An uncertain computational model for random vibration analysis of subsea pipelines subjected to spatially varying ground motions

Yahui, Zhang, Yuyin, Li and Kennedy, David ORCID: https://orcid.org/0000-0002-8837-7296 2019. An uncertain computational model for random vibration analysis of subsea pipelines subjected to spatially varying ground motions. Engineering Structures 183 , pp. 550-561. 10.1016/j.engstruct.2019.01.031

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Abstract

Based on a nonparametric modelling approach, this paper presents a random vibration analysis of a subsea pipeline subjected to spatially varying ground motions. The earthquake-induced ground motions are modelled as nonstationary random processes and their spatial variations are considered. The modelling uncertainties of the subsea pipeline are taken into account using a random matrix theory, while the unilateral contact relationship between the pipeline and seabed is also considered. Thus, an uncertain computational model for the subsea pipeline subjected to a random earthquake is established, and the corresponding solutions are calculated using Monte Carlo simulation (MCS). In order to highlight the contribution of the unilateral contact effect to random responses of pipelines, comparative studies are performed between the unilateral and permanent contact models. In numerical examples, the possible convergence problems in the present computational model are firstly studied to determine the optimal numbers of reduced modes and MCS samples. Then influences of the randomness in the earthquake and modelling uncertainties in the pipeline are investigated qualitatively through three representative cases. The different propagations of randomness and modelling uncertainties in the unilateral and permanent models are also examined and discussed. It is concluded that the randomness of the earthquake and modelling uncertainties of the pipeline have significant influences on the statistical characteristics of earthquake responses of the pipeline.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	0141-0296
Date of First Compliant Deposit:	8 January 2019
Date of Acceptance:	7 January 2019
Last Modified:	06 Jan 2024 18:06
URI:	https://orca.cardiff.ac.uk/id/eprint/118218

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