IMPACT RELIABILITY ANALYSIS OF ISOLATION SYSTEM SHOCK ABSORBER

Hongyi An; Zhonghui Qiu; Xi Liu; Rongqiao Wang; Dianyin Hu

doi:10.1049/icp.2023.1619

IMPACT RELIABILITY ANALYSIS OF ISOLATION SYSTEM SHOCK ABSORBER

Hongyi An
, Zhonghui Qiu
, Xi Liu^*
, Rongqiao Wang
, Dianyin Hu

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

A reliability analysis study was conducted on the shock absorber used in a certain ship. Firstly, a multi-source uncertainty quantification model was established. Different forms of models are used to quantify the uncertainty of loads, geometric shapes, and material properties based on their characteristics. Then, combining Monte-Carlo method with BP neural network surrogate model, the relationship between input variables and output acceleration is established. Finally, based on the surrogate model, the response distribution and reliability of the shock absorber are obtained, which provides a reference for the subsequent structural analysis and optimization.

Original language	English
Pages (from-to)	49-57
Number of pages	9
Journal	IET Conference Proceedings
Volume	2023
Issue number	9
DOIs	https://doi.org/10.1049/icp.2023.1619
State	Published - 2023
Event	13th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2023 - Kunming, China Duration: 26 Jul 2023 → 29 Jul 2023

Keywords

ABSORBER
MONTE-CARLO METHOD
RELIABILITY ANALYSIS
SURROGATE MODEL

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10.1049/icp.2023.1619

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title = "IMPACT RELIABILITY ANALYSIS OF ISOLATION SYSTEM SHOCK ABSORBER",

abstract = "A reliability analysis study was conducted on the shock absorber used in a certain ship. Firstly, a multi-source uncertainty quantification model was established. Different forms of models are used to quantify the uncertainty of loads, geometric shapes, and material properties based on their characteristics. Then, combining Monte-Carlo method with BP neural network surrogate model, the relationship between input variables and output acceleration is established. Finally, based on the surrogate model, the response distribution and reliability of the shock absorber are obtained, which provides a reference for the subsequent structural analysis and optimization.",

keywords = "ABSORBER, MONTE-CARLO METHOD, RELIABILITY ANALYSIS, SURROGATE MODEL",

author = "Hongyi An and Zhonghui Qiu and Xi Liu and Rongqiao Wang and Dianyin Hu",

note = "Publisher Copyright: {\textcopyright} The Institution of Engineering \& Technology 2023.; 13th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2023 ; Conference date: 26-07-2023 Through 29-07-2023",

year = "2023",

doi = "10.1049/icp.2023.1619",

language = "英语",

volume = "2023",

pages = "49--57",

journal = "IET Conference Proceedings",

issn = "2732-4494",

publisher = "Institution of Engineering and Technology",

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TY - JOUR

T1 - IMPACT RELIABILITY ANALYSIS OF ISOLATION SYSTEM SHOCK ABSORBER

AU - An, Hongyi

AU - Qiu, Zhonghui

AU - Liu, Xi

AU - Wang, Rongqiao

AU - Hu, Dianyin

N1 - Publisher Copyright: © The Institution of Engineering & Technology 2023.

PY - 2023

Y1 - 2023

N2 - A reliability analysis study was conducted on the shock absorber used in a certain ship. Firstly, a multi-source uncertainty quantification model was established. Different forms of models are used to quantify the uncertainty of loads, geometric shapes, and material properties based on their characteristics. Then, combining Monte-Carlo method with BP neural network surrogate model, the relationship between input variables and output acceleration is established. Finally, based on the surrogate model, the response distribution and reliability of the shock absorber are obtained, which provides a reference for the subsequent structural analysis and optimization.

AB - A reliability analysis study was conducted on the shock absorber used in a certain ship. Firstly, a multi-source uncertainty quantification model was established. Different forms of models are used to quantify the uncertainty of loads, geometric shapes, and material properties based on their characteristics. Then, combining Monte-Carlo method with BP neural network surrogate model, the relationship between input variables and output acceleration is established. Finally, based on the surrogate model, the response distribution and reliability of the shock absorber are obtained, which provides a reference for the subsequent structural analysis and optimization.

KW - ABSORBER

KW - MONTE-CARLO METHOD

KW - RELIABILITY ANALYSIS

KW - SURROGATE MODEL

UR - https://www.scopus.com/pages/publications/85188289341

U2 - 10.1049/icp.2023.1619

DO - 10.1049/icp.2023.1619

M3 - 会议文章

AN - SCOPUS:85188289341

SN - 2732-4494

VL - 2023

SP - 49

EP - 57

JO - IET Conference Proceedings

JF - IET Conference Proceedings

IS - 9

T2 - 13th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2023

Y2 - 26 July 2023 through 29 July 2023

ER -

IMPACT RELIABILITY ANALYSIS OF ISOLATION SYSTEM SHOCK ABSORBER

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Keywords

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