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Preliminary Analysis of the Chinchilla Blast Overpressure Data William J. Murphy Amir Khan Peter B. Shaw Hearing Loss Prevention Section Division of Applied Research and Technology National Institute for Occupational Safety and Health September 29,2008 The results reported in this paper represent the opinions of the authors and are not representative of the policies of the National Institute for Occupational Safety and Health.

Preliminary Analysis of the Chinchilla Blast Overpressure Data William J. Murphy Amir Khan Peter B. Shaw Hearing Loss Prevention Section Division of Applied

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Preliminary Analysis of the ChinchillaBlast Overpressure Data

Preliminary Analysis of the ChinchillaBlast Overpressure Data

William J. Murphy

Amir Khan

Peter B. ShawHearing Loss Prevention Section

Division of Applied Research and Technology

National Institute for Occupational Safety and Health

September 29,2008

William J. Murphy

Amir Khan

Peter B. ShawHearing Loss Prevention Section

Division of Applied Research and Technology

National Institute for Occupational Safety and Health

September 29,2008

The results reported in this paper represent the opinions of the authors and are not representative of the policies of the

National Institute for Occupational Safety and Health.

The results reported in this paper represent the opinions of the authors and are not representative of the policies of the

National Institute for Occupational Safety and Health.

2

OutlineOutline Summary of Exposures

Spectrum

Interstimulus Interval

Level

Exposure Metrics

MilStd 1474D

LAeq8hr Unprotected

AHAAH Warned & Unwarned

Pfander

Smoorenburg

Summary of Exposures

Spectrum

Interstimulus Interval

Level

Exposure Metrics

MilStd 1474D

LAeq8hr Unprotected

AHAAH Warned & Unwarned

Pfander

Smoorenburg

3

Statistical Analysis of BOP DataStatistical Analysis of BOP Data

Statistical model for effects threshold

Linear Mixed Effects Models

Statistical Fits

Questions to consider for the analysis

Trading Ratios?

Log(AHAAH)

Frequency Dependency

Statistical model for effects threshold

Linear Mixed Effects Models

Statistical Fits

Questions to consider for the analysis

Trading Ratios?

Log(AHAAH)

Frequency Dependency

4

101

102

-70

-60

-50

-40

-30

-20

-10

0

10

Frequency (kHz)

Wel

ch P

ower

Spe

ctra

l Den

sity

Est

imat

eP

ower

/fre

quen

cy (

dB/H

z)

Conventional Shock Tube Nonreverberant

5

101

102

-45

-40

-35

-30

-25

-20

-15

-10

-5

Frequency (kHz)

Wel

ch P

ower

Spe

ctra

l Den

sity

Est

imat

eP

ower

/fre

quen

cy (

dB/H

z)

Fast Acting Valve

6

101

102

-40

-35

-30

-25

-20

-15

-10

Frequency (kHz)

Wel

ch P

ower

Spe

ctra

l Den

sity

Est

imat

eP

ower

/fre

quen

cy (

dB/H

z)

Spark Gap Generated Impulse

7

10-1

100

101

-70

-60

-50

-40

-30

-20

-10

0

10

Frequency Hz

Welc

h P

ow

er

Spectr

al D

ensity E

stim

ate

Pow

er/

Fre

quency (

dB

/Hz)

Narrow Band Impact Noises

260 Hz775 Hz

1025 Hz

1350 Hz

2450 Hz3550 Hz

8

500

2000

8000

140

150

160

170

180

190-10

0

10

20

30

40

50

60

70

80

90

Frequency (Hz)

Temporary Threshold Shift vs MIL-STD-1474D

MIL-STD-1474D (dB)

Tem

pora

ry T

hres

hold

Shi

ft (

dB)

9

500

2000

8000

120

140

160

180

200-10

0

10

20

30

40

50

60

70

80

90

Frequency (Hz)

Temporary Threshold Shift vs Pfander

Pfander (dB)

Tem

pora

ry T

hres

hold

Shi

ft (

dB)

10

500

2000

8000

140

150

160

170

180

190-10

0

10

20

30

40

50

60

70

80

90

Frequency (Hz)

Temporary Threshold Shift vs Smoorenburg

Smoorenburg (dB)

Tem

pora

ry T

hres

hold

Shi

ft (

dB)

11

500

2000

8000

100

102

104

106

-10

0

10

20

30

40

50

60

70

80

90

Frequency (Hz)

Temporary Threshold Shift vs Unwarned AHAAH

Unwarned AHAAH (ARUs)

Tem

pora

ry T

hres

hold

Shi

ft (

dB)

12

500

2000

8000

100

105

-10

0

10

20

30

40

50

60

70

80

90

Frequency (Hz)

Temporary Threshold Shift vs Warned AHAAH

Warned AHAAH (ARUs)

Tem

pora

ry T

hres

hold

Shi

ft (

dB)

13

500

2000

8000

100

110

120

130

140

150-10

0

10

20

30

40

50

60

70

80

90

Frequency (Hz)

Temporary Threshold Shift vs LAeq8

LAeq8

(dB)

Tem

pora

ry T

hres

hold

Shi

ft (

dB)

14

5001000

20004000

8000

150

160

170

180

-10

0

10

20

30

40

50

60

Frequency (Hz)

Permanent Threshold Shift vs MIL-STD-1474D

MIL-STD-1474D (dB)

Perm

anent

Thre

shold

Shift

(dB

)

15

5001000

20004000

8000

120

140

160

180

200-10

0

10

20

30

40

50

60

Frequency (Hz)

Permanent Threshold Shift vs Pfander

Pfander (dB)

Perm

anent

Thre

shold

Shift

(dB

)

16

5001000

20004000

8000

150

160

170

180

-10

0

10

20

30

40

50

60

Frequency (Hz)

Permanent Threshold Shift vs Smoorenburg

Smoorenburg (dB)

Perm

anent

Thre

shold

Shift

(dB

)

17

5001000

20004000

8000

100

105

-10

0

10

20

30

40

50

60

Frequency (Hz)

Permanent Threshold Shift vs Warned AHAAH

Warned AHAAH (ARUs)

Perm

anent

Thre

shold

Shift

(dB

)

18

5001000

20004000

8000

100

102

104

106

-10

0

10

20

30

40

50

60

Frequency (Hz)

Permanent Threshold Shift vs Unwarned AHAAH

Unwarned AHAAH (ARUs)

Perm

anent

Thre

shold

Shift

(dB

)

19

5001000

20004000

8000

100

110

120

130

140

150-10

0

10

20

30

40

50

60

Frequency (Hz)

Permanent Threshold Shift vs LAeq8

LAeq8

(dB)

Perm

anent

Thre

shold

Shift

(dB

)

20

Applied linear mixed effects regression models to compare the different metrics

Fixed effects: metric and frequency and log transformations of these variables

Random effects: subject and exposure code (takes into account correlated nature of data for given subject and exposure code)

Applied linear mixed effects regression models to compare the different metrics

Fixed effects: metric and frequency and log transformations of these variables

Random effects: subject and exposure code (takes into account correlated nature of data for given subject and exposure code)

Statistical Analysis of Chinchilla Data

Statistical Analysis of Chinchilla Data

21

PTS Data AnalysisPTS Data Analysis

Indep. Variables (fixed effects)

AIC BIC

MIL STD 1474D + frequency 51279.99 51320.97

LAeq8+ frequency 51214.76 51255.75

warned AHAAH + frequency 51263.38 51304.36

unwarned AHAAH + frequency

51236.62 51277.6

Pfander + frequency 51253.09 51294.07

Smoorenburg + frequency 51258.78 51299.77

25

TTS DataTTS Data

Indep. Variables (fixed effects) AIC BIC

MIL STD 1474D + frequency 35060.91 35098.91

LAeq8+ frequency 34956.34 34994.34

warned AHAAH + frequency 35068.4 35106.41

unwarned AHAAH + frequency 35055.47 35093.47

Pfander + frequency 35021.17 35059.17

Smoorenburg + frequency 35031.85 35069.85

29

Preliminary FindingsPreliminary Findings

LAeq8 provides the best fit to the TTS data of the competing metrics.

Unwarned AHAAH tends to provide the best fit to the PTS data after a log(AHAAH) transformation.

LAeq8 provides the best fit to the TTS data of the competing metrics.

Unwarned AHAAH tends to provide the best fit to the PTS data after a log(AHAAH) transformation.

30

Discussion TopicsDiscussion Topics

Utility of providing a transformation of AHAAH estimates.

Sampling Rate questions for all models.

Frequency dependency for the models.

AHAAH model may have predictive capability for frequency that other models do not.

Should we pursue finding best trading ratios?

10 log(N), 5 log(N), x log(N)

Utility of providing a transformation of AHAAH estimates.

Sampling Rate questions for all models.

Frequency dependency for the models.

AHAAH model may have predictive capability for frequency that other models do not.

Should we pursue finding best trading ratios?

10 log(N), 5 log(N), x log(N)

31

Discussion topicsDiscussion topics

What outcome variable is the most useful here?

Are we interested in developing a better model to fit the data or just existing models?

What outcome variable is the most useful here?

Are we interested in developing a better model to fit the data or just existing models?