Development and Validation of a Computational Process for Pass-By Noise Simulation

Zhang, Zhidong; Vlahopoulos, Nickolas; Allen, Thomas E.; Zhang, Kevin; Huang, Xianli; Moenssen, David J.

doi:10.4271/2001-01-1561

Cited by 2 publications

(2 citation statements)

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“…A procedure was developed in the past for characterizing noise sources on a boundary element model from near field data and then using them for performing a pass-by noise simulation [7]. The same procedure is employed in this paper for developing appropriate boundary conditions for the BEA or EBEA analyses.…”

Section: Characterization Of Sources From Nearfield Measurementsmentioning

confidence: 98%

“…The acoustic signature of the vehicle is computed by following a methodology developed in the past for pass-by noise simulations [7]. The acoustic spectrum for each source is used for computing appropriate velocity or intensity boundary conditions (in the BEA or EBEA method, respectively) which recreate the prescribed acoustic spectrum from each source in the nearfield.…”

Section: Introductionmentioning

confidence: 99%

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A computational approach for evaluating the probability of acoustic detection of a military vehicle

Hong

Vlahopoulos

Mantey

et al. 2004

Targets and Backgrounds X: Characterization and Representation

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ADRPM (Acoustic Detection Range Prediction Model) is a software program that models the propagation of acoustic energy through the atmosphere and evaluates detectability. ADRPM predicts the distance of detection for a noise source based on the acoustic signature of the source. In this paper the assessment of the acoustic signature which characterizes a vehicle is performed by the conventional Boundary Element Analysis (BEA), and by the Energy Boundary Element Analysis (EBEA). BEA is used for computing the radiated noise for the 1/3 octave bands up to 500Hz, and the EBEA is used for the remaining frequency range. By combining the conventional BEA (for low frequency) with the EBEA (for high frequency), it is possible to perform noise radiation computations over the entire frequency range in a seamless manner. Once the initial detection range is predicted, the main contributors to the acoustic detection are identified and their location on the vehicle is modified in order to assess the corresponding effect to the detectability.

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Section: Characterization Of Sources From Nearfield Measurementsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%