Full Content is available to subscribers

Subscribe/Learn More  >

The Reliability Estimation of Simplified Natural Gas Pipeline Compressor Stations Based on Statistics Principles

[+] Author Affiliations
Muwei Fan, Yang Wu, Wenhui Kong, Jing Gong

China University of Petroleum-Beijing, Beijing, China

Paper No. IPC2016-64084, pp. V002T02A006; 9 pages
  • 2016 11th International Pipeline Conference
  • Volume 2: Pipeline Safety Management Systems; Project Management, Design, Construction and Environmental Issues; Strain Based Design; Risk and Reliability; Northern Offshore and Production Pipelines
  • Calgary, Alberta, Canada, September 26–30, 2016
  • Conference Sponsors: Pipeline Division
  • ISBN: 978-0-7918-5026-6
  • Copyright © 2016 by ASME


With the rapid economic and rigorous requirement of environmental governance, natural gas serves as important energy source in industry consumption. In 2015, the total consumption of natural gas in China is approximately 142 billion m3. As the primary mode of natural gas transport, early pipeline operated for more than 20 years in China, and its reliability also attracts abundant concerns by the increasing potential risks. However, the process of pipeline reliability evaluating and estimation in China is still located under development. To solve the problem, a simplified reliability estimation method is introduced in this article. To begin with the main equipment of a compressing station, the filter, air cooler and compressors are three research objectives. Because of redundant design for enhancing reliability, the major equipment usually operates with a same spare unit. Thus, the simplified station is consisted by 3 main sections with multiple units as filter section, compressing section and cooling section. By assuming their reliability following normal distribution, the multivariate normal distribution model is available. Each unit is characterized by one dimension of the multivariate normal distribution. This article considers both relevant and irrelevant processes while the equipment is operating simultaneously and illustrates the results via two and three dimensions normal distribution calculation. Due to the model being singular function because of be established based on multivariate normal distribution and parameter estimation principles, the analytical solution is not available. Therefore, numerical computation is the compulsory solution. However, the reliability analysis of pipe is different from equipment and it has been studied for years in details from theory to experiments. Consequently, the reliability of pipe is analyzed by statistics method from collected operating data.

A pipeline with 25-years operating data in China is applied in the case study chapter for reliability estimation and analysis. According to the operating data collected by China National Petroleum Corporation, the failure rate of major equipment is estimated by determining the parameters of each distribution and fitted a curve like bathtub curve. Similarly, the failure rate of pipe is indicated as failures per 103 km • year. For comparing, the operating data is also fitted a curve to validate the result of the model with the purpose of reasonably estimating the whole period reliability. The result demonstrates that the model is available in practice if the parameters are determined properly.

Copyright © 2016 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In