A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model

It is necessary to conduct a safety assessment for pipelines which are regarded as important lifeline projects after an earthquake. Since the random process of loading in earthquake engineering requires a large amount of samples, this paper establishes a non-random vibration method based on convex m...

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Main Authors:	Peng Zhang, Yihuan Wang, Guojin Qin
Format:	Article
Language:	English
Published:	MDPI AG 2019-02-01
Series:	Applied Sciences
Subjects:	non-random process earthquake pipelines fuzziness and randomness cloud model
Online Access:	https://www.mdpi.com/2076-3417/9/4/812

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spelling	doaj-fc57131a040a4e9480c5fa90c48d58da2020-11-24T23:30:54ZengMDPI AGApplied Sciences2076-34172019-02-019481210.3390/app9040812app9040812A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud ModelPeng Zhang0Yihuan Wang1Guojin Qin2School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, ChinaSchool of Mechatronic Engineering, Southwest Petroleum University, Chengdu 610500, ChinaSchool of Mechatronic Engineering, Southwest Petroleum University, Chengdu 610500, ChinaIt is necessary to conduct a safety assessment for pipelines which are regarded as important lifeline projects after an earthquake. Since the random process of loading in earthquake engineering requires a large amount of samples, this paper establishes a non-random vibration method based on convex model theory and applies it to small sample engineering. Moreover, a space⁻time analytical model of buried pipeline and a finite element model are established to solve the dynamic response of pipelines with non-random process seismic excitation. Furthermore, the randomness of the stress values of the pipeline subjected to earthquake and the fuzziness of the degree of damage to pipelines are considered. Therefore, a novel method for assessing damage to pipelines is proposed based on cloud model. The results indicate that an analysis of non-random vibration combined with the cloud inference method can solve the fuzziness and randomness of the quantitative description and qualitative concept conversion for damage evaluation of pipelines. The method is also an adaptive and effective assessment method for pipelines exposed to earthquake and is able to promote safety management of pipeline engineering.https://www.mdpi.com/2076-3417/9/4/812non-random processearthquakepipelinesfuzziness and randomnesscloud model
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Peng Zhang Yihuan Wang Guojin Qin
spellingShingle	Peng Zhang Yihuan Wang Guojin Qin A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model Applied Sciences non-random process earthquake pipelines fuzziness and randomness cloud model
author_facet	Peng Zhang Yihuan Wang Guojin Qin
author_sort	Peng Zhang
title	A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model
title_short	A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model
title_full	A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model
title_fullStr	A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model
title_full_unstemmed	A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model
title_sort	novel method to assess safety of buried pressure pipelines under non-random process seismic excitation based on cloud model
publisher	MDPI AG
series	Applied Sciences
issn	2076-3417
publishDate	2019-02-01
description	It is necessary to conduct a safety assessment for pipelines which are regarded as important lifeline projects after an earthquake. Since the random process of loading in earthquake engineering requires a large amount of samples, this paper establishes a non-random vibration method based on convex model theory and applies it to small sample engineering. Moreover, a space⁻time analytical model of buried pipeline and a finite element model are established to solve the dynamic response of pipelines with non-random process seismic excitation. Furthermore, the randomness of the stress values of the pipeline subjected to earthquake and the fuzziness of the degree of damage to pipelines are considered. Therefore, a novel method for assessing damage to pipelines is proposed based on cloud model. The results indicate that an analysis of non-random vibration combined with the cloud inference method can solve the fuzziness and randomness of the quantitative description and qualitative concept conversion for damage evaluation of pipelines. The method is also an adaptive and effective assessment method for pipelines exposed to earthquake and is able to promote safety management of pipeline engineering.
topic	non-random process earthquake pipelines fuzziness and randomness cloud model
url	https://www.mdpi.com/2076-3417/9/4/812
work_keys_str_mv	AT pengzhang anovelmethodtoassesssafetyofburiedpressurepipelinesundernonrandomprocessseismicexcitationbasedoncloudmodel AT yihuanwang anovelmethodtoassesssafetyofburiedpressurepipelinesundernonrandomprocessseismicexcitationbasedoncloudmodel AT guojinqin anovelmethodtoassesssafetyofburiedpressurepipelinesundernonrandomprocessseismicexcitationbasedoncloudmodel AT pengzhang novelmethodtoassesssafetyofburiedpressurepipelinesundernonrandomprocessseismicexcitationbasedoncloudmodel AT yihuanwang novelmethodtoassesssafetyofburiedpressurepipelinesundernonrandomprocessseismicexcitationbasedoncloudmodel AT guojinqin novelmethodtoassesssafetyofburiedpressurepipelinesundernonrandomprocessseismicexcitationbasedoncloudmodel
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A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model

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