Transmission pipelines comprise a major part of a gas network, conveying natural gas within jurisdictions, and across international boundaries. In the United States, more than 10,000 failure incidents have been reported in gas transmission pipelines in a 20-year period from 1996 to 2016 leading to a cumulative property damage of more than $748 million. Among different failure sources, corrosion is ranked as the most frequent one, corresponding to approximately a quarter of total failures. Though in-line inspection is counted as the most frequently applied corrosion monitoring technique for oil and gas pipelines, it imposes considerable costs due to the necessity of implementing frequent inspections using smart devices. For this reason, several failure prediction models have been developed to estimate the corrosion failure. However, the majorities of these prediction models rely solely on experimental tests or limited historical records which undermine the extent of their applicability and ignore pipeline environmental and geographical circumstances. The objective of this research is to develop failure prediction models for external corrosion in underground gas transmission pipelines by considering both conventional and environmental/geographical variables. For this objective, multiple regression analysis was performed on the accessible historical data reported for gas transmission pipelines. Two main climate regions of Great Plains and South East in the US were selected, and their corresponding failure prediction models were developed. Such development was based on a step by step procedure analyzing different scenarios. Considering diagnostic measures, null hypothesis and residual analysis, scenario 3 was selected as satisfactory. The validation tests of the developed models present a root mean square error (RMSE) of 0.04 and 0.07 and R-Sq of 0.93 and 0.75, respectively. The results of this research can be applied in maintenance planning of gas transmission pipeline to estimate the critical time in which a pipeline may encounter external corrosion failure, and to accordingly schedule the maintenance activities.

输气管道占天然气网络的主要部分，可在辖区内和跨国际边界输送天然气。在美国，从1996年到2016年的20年间，天然气输送管道发生了10,000多起故障事件，累计财产损失超过7.48亿美元。在不同的故障源中，腐蚀被列为最常见的故障源，约占全部故障的四分之一。尽管在线检查被认为是油气管道最常用的腐蚀监测技术，但是由于必须使用智能设备进行频繁的检查，因此它带来了可观的成本。因此，已经开发了几种失效预测模型来估计腐蚀失效。然而，这些预测模型的大多数仅依赖于实验测试或有限的历史记录，这破坏了它们的适用范围，并忽略了管道的环境和地理环境。这项研究的目的是通过考虑常规变量和环境/地理变量来开发地下输气管道外部腐蚀的故障预测模型。为此，对报告的输气管道可访问的历史数据进行了多元回归分析。选择了美国大平原和东南部的两个主要气候区域，并开发了它们相应的破坏预测模型。此类开发基于逐步分析不同场景的过程。考虑诊断措施，零假设和残差分析，选择方案3是令人满意的。所开发模型的验证测试分别显示出均方根误差（RMSE）为0.04和0.07，R-Sq为0.93和0.75。该研究结果可用于输气管道的维修计划，以估计管道可能遭受外部腐蚀破坏的关键时间，并据此安排维修活动。