Preliminary Analysis of the ChinchillaBlast Overpressure Data

William J. MurphyAmir Khan

Peter B. ShawHearing Loss Prevention Section

Division of Applied Research and TechnologyNational 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.

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Outline Summary of Exposures

Spectrum Interstimulus Interval Level

Exposure Metrics MilStd 1474D LAeq8hr Unprotected AHAAH Warned & Unwarned Pfander Smoorenburg

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Statistical 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

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/freq

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Conventional Shock Tube Nonreverberant

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Fast Acting Valve

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Spark Gap Generated Impulse

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Narrow Band Impact Noises

260 Hz775 Hz1025 Hz1350 Hz2450 Hz3550 Hz

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Temporary Threshold Shift vs MIL-STD-1474D

MIL-STD-1474D (dB)

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Temporary Threshold Shift vs Pfander

Pfander (dB)

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Temporary Threshold Shift vs Smoorenburg

Smoorenburg (dB)

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Temporary Threshold Shift vs Unwarned AHAAH

Unwarned AHAAH (ARUs)

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Temporary Threshold Shift vs Warned AHAAH

Warned AHAAH (ARUs)

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Temporary Threshold Shift vs LAeq8

LAeq8 (dB)

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Permanent Threshold Shift vs MIL-STD-1474D

MIL-STD-1474D (dB)

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Permanent Threshold Shift vs Pfander

Pfander (dB)

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Permanent Threshold Shift vs Smoorenburg

Smoorenburg (dB)

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Permanent Threshold Shift vs Warned AHAAH

Warned AHAAH (ARUs)

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Permanent Threshold Shift vs Unwarned AHAAH

Unwarned AHAAH (ARUs)

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Permanent Threshold Shift vs LAeq8

LAeq8 (dB)

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hres

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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

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PTS 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

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TTS 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

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Preliminary 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.

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Discussion 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)

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Discussion 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?