Optimization under uncertainty of Nonlinear Energy Sinks

Ethan Boroson, Samy Missoum, Pierre Olivier Mattei, Christophe Vergez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Nonlinear Energy Sinks (NES) are used to passively reduce the amplitude of vibrations. This reduction is made possible by introducing a nonlinearly stiffening behavior in the NES, which might lead to an irreversible transfer of energy between the main system (e.g., a building) and the NES. However, this irreversible transfer, and therefore the efficiency of the NES, is strongly dependent on the design parameters of the NES. In fact, the efficiency of the NES might be so sensitive to changes in design parameters and other factors (e.g., initial conditions) that it is discontinuous, switching from efficiency to inefficiency for a small perturbation of parameters. For this reason, this work introduces a novel technique for the optimization under uncertainty of NES. The approach is based on a support vector machine classifier, which is insensitive to discontinuities and allows one to efficiently propagate uncertainties. This enables one to efficiently solve an optimization under uncertainty problem. The various techniques presented in this paper are applied to an analytical NES example.

Original languageEnglish (US)
Title of host publicationProceedings of the ASME Design Engineering Technical Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
Volume8
ISBN (Print)9780791846414
DOIs
StatePublished - 2014
EventASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014 - Buffalo, United States
Duration: Aug 17 2014Aug 20 2014

Other

OtherASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014
CountryUnited States
CityBuffalo
Period8/17/148/20/14

Fingerprint

Uncertainty
Optimization
Energy
Support vector machines
Classifiers
Parameter Design
Small Perturbations
Discontinuity
Support Vector Machine
Initial conditions
Vibration
Classifier
Dependent

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

Cite this

Boroson, E., Missoum, S., Mattei, P. O., & Vergez, C. (2014). Optimization under uncertainty of Nonlinear Energy Sinks. In Proceedings of the ASME Design Engineering Technical Conference (Vol. 8). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2014-34238

Optimization under uncertainty of Nonlinear Energy Sinks. / Boroson, Ethan; Missoum, Samy; Mattei, Pierre Olivier; Vergez, Christophe.

Proceedings of the ASME Design Engineering Technical Conference. Vol. 8 American Society of Mechanical Engineers (ASME), 2014.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Boroson, E, Missoum, S, Mattei, PO & Vergez, C 2014, Optimization under uncertainty of Nonlinear Energy Sinks. in Proceedings of the ASME Design Engineering Technical Conference. vol. 8, American Society of Mechanical Engineers (ASME), ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014, Buffalo, United States, 8/17/14. https://doi.org/10.1115/DETC2014-34238
Boroson E, Missoum S, Mattei PO, Vergez C. Optimization under uncertainty of Nonlinear Energy Sinks. In Proceedings of the ASME Design Engineering Technical Conference. Vol. 8. American Society of Mechanical Engineers (ASME). 2014 https://doi.org/10.1115/DETC2014-34238
Boroson, Ethan ; Missoum, Samy ; Mattei, Pierre Olivier ; Vergez, Christophe. / Optimization under uncertainty of Nonlinear Energy Sinks. Proceedings of the ASME Design Engineering Technical Conference. Vol. 8 American Society of Mechanical Engineers (ASME), 2014.
@inproceedings{348cfc2f32da469b9a0079360086fa6c,
title = "Optimization under uncertainty of Nonlinear Energy Sinks",
abstract = "Nonlinear Energy Sinks (NES) are used to passively reduce the amplitude of vibrations. This reduction is made possible by introducing a nonlinearly stiffening behavior in the NES, which might lead to an irreversible transfer of energy between the main system (e.g., a building) and the NES. However, this irreversible transfer, and therefore the efficiency of the NES, is strongly dependent on the design parameters of the NES. In fact, the efficiency of the NES might be so sensitive to changes in design parameters and other factors (e.g., initial conditions) that it is discontinuous, switching from efficiency to inefficiency for a small perturbation of parameters. For this reason, this work introduces a novel technique for the optimization under uncertainty of NES. The approach is based on a support vector machine classifier, which is insensitive to discontinuities and allows one to efficiently propagate uncertainties. This enables one to efficiently solve an optimization under uncertainty problem. The various techniques presented in this paper are applied to an analytical NES example.",
author = "Ethan Boroson and Samy Missoum and Mattei, {Pierre Olivier} and Christophe Vergez",
year = "2014",
doi = "10.1115/DETC2014-34238",
language = "English (US)",
isbn = "9780791846414",
volume = "8",
booktitle = "Proceedings of the ASME Design Engineering Technical Conference",
publisher = "American Society of Mechanical Engineers (ASME)",

}

TY - GEN

T1 - Optimization under uncertainty of Nonlinear Energy Sinks

AU - Boroson, Ethan

AU - Missoum, Samy

AU - Mattei, Pierre Olivier

AU - Vergez, Christophe

PY - 2014

Y1 - 2014

N2 - Nonlinear Energy Sinks (NES) are used to passively reduce the amplitude of vibrations. This reduction is made possible by introducing a nonlinearly stiffening behavior in the NES, which might lead to an irreversible transfer of energy between the main system (e.g., a building) and the NES. However, this irreversible transfer, and therefore the efficiency of the NES, is strongly dependent on the design parameters of the NES. In fact, the efficiency of the NES might be so sensitive to changes in design parameters and other factors (e.g., initial conditions) that it is discontinuous, switching from efficiency to inefficiency for a small perturbation of parameters. For this reason, this work introduces a novel technique for the optimization under uncertainty of NES. The approach is based on a support vector machine classifier, which is insensitive to discontinuities and allows one to efficiently propagate uncertainties. This enables one to efficiently solve an optimization under uncertainty problem. The various techniques presented in this paper are applied to an analytical NES example.

AB - Nonlinear Energy Sinks (NES) are used to passively reduce the amplitude of vibrations. This reduction is made possible by introducing a nonlinearly stiffening behavior in the NES, which might lead to an irreversible transfer of energy between the main system (e.g., a building) and the NES. However, this irreversible transfer, and therefore the efficiency of the NES, is strongly dependent on the design parameters of the NES. In fact, the efficiency of the NES might be so sensitive to changes in design parameters and other factors (e.g., initial conditions) that it is discontinuous, switching from efficiency to inefficiency for a small perturbation of parameters. For this reason, this work introduces a novel technique for the optimization under uncertainty of NES. The approach is based on a support vector machine classifier, which is insensitive to discontinuities and allows one to efficiently propagate uncertainties. This enables one to efficiently solve an optimization under uncertainty problem. The various techniques presented in this paper are applied to an analytical NES example.

UR - http://www.scopus.com/inward/record.url?scp=84930192764&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84930192764&partnerID=8YFLogxK

U2 - 10.1115/DETC2014-34238

DO - 10.1115/DETC2014-34238

M3 - Conference contribution

AN - SCOPUS:84930192764

SN - 9780791846414

VL - 8

BT - Proceedings of the ASME Design Engineering Technical Conference

PB - American Society of Mechanical Engineers (ASME)

ER -