...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Performance of Constructed Facilities >Consequence of Failure: Neurofuzzy-Based Prediction Model for Gas Pipelines
【24h】

Consequence of Failure: Neurofuzzy-Based Prediction Model for Gas Pipelines

机译：失效后果：基于神经模糊的燃气管道预测模型

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Overall performance of energy infrastructure in the United States has been assessed as D+. More than 65% of America's energy is transported through the oil and gas pipelines, which have experienced more than 10,000 failures during the last three decades. There is a critical need for a failure prediction tool that can forecast the consequences of the hazardous failures. Failure of gas pipelines has become the subject of interest for some studies in the past. Previous studies mainly focused on physical models that need inspection data or developed subjective models. This paper aims at developing a model to forecast the consequences of the potential failures of such pipes using the historical data of the U.S. gas pipes network. The model applies a neurofuzzy technique in order to recognize the existing pattern among the input and output variables. It estimates the financial consequences of various failure scenarios for specific pipes in terms of size and specified minimum yield strength. For this purpose, a bowtie model is developed, and all possible scenarios of failure are identified. Various combinations of the identified factors and different number and types of membership functions, are applied in order to optimize the model's efficiency. The developed model is validated with an approximate accuracy of 80%. This study assists practitioners and academics who are working on the risk assessment of gas pipelines to plan for their lifecycle inspection. (C) 2015 American Society of Civil Engineers.
机译：美国能源基础设施的总体绩效已评估为D +。美国超过65％的能源是通过石油和天然气管道输送的，在过去的三十年中，石油和天然气管道经历了10,000多次故障。迫切需要一种可以预测危险故障后果的故障预测工具。过去，天然气管道的故障已成为一些研究的主题。先前的研究主要集中在需要检查数据的物理模型或开发的主观模型上。本文旨在开发一种模型，以使用美国天然气管网的历史数据预测此类管道的潜在故障后果。该模型应用了神经模糊技术，以便识别输入和输出变量之间的现有模式。它根据尺寸和指定的最小屈服强度来估算特定管道各种故障场景的财务后果。为此，开发了领结模型，并确定了所有可能的故障情况。为了优化模型的效率，应用了已识别因素的各种组合以及隶属函数的不同数量和类型。所开发的模型以大约80％的准确度验证。这项研究可以帮助从事天然气管道风险评估的从业者和学者规划其生命周期检查。 （C）2015年美国土木工程师学会。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号