Cargando…

Study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration

A vehicle-bridge tuned mass damper (TMD) coupled dynamic analysis and vibration-control model was established to optimize TMD damping effects on a steel-box girder bridge bearing vehicle loads. It was also used to investigate optimization efficiency of different algorithms in TMD design parameters....

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Jianwei, Li, Dejian, Yu, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478324/
https://www.ncbi.nlm.nih.gov/pubmed/31013304
http://dx.doi.org/10.1371/journal.pone.0215773
_version_ 1783413151979536384
author Liu, Jianwei
Li, Dejian
Yu, Peng
author_facet Liu, Jianwei
Li, Dejian
Yu, Peng
author_sort Liu, Jianwei
collection PubMed
description A vehicle-bridge tuned mass damper (TMD) coupled dynamic analysis and vibration-control model was established to optimize TMD damping effects on a steel-box girder bridge bearing vehicle loads. It was also used to investigate optimization efficiency of different algorithms in TMD design parameters. This model simulated bridges and vehicles with the use of a 7 degrees of freedom curved-beam element model and a 7 degrees of freedom vehicle model, respectively. The TMD system was simulated with the use of multiple rigid-body systems linked with springs and dampers. Road surface condition, as a vibration source, was simulated with the use of a frequency equivalent method based on a power spectrum. A variably-accelerated pattern search algorithm was proposed in line with the initial TMD parameters calculated by Den Hartog formula. Visual software was compiled by Fortran and used for an optimization study of vibration reduction. A three-span, curved, continuous steel-box girder bridge was used as the numerical example. Optimized effects and computational efficiency of vibration reduction under different methods were compared. The comparison included a single variable optimization based on Den Hartog formula, an ergodic search method, an integer programming method, a traditional genetic algorithm, a traditional pattern search algorithm, and a variably-accelerated pattern search algorithm. The results indicate that variably-accelerated pattern search algorithm is more efficient at improving TMD optimal parameter design. Final TMD parameter optimization values obtained by different methods are quite close to each other and tends verify the reliability of the optimization results.
format Online
Article
Text
id pubmed-6478324
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-64783242019-05-07 Study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration Liu, Jianwei Li, Dejian Yu, Peng PLoS One Research Article A vehicle-bridge tuned mass damper (TMD) coupled dynamic analysis and vibration-control model was established to optimize TMD damping effects on a steel-box girder bridge bearing vehicle loads. It was also used to investigate optimization efficiency of different algorithms in TMD design parameters. This model simulated bridges and vehicles with the use of a 7 degrees of freedom curved-beam element model and a 7 degrees of freedom vehicle model, respectively. The TMD system was simulated with the use of multiple rigid-body systems linked with springs and dampers. Road surface condition, as a vibration source, was simulated with the use of a frequency equivalent method based on a power spectrum. A variably-accelerated pattern search algorithm was proposed in line with the initial TMD parameters calculated by Den Hartog formula. Visual software was compiled by Fortran and used for an optimization study of vibration reduction. A three-span, curved, continuous steel-box girder bridge was used as the numerical example. Optimized effects and computational efficiency of vibration reduction under different methods were compared. The comparison included a single variable optimization based on Den Hartog formula, an ergodic search method, an integer programming method, a traditional genetic algorithm, a traditional pattern search algorithm, and a variably-accelerated pattern search algorithm. The results indicate that variably-accelerated pattern search algorithm is more efficient at improving TMD optimal parameter design. Final TMD parameter optimization values obtained by different methods are quite close to each other and tends verify the reliability of the optimization results. Public Library of Science 2019-04-23 /pmc/articles/PMC6478324/ /pubmed/31013304 http://dx.doi.org/10.1371/journal.pone.0215773 Text en © 2019 Liu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Liu, Jianwei
Li, Dejian
Yu, Peng
Study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration
title Study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration
title_full Study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration
title_fullStr Study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration
title_full_unstemmed Study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration
title_short Study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration
title_sort study on optimization algorithm of tuned mass damper parameters to reduce vehicle-bridge coupled vibration
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478324/
https://www.ncbi.nlm.nih.gov/pubmed/31013304
http://dx.doi.org/10.1371/journal.pone.0215773
work_keys_str_mv AT liujianwei studyonoptimizationalgorithmoftunedmassdamperparameterstoreducevehiclebridgecoupledvibration
AT lidejian studyonoptimizationalgorithmoftunedmassdamperparameterstoreducevehiclebridgecoupledvibration
AT yupeng studyonoptimizationalgorithmoftunedmassdamperparameterstoreducevehiclebridgecoupledvibration