomograph of OASPL values for point 27.

It is possible to predict noise levels knowing any two of the three parameters, H, Moo and V<, from the isophonic curves of the nomographs. The isophonic curves, being hyperbolic, are initially (up to a certain altitude and related M~) nearly parallel with the lines of constant Vc. At larger values of H and M~---V~ remaining constant--a small increase in altitude causes a significant increase in the noise level. At lower constant altitudes, change of mach number by 0.1 (between 0.6 and 0.7 mach) gives an increase of the OASPL of approximately 3 dB whereas, at higher constant altitudes, the same change in mach number gives an increase of the OASPL of about 9 dB. Note that the nomographs present OASPL values for H varying from 14.103 ft up to 44.103 ft. It is intended to extend the prediction method for the low altitude range where the method needs verification. Figures 8, 9 and 10 present the results of the development of a similar prediction procedure for one-third octave band spectrum curves. The Figures show predicted spectrum shapes for measurement points 1, 16 and 28, respectively. The prediction was performed separately for each frequency band. The nomographs in Figs 8, 9 and 10, unlike those in Figs 4 to 7, have only one entry parameter, H(1 - M~). The accuracy of spectrum shape prediction is about _+ 1.5 dB for point 1 and about ___2 dB for points 16 and 28. This is not unexpected since a single parameter is used to predict a very complex spectrum function influenced by many factors. 1 For

39

EMPIRICAL METHOD FOR PREDICTION OF JET CABIN NOISE LEVELS

example, engine noise peaks make their contribution to the SPL at low frequencies and reduce data correlation with H(I - Mo~). The influence of engine noise is less noticeable for point 1, distant from the engine noise source. Figures 8 and 9 show engine noise peaks predicted at the 100 Hz and 160 Hz frequency bands noticeable for low SPL values and masked for higher ones. It is also possible to see the displacement of the location of the central maximum with increase of H(1 - M ~ ) - to the region of larger frequencies for point 1 and to that of smaller frequencies for point 16. These relationships are in accordance with the data of Experiments 1 and 2. Other frequency bands of larger prediction errors (and of less strong correlation between the SPL and H(1 - M~) values) are the bands adjacent to 1000 Hz and 4000 Hz.

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M ® - f l i g h t mach; H - a l t i t u d e ; L~ reference SPL

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0.63

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t.6

2.5

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6.3 tOkHz frequency

Nomograph for the prediction of one-third octave band spectrum levels for point 1.

40

N. M. MOSES, TANYA ROXNER POINT

16

SPL

~'N ~" , /~ / ~ _ ~ - ~ ' ~

L2+55 dB

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Iii.3 10 kHz frequency

N o m o g r a p h for the prediction of one-third octave band spectrum levels for point 16.

For point 28 (see Fig. 10) the dotted parts of the prediction spectrum curves and the high frequency band range do not show any noticeable correlation between the SPL and H(I - Moo) values. In the case of the 800 Hz band and the high frequency range (6"3 + 10 kHz) the predicted values can be obtained with the help of multiple correlation with H and Moo (whereas the 160Hz band appears to show no correlation with H and Moo or with H(1 - Moo )). The results of such a prediction for point 28 at 800 Hz and in the high frequency range (6.3 - 10 kHz) are not shown in Fig. 10 because it should be a three-dimensional nomograph with two entry variables, H a n d Moo. It is possible to plot the results of such a prediction in the form of a Table or a n o m o g r a p h for each of the bands of interest taken separately. CONCLUSIONS

(a)

O A S P L values measured at different points along the axis of a WW-1124

EMPIRICAL METHOD FOR PREDICTION

41

OF JET CABIN NOISE LEVELS

POINT

28

SPL

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M¢o- f l i g h t

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L2+65

I

0.1

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0.25

0.4

0.63

1

1.6

2.5

4

kHz frequency

N o m o g r a p h for the prediction o f one-third octave band spectrum levels for point 28.

cabin show a strong correlation with H(1 - Moo) values (H--altitude, M~o --flight mach). SPL values for a fixed frequency band of the one-third octave band spectrum are also strongly correlated with H(1 - Moo) for most frequency bands from 63 to 104 Hz. The strong correlation between OASPL (or SPL, for a fixed frequency band) and H(1 - Moo) makes it possible to develop a simple prediction method for the OASPL as well as for the spectrum shape if the test flight conditions are given. The advantages of the method are: high accuracy (about + l d B for the OASPL and about +1.5 + 2 d B for the SPL (spectrum shape)) and the possibility of obtaining a prediction for a wide range of test flight conditions based on only a few experimental measurements. Practical prediction can be performed quickly with the help of nomographs

42

N. M. MOSES, TANYA ROXNER (given a n y two o f three test c o n d i t i o n variables, H, M:~: and Vc (flight speed), for O A S P L p r e d i c t i o n o r the value o f H(1 - M:~) for s p e c t r u m s h a p e prediction).

ACKNOWLEDGEMENTS The a u t h o r s wish to t h a n k L. Shaki who p e r f o r m e d the flight noise m e a s u r e m e n t s .

REFERENCE 1. N. GANESAN,Evaluation of aircraft internal noise. Society of Automotive Engineers' Preprint No. 740360 for Business Aircraft Meeting, Wichita, Kansas, USA, 2-5 April, 1974, 7 pp.