In acoustic intensity estimation, adding a microphone at the probe center removes errors associated with pressure averaging. Analytical bias errors are presented for a one-dimensional, three-microphone probe for active intensity, reactive intensity, and specific acoustic impedance in a monopole field. Traditional estimation is compared with the Phase and Amplitude Gradient Estimator (PAGE) method; the PAGE method shows an increased bandwidth for all three quantities. The two- and three-microphone methods are compared experimentally, showing reduced bias errors with three-microphone PAGE for active and reactive intensity, whereas using two microphones is preferred for specific acoustic impedance.
An impulsive noise exposure model for outdoor military shooting ranges was created. The inputs to the model included spatial interpolation of noise exposure metrics measured from a single round of fire from a small-arms ballistic weapon. Energies from this single-shot model were spatially translated and summed to simulate multiple shooters firing multiple rounds based on the equal energy hypothesis for damage risk assessment. A validation measurement was performed, and the uncertainties associated with measurement and modeling were shown to be acceptably low. This model can predict and assess total exposures and protection measures for shooters, instructors, and other range personnel.
Small caliber firearm (SCF) noise sources are typically impulsive in nature, possess a large amount of acoustic energy (consequently a large hearing damage risk), and are not omnidirectional. These sources are often operated in indoor shooting ranges where the potential for noise exposure risk is greater due to the reflective surfaces in the room. Indoor sound propagation models require inputs such as geometry, wall material properties, and some quantified source level description. One such room acoustic modeling technique is the Image-Source Method (ISM). ISM typically assumes specular reflections off the walls and represents those reflections as image sources. Many ISM algorithms can operate with high computational efficiency for simple omnidirectional source models, usually represented by a single quantity: sound power. However, ISM models using an omnidirectional source assumption can produce high errors in some scenarios involving highly directional sources, such as SCFs. In this work, an ISM algorithm has been modified to predict listener exposure levels from non-omnidirectional sources in complicated room designs, and has been validated against measured data from an SCF on an indoor Air Force shooting range.
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