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Author:

An, Shao (An, Shao.) | Wang, Wei (Wang, Wei.) (Scholars:王伟) | Wang, Ziyi (Wang, Ziyi.)

Indexed by:

EI Scopus

Abstract:

For the drawbacks of complex buried pipeline structural performance function and large amount of calculation of nonlinear problems and to obtain the influence on pipeline failure probability of the shear wave velocity, characteristic period, pipeline diameter, wall thickness, seismic wave incidence angle in different site types. Firstly based on the FOSM of traditional reliability analysis, the artificial neural network is introduced to do intelligent analysis and the failure probability is calculated separately in different site types. The comparison with FOSM shows that the results are reliable. Secondly, the commonly used gray cast iron pipeline at home is analyzed. Finally, some meaningful conclusions that siteIand IV are respectively the most favorable and disadvantaged sections, the buried pipeline seismic capacity can be improved by the method of increasing pipe diameter and wall thickness in site II, III, are obtained. © 2015 ejge.

Keyword:

Cast iron Wave propagation Seismic waves Intelligent computing Shear waves Seismology Structural analysis Reliability Neural networks Reliability analysis Shear flow Complex networks Pipelines

Author Community:

  • [ 1 ] [An, Shao]Institute of Earthquake Resistance and Disaster Reduction, Beijing University of Technology, Beijing, China
  • [ 2 ] [Wang, Wei]College of Architecture and Urban Planning, Institute of Earthquake Resistance and Disaster Reduction, Beijing University of Technology, Beijing, China
  • [ 3 ] [Wang, Ziyi]Zhengzhou Design and Research Institute of Coal Industry Co. Ltd, Zhenzhou, China

Reprint Author's Address:

  • 王伟

    [wang, wei]college of architecture and urban planning, institute of earthquake resistance and disaster reduction, beijing university of technology, beijing, china

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Source :

Electronic Journal of Geotechnical Engineering

Year: 2015

Issue: 23

Volume: 20

Page: 11693-11705

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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