Persistent Link:
http://hdl.handle.net/10150/595972
Title:
Optimization Under Uncertainty of Nonlinear Energy Sinks
Author:
Boroson, Ethan Rain
Issue Date:
2015
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Nonlinear Energy Sinks (NESs) are a promising technique for passively reducing the amplitude of vibrations. Through nonlinear stiffness properties, a NES is able to passively absorb energy. Unlike a traditional Tuned Mass Damper (TMD), NESs do not require a specific tuning and absorb energy from a wide range of frequencies. However, each NES is only efficient over a limited range of excitations. In addition, NES efficiency is extremely sensitive to perturbations in design parameters or loading, demonstrating a nearly discontinuous efficiency. Therefore, in order to optimally design a NES, uncertainties must be accounted for. This thesis focuses on optimally selecting parameters to design an effective NES system through optimization under uncertainty. For this purpose, a specific algorithm is introduced that makes use of clustering techniques to segregate efficient and inefficient NES behavior. SVM and Kriging approximations as well as new adaptive sampling techniques are used for the optimization under uncertainty. The variables of the problems are either random design variables or aleatory variables. For example, the excitation applied to the main vibrating system is treated as aleatory. In an effort to increase the range of excitations for which NESs are effective, a combination of NESs configured in parallel is considered. Optimization under uncertainty is performed on several examples with varying design parameters as well as different numbers of NESs (from 1 to 10). Results show that combining NESs in parallel is an effective method to increase the excitation range over which a NES is effective.
Type:
text; Electronic Thesis
Keywords:
Optimization; Uncertainty; Mechanical Engineering; NES
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College; Mechanical Engineering
Degree Grantor:
University of Arizona
Advisor:
Missoum, Samy

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleOptimization Under Uncertainty of Nonlinear Energy Sinksen_US
dc.creatorBoroson, Ethan Rainen
dc.contributor.authorBoroson, Ethan Rainen
dc.date.issued2015en
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.description.abstractNonlinear Energy Sinks (NESs) are a promising technique for passively reducing the amplitude of vibrations. Through nonlinear stiffness properties, a NES is able to passively absorb energy. Unlike a traditional Tuned Mass Damper (TMD), NESs do not require a specific tuning and absorb energy from a wide range of frequencies. However, each NES is only efficient over a limited range of excitations. In addition, NES efficiency is extremely sensitive to perturbations in design parameters or loading, demonstrating a nearly discontinuous efficiency. Therefore, in order to optimally design a NES, uncertainties must be accounted for. This thesis focuses on optimally selecting parameters to design an effective NES system through optimization under uncertainty. For this purpose, a specific algorithm is introduced that makes use of clustering techniques to segregate efficient and inefficient NES behavior. SVM and Kriging approximations as well as new adaptive sampling techniques are used for the optimization under uncertainty. The variables of the problems are either random design variables or aleatory variables. For example, the excitation applied to the main vibrating system is treated as aleatory. In an effort to increase the range of excitations for which NESs are effective, a combination of NESs configured in parallel is considered. Optimization under uncertainty is performed on several examples with varying design parameters as well as different numbers of NESs (from 1 to 10). Results show that combining NESs in parallel is an effective method to increase the excitation range over which a NES is effective.en
dc.typetexten
dc.typeElectronic Thesisen
dc.subjectOptimizationen
dc.subjectUncertaintyen
dc.subjectMechanical Engineeringen
dc.subjectNESen
thesis.degree.nameM.S.en
thesis.degree.levelmastersen
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorUniversity of Arizonaen
dc.contributor.advisorMissoum, Samyen
dc.contributor.committeememberMissoum, Samyen
dc.contributor.committeememberNikravesh, Parvizen
dc.contributor.committeememberShkarayev, Sergeyen
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