Durham School of Architectural Engineering and Construction

 

Date of this Version

8-2012

Document Type

Article

Comments

A Thesis Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Architectural Engineering, Under the Supervision of Professor Lily M. Wang. Lincoln, Nebraska: August, 2012

Copyright 2012 Christopher Ainley

Abstract

The goal of this research project is to better quantify human reactions to short bursts of noise, to complement research at NASA Langley Research Center on evaluating human response inside buildings to low-level sonic booms. The project involved exposing participants over 30-minute sessions to a number of 250 ms broadband noise bursts of certain levels, presented in a controlled yet randomized fashion throughout the session, and gathering responses on human perception and performance on an arithmetic task dealing with short-term memory. While previous research has demonstrated effects of noise bursts of varying amplitudes on other types of tasks that study cognitive processing including attention and at louder levels on this arithmetic task (i.e. 100 dB peak), more information is needed to indicate at what level and to what degree such noise bursts may impact human performance and perception.

Twenty-seven test subjects were tested over multiple 30-minute test sessions, with four different levels of the noise bursts. The noise bursts ranged from peak A-weighted sound pressure levels (LApk) of 47 to 77 dBA presented over an ambient background noise level of 37 dB Leq measured over 2 minutes, or RC-29 (H).

Few significant relationships were found in relation to task performance, although there are still some general trends including an increase in incorrect answers for impulse-presented test questions as the noise burst level increases. Results show significant relationships, pApkaround 67 dBA and higher may not be considered acceptable in an otherwise ambient background noise level condition, in this case RC-29(H).

Adviser: Lily M. Wang

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