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An Objective Material Selection Metr...

Pessler, Devon,

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An Objective Material Selection Metric for Acoustic Guitar Soundboards /

Record Type:	Electronic resources : Monograph/item
Title/Author:	An Objective Material Selection Metric for Acoustic Guitar Soundboards // Devon Pessler.
Author:	Pessler, Devon,
Description:	1 electronic resource (121 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-04, Section: A.
Contained By:	Dissertations Abstracts International86-04A.
Subject:	Wood. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31285304
ISBN:	9798342104258

An Objective Material Selection Metric for Acoustic Guitar Soundboards /
Pessler, Devon,

An Objective Material Selection Metric for Acoustic Guitar Soundboards /Devon Pessler. - 1 electronic resource (121 pages)

Source: Dissertations Abstracts International, Volume: 86-04, Section: A.

Acoustic guitar soundboard material selection is based on selective evaluations that have been developed over centuries. These traditional practices are not conducive to the guitar industry we experience today because the supply of traditionally acceptable soundboard wood has decreased greatly. The purpose of this research was to develop an objective wood selection metric to determine the sound quality of an acoustic guitar's soundboard. The metric would replace the subjective evaluations traditionally used to select materials for acoustic guitar soundboards.The acoustic properties of sound radiation coefficient, material's speed of sound, resonance and damping and the material properties of longitudinal and radial elastic modulus, density, and specific modulus were used in an attempt to construct a material selection metric. These variables were selected because the literature review revealed that these were the most critical variables in determining sound quality. The gaps in the literature were testing and analyzing samples that represented the true dimensions of an acoustic guitar soundboard blank and forming the metric. The literature revealed that the previous experimental studies did not have the appropriate test sample dimensions that correspond to the test samples evaluated by the subjective methods.The methodology was carried out by using the objective testing counterparts to the subjective assessments found in the literature review. Instrumented hammer tap testing collected data to determine damping and resonance frequencies. A three-point static bending test collected data for longitudinal and radial elastic modulus. Mass and dimension measurements were recorded to calculate density. Calculations were done to compute the acoustic properties and specific modulus of the test samples. These variables were put into a table and underwent statistical analysis in the form of predictor correlation and logistical regression. The experimental variables were modeled against an expert's subjective evaluation of the test samples' usability.Statistical analysis proved that the dataset did not show any significant separation between "good" or "bad" test samples or a significant correlation between the usability of the test sample and the variables in the dataset. The methodology did not produce an objective material selection metric to determine the sound quality of an acoustic guitar's soundboard. Future research should include a wider range of measured frequencies and the collection of time domain data.

English

ISBN: 9798342104258Subjects--Topical Terms:

540142
Wood.

An Objective Material Selection Metric for Acoustic Guitar Soundboards /
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520 $a Acoustic guitar soundboard material selection is based on selective evaluations that have been developed over centuries. These traditional practices are not conducive to the guitar industry we experience today because the supply of traditionally acceptable soundboard wood has decreased greatly. The purpose of this research was to develop an objective wood selection metric to determine the sound quality of an acoustic guitar's soundboard. The metric would replace the subjective evaluations traditionally used to select materials for acoustic guitar soundboards.The acoustic properties of sound radiation coefficient, material's speed of sound, resonance and damping and the material properties of longitudinal and radial elastic modulus, density, and specific modulus were used in an attempt to construct a material selection metric. These variables were selected because the literature review revealed that these were the most critical variables in determining sound quality. The gaps in the literature were testing and analyzing samples that represented the true dimensions of an acoustic guitar soundboard blank and forming the metric. The literature revealed that the previous experimental studies did not have the appropriate test sample dimensions that correspond to the test samples evaluated by the subjective methods.The methodology was carried out by using the objective testing counterparts to the subjective assessments found in the literature review. Instrumented hammer tap testing collected data to determine damping and resonance frequencies. A three-point static bending test collected data for longitudinal and radial elastic modulus. Mass and dimension measurements were recorded to calculate density. Calculations were done to compute the acoustic properties and specific modulus of the test samples. These variables were put into a table and underwent statistical analysis in the form of predictor correlation and logistical regression. The experimental variables were modeled against an expert's subjective evaluation of the test samples' usability.Statistical analysis proved that the dataset did not show any significant separation between "good" or "bad" test samples or a significant correlation between the usability of the test sample and the variables in the dataset. The methodology did not produce an objective material selection metric to determine the sound quality of an acoustic guitar's soundboard. Future research should include a wider range of measured frequencies and the collection of time domain data.
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