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Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties
Composite Structures, Volume: 160, Pages: 312 - 334
Swansea University Author: Sondipon Adhikari
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DOI (Published version): 10.1016/j.compstruct.2016.10.035
Abstract
This paper presents a stochastic approach to study the natural frequencies of thin-walled laminated composite beams with spatially varying matrix cracking damage in a multi-scale framework. A novel concept of stochastic representative volume element (SRVE) is introduced for this purpose. An efficien...
Published in: | Composite Structures |
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ISSN: | 0263-8223 |
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2017
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URI: | https://cronfa.swan.ac.uk/Record/cronfa30718 |
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2016-11-11T15:14:47.2331220 v2 30718 2016-10-19 Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties 4ea84d67c4e414f5ccbd7593a40f04d3 0000-0003-4181-3457 Sondipon Adhikari Sondipon Adhikari true false 2016-10-19 ACEM This paper presents a stochastic approach to study the natural frequencies of thin-walled laminated composite beams with spatially varying matrix cracking damage in a multi-scale framework. A novel concept of stochastic representative volume element (SRVE) is introduced for this purpose. An efficient radial basis function (RBF) based uncertainty quantification algorithm is developed to quantify the probabilistic variability in free vibration responses of the structure due to spatially random stochasticity in the micro-mechanical and geometric properties. The convergence of the proposed algorithm for stochastic natural frequency analysis of damaged thin-walled composite beam is verified and validated with original finite element method (FEM) along with traditional Monte Carlo simulation (MCS). Sensitivity analysis is carried out to ascertain the relative influence of different stochastic input parameters on the natural frequencies. Subsequently the influence of noise is investigated on radial basis function based uncertainty quantification algorithm to account for the inevitable variability for practical field applications. The study reveals that stochasticity/ system irregularity in structural and material attributes affects the system performance significantly. To ensure robustness, safety and sustainability of the structure, it is very crucial to consider such forms of uncertainties during the analysis. Journal Article Composite Structures 160 312 334 0263-8223 15 1 2017 2017-01-15 10.1016/j.compstruct.2016.10.035 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University 2016-11-11T15:14:47.2331220 2016-10-19T14:11:52.5309380 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised S. Naskar 1 T. Mukhopadhyay 2 S. Sriramula 3 S. Adhikari 4 Sondipon Adhikari 0000-0003-4181-3457 5 0030718-19102016141306.pdf naskar2016.pdf 2016-10-19T14:13:06.1630000 Output 2705761 application/pdf Accepted Manuscript true 2017-10-18T00:00:00.0000000 false |
title |
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties |
spellingShingle |
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties Sondipon Adhikari |
title_short |
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties |
title_full |
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties |
title_fullStr |
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties |
title_full_unstemmed |
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties |
title_sort |
Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties |
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4ea84d67c4e414f5ccbd7593a40f04d3 |
author_id_fullname_str_mv |
4ea84d67c4e414f5ccbd7593a40f04d3_***_Sondipon Adhikari |
author |
Sondipon Adhikari |
author2 |
S. Naskar T. Mukhopadhyay S. Sriramula S. Adhikari Sondipon Adhikari |
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Journal article |
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Composite Structures |
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2017 |
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Swansea University |
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0263-8223 |
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10.1016/j.compstruct.2016.10.035 |
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Faculty of Science and Engineering |
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Faculty of Science and Engineering |
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Faculty of Science and Engineering |
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School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised |
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description |
This paper presents a stochastic approach to study the natural frequencies of thin-walled laminated composite beams with spatially varying matrix cracking damage in a multi-scale framework. A novel concept of stochastic representative volume element (SRVE) is introduced for this purpose. An efficient radial basis function (RBF) based uncertainty quantification algorithm is developed to quantify the probabilistic variability in free vibration responses of the structure due to spatially random stochasticity in the micro-mechanical and geometric properties. The convergence of the proposed algorithm for stochastic natural frequency analysis of damaged thin-walled composite beam is verified and validated with original finite element method (FEM) along with traditional Monte Carlo simulation (MCS). Sensitivity analysis is carried out to ascertain the relative influence of different stochastic input parameters on the natural frequencies. Subsequently the influence of noise is investigated on radial basis function based uncertainty quantification algorithm to account for the inevitable variability for practical field applications. The study reveals that stochasticity/ system irregularity in structural and material attributes affects the system performance significantly. To ensure robustness, safety and sustainability of the structure, it is very crucial to consider such forms of uncertainties during the analysis. |
published_date |
2017-01-15T19:01:10Z |
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11.04748 |