Acoustic control in enclosures using optimally designed Helmholtz resonators
Abstract (Summary)
A virtual design methodology is developed to minimize the noise in enclosures
with optimally designed, passive, acoustic absorbers (Helmholtz resonators). A series
expansion of eigen functions is used to represent the acoustic absorbers as external
volume velocities, eliminating the need for a solution of large matrix eigen value
problems. A determination of this type (efficient model/reevaluation approach)
significantly increases the design possibilities when optimization techniques are
implemented. As a benchmarking exercise, this novel methodology was experimentally
validated for a narrowband acoustic assessment of two optimally designed Helmholtz
resonators coupled to a 2D enclosure. The resonators were tuned to the two lowest
resonance frequencies of a 30.5 by 40.6 by 2.5 cm (12 x 16 x 1 inch) cavity with the
resonator volume occupying only 2% of the enclosure volume. A maximum potential
energy reduction of 12.4 dB was obtained at the second resonance of the cavity.
As a full-scale demonstration of the efficacy of the proposed design method, the
acoustic response from 90-190 Hz of a John Deere 7000 Ten series tractor cabin was
investigated. The lowest cabin mode, referred to as a “boom” mode, proposes a
significant challenge to a noise control engineer since its anti-node is located near the
head of the operator and often generates unacceptable sound pressure levels. Exploiting
the low frequency capability of Helmholtz resonators, lumped parameter models of these
resonators were coupled to the enclosure via an experimentally determined acoustic
model of the tractor cabin. The virtual design methodology uses gradient optimization
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techniques as a post processor for the modeling and analysis of the unmodified acoustic
interior to determine optimal resonator characteristics. Using two optimally designed
Helmholtz resonators; potential energy was experimentally reduced by 3.4 and 10.3 dB at
117 and 167 Hz, respectively.
Bibliographical Information:
Advisor:
School:Pennsylvania State University
School Location:USA - Pennsylvania
Source Type:Master's Thesis
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