MACHINE LEARNING-BASED INVESTIGATIONS ON NONLINEAR VIBRATIONS OF CFRP COMPOSITE

Jia Ao Hou; Chao Wu; Yangping Yao; Renyuan Qin; Denvid Lau; Lik Ho Tam

MACHINE LEARNING-BASED INVESTIGATIONS ON NONLINEAR VIBRATIONS OF CFRP COMPOSITE

Jia Ao Hou
, Chao Wu^*
, Yangping Yao
, Renyuan Qin
, Denvid Lau
, Lik Ho Tam^*

^*Corresponding author for this work

School of Transportation Science and Engineering

Beihang University
Dongguan University of Technology
City University of Hong Kong

Research output: Contribution to conference › Paper › peer-review

2 Scopus citations

Abstract

Carbon fiber-reinforced polymer (CFRP) composite has been increasingly used in constructions, which is subjected to external loads that cause severe nonlinear vibrations and final structural failure. In this work, a machine learning approach is adopted to investigate nonlinear vibrations of CFRP composite. A dataset about nonlinear frequency ratios of CFRP composite under different load levels, sizes, and boundary conditions is established, which is used to train prediction model. Using developed model, attribute importance of nonlinear vibration and nonlinear frequency ratios under various conditions are investigated. The finding of this work contributes to predicting long-term vibration properties of CFRP composite.

Original language	English
State	Published - 2023
Event	11th International Conference on Fiber-Reinforced Polymer ,FRP Composites in Civil Engineering, CICE 2023 - Rio de Janeiro, Brazil Duration: 23 Jul 2023 → 26 Jul 2023

Conference

Conference	11th International Conference on Fiber-Reinforced Polymer ,FRP Composites in Civil Engineering, CICE 2023
Country/Territory	Brazil
City	Rio de Janeiro
Period	23/07/23 → 26/07/23

Keywords

CFPR composite
Compression load
Machine learning
Nonlinear vibration
Prediction model

Cite this

@conference{214d347da25342409f6ebd4df97e8d44,

title = "MACHINE LEARNING-BASED INVESTIGATIONS ON NONLINEAR VIBRATIONS OF CFRP COMPOSITE",

abstract = "Carbon fiber-reinforced polymer (CFRP) composite has been increasingly used in constructions, which is subjected to external loads that cause severe nonlinear vibrations and final structural failure. In this work, a machine learning approach is adopted to investigate nonlinear vibrations of CFRP composite. A dataset about nonlinear frequency ratios of CFRP composite under different load levels, sizes, and boundary conditions is established, which is used to train prediction model. Using developed model, attribute importance of nonlinear vibration and nonlinear frequency ratios under various conditions are investigated. The finding of this work contributes to predicting long-term vibration properties of CFRP composite.",

keywords = "CFPR composite, Compression load, Machine learning, Nonlinear vibration, Prediction model",

author = "Hou, \{Jia Ao\} and Chao Wu and Yangping Yao and Renyuan Qin and Denvid Lau and Tam, \{Lik Ho\}",

note = "Publisher Copyright: {\textcopyright} CICE 2023 - 11th International Conference on FRP Composites in Civil Engineering. All rights reserved.; 11th International Conference on Fiber-Reinforced Polymer ,FRP Composites in Civil Engineering, CICE 2023 ; Conference date: 23-07-2023 Through 26-07-2023",

year = "2023",

language = "英语",

}

TY - CONF

T1 - MACHINE LEARNING-BASED INVESTIGATIONS ON NONLINEAR VIBRATIONS OF CFRP COMPOSITE

AU - Hou, Jia Ao

AU - Wu, Chao

AU - Yao, Yangping

AU - Qin, Renyuan

AU - Lau, Denvid

AU - Tam, Lik Ho

PY - 2023

Y1 - 2023

N2 - Carbon fiber-reinforced polymer (CFRP) composite has been increasingly used in constructions, which is subjected to external loads that cause severe nonlinear vibrations and final structural failure. In this work, a machine learning approach is adopted to investigate nonlinear vibrations of CFRP composite. A dataset about nonlinear frequency ratios of CFRP composite under different load levels, sizes, and boundary conditions is established, which is used to train prediction model. Using developed model, attribute importance of nonlinear vibration and nonlinear frequency ratios under various conditions are investigated. The finding of this work contributes to predicting long-term vibration properties of CFRP composite.

AB - Carbon fiber-reinforced polymer (CFRP) composite has been increasingly used in constructions, which is subjected to external loads that cause severe nonlinear vibrations and final structural failure. In this work, a machine learning approach is adopted to investigate nonlinear vibrations of CFRP composite. A dataset about nonlinear frequency ratios of CFRP composite under different load levels, sizes, and boundary conditions is established, which is used to train prediction model. Using developed model, attribute importance of nonlinear vibration and nonlinear frequency ratios under various conditions are investigated. The finding of this work contributes to predicting long-term vibration properties of CFRP composite.

KW - CFPR composite

KW - Compression load

KW - Machine learning

KW - Nonlinear vibration

KW - Prediction model

UR - https://www.scopus.com/pages/publications/85197549015

M3 - 论文

AN - SCOPUS:85197549015

T2 - 11th International Conference on Fiber-Reinforced Polymer ,FRP Composites in Civil Engineering, CICE 2023

Y2 - 23 July 2023 through 26 July 2023

ER -

MACHINE LEARNING-BASED INVESTIGATIONS ON NONLINEAR VIBRATIONS OF CFRP COMPOSITE

Abstract

Conference

Keywords

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