
Even though oil and gas pipelines are the safest way to transport petroleum products, they still break generating hazardous consequences and irreparable environmental damages. Many models have been developed in the last decade to predict pipeline failure and conditions. However, most of these models were limited to one break type, such as corrosion, or relied mainly on expert opinion analysis. The objective of this paper is to develop a model that predicts the break cause of oil and gas pipelines based on factors other than corrosion. A fuzzy-based model was developed to help decision makers predict break occurrence using fuzzy expert system (FES) according to historical data of pipeline accidents. The model was able to satisfactorily predict pipeline breaks due to mechanical, operational, corrosion, third party, and natural hazards with an average percent validity of 93%. The developed model will assist decision makers and pipeline operators to predict the expected break cause(s) and to take the necessary actions to avoid them.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
