Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | 107184 |
Fachzeitschrift | Mechanical Systems and Signal Processing |
Jahrgang | 149 |
Frühes Online-Datum | 31 Aug. 2020 |
Publikationsstatus | Veröffentlicht - 15 Feb. 2021 |
Abstract
The response analysis of the composite structural-acoustic systems with multiple types of epistemic uncertainties is investigated in this paper. Based on the available information for the uncertain parameters, the multiple types of epistemic uncertainties refer to probability-box (p-box) variables, evidence variables and interval variables. The proposed development focused on an efficient computation of the output bounds of the cumulative distribution function of the sound pressure response when dealing with the combination of p-box variables, evidence variables and interval variables. To reduce the involved computational cost but ensuring the accuracy, all evidence variables and interval variables are transformed into p-box-form variables. Then, a modified interval Monte Carlo method (MIMCM) is developed to estimate the bounds of the cumulative distribution function of the system response. In MIMCM, a sparse Gegenbauer polynomial surrogate model is established with focus on the efficiency and accuracy and then applied for the interval analysis in each iteration. A numerical example and two engineering examples with respect to multiple types of epistemic uncertainties are carried out to illustrate the accuracy and efficiency of the MIMCM by conducting comparisons with traditional algorithms. The ability of the proposed method for risk and conservative reliability analysis is also investigated.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Signalverarbeitung
- Ingenieurwesen (insg.)
- Tief- und Ingenieurbau
- Ingenieurwesen (insg.)
- Luft- und Raumfahrttechnik
- Ingenieurwesen (insg.)
- Maschinenbau
- Informatik (insg.)
- Angewandte Informatik
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in: Mechanical Systems and Signal Processing, Jahrgang 149, 107184, 15.02.2021.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - A probability-box-based method for propagation of multiple types of epistemic uncertainties and its application on composite structural-acoustic system
AU - Zhu, Whenqing
AU - Chen, Ning
AU - Liu, Jian
AU - Beer, Michael
N1 - Funding Information: The paper is supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 51621004 ), the National Natural Science Foundation of China (Grant No. 51905162 ), the Natural Science Foundation of Hunan Province (Grant No. 2019JJ50062 ) and the Fundamental Research Funds for the Central Universities (Grant No. 531107051148 ). The authors would also like to thank reviewers for their valuable suggestions.
PY - 2021/2/15
Y1 - 2021/2/15
N2 - The response analysis of the composite structural-acoustic systems with multiple types of epistemic uncertainties is investigated in this paper. Based on the available information for the uncertain parameters, the multiple types of epistemic uncertainties refer to probability-box (p-box) variables, evidence variables and interval variables. The proposed development focused on an efficient computation of the output bounds of the cumulative distribution function of the sound pressure response when dealing with the combination of p-box variables, evidence variables and interval variables. To reduce the involved computational cost but ensuring the accuracy, all evidence variables and interval variables are transformed into p-box-form variables. Then, a modified interval Monte Carlo method (MIMCM) is developed to estimate the bounds of the cumulative distribution function of the system response. In MIMCM, a sparse Gegenbauer polynomial surrogate model is established with focus on the efficiency and accuracy and then applied for the interval analysis in each iteration. A numerical example and two engineering examples with respect to multiple types of epistemic uncertainties are carried out to illustrate the accuracy and efficiency of the MIMCM by conducting comparisons with traditional algorithms. The ability of the proposed method for risk and conservative reliability analysis is also investigated.
AB - The response analysis of the composite structural-acoustic systems with multiple types of epistemic uncertainties is investigated in this paper. Based on the available information for the uncertain parameters, the multiple types of epistemic uncertainties refer to probability-box (p-box) variables, evidence variables and interval variables. The proposed development focused on an efficient computation of the output bounds of the cumulative distribution function of the sound pressure response when dealing with the combination of p-box variables, evidence variables and interval variables. To reduce the involved computational cost but ensuring the accuracy, all evidence variables and interval variables are transformed into p-box-form variables. Then, a modified interval Monte Carlo method (MIMCM) is developed to estimate the bounds of the cumulative distribution function of the system response. In MIMCM, a sparse Gegenbauer polynomial surrogate model is established with focus on the efficiency and accuracy and then applied for the interval analysis in each iteration. A numerical example and two engineering examples with respect to multiple types of epistemic uncertainties are carried out to illustrate the accuracy and efficiency of the MIMCM by conducting comparisons with traditional algorithms. The ability of the proposed method for risk and conservative reliability analysis is also investigated.
KW - Composite structural-acoustic system
KW - Modified interval Monte Carlo method
KW - Multiple types of epistemic uncertainties
KW - Probability-box
KW - Sparse Gegenbauer polynomial
UR - http://www.scopus.com/inward/record.url?scp=85089938118&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2020.107184
DO - 10.1016/j.ymssp.2020.107184
M3 - Article
AN - SCOPUS:85089938118
VL - 149
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
SN - 0888-3270
M1 - 107184
ER -