Abstract

PurposeThe aim of this study is to assess the opportunity for the development of hydrocarbon transportation using high-strength steel (HSS) in pipeline construction in terms of cost savings and reliability.Design/methodology/approachSeveral optimizations of pipeline design and operations were performed to estimate the total life-cycle cost variation associated with different grades of high-strength steel. The generalized reduced gradient (GRG) method was used in an Excel table to determine optimal total life cycle each pipeline. Variables used in this optimization with respect to each steel grade were as follows: pipeline external diameter, wall thickness, number of compression stations and installed power in each compression station. The reliability of a pipeline with optimal cost was assessed to highlight the impact of steel grade on pipeline reliability.FindingsThe study showed that the cost reduction is strongly dependent on the adopted gas pipeline configuration. The number of compression stations and external diameter are the main factors influencing the pipeline total life cycle cost, while the steel price seems to have a minor effect, the reduction of the gas pipeline total life cycle does not exceed 5% even with a 50% difference in pipe steel prices between X70 and X100 steels. On the other side, for the same external diameter, X100 steel presents better pipeline reliability against carbonic corrosion compared to X70 steel.Practical implicationsThe main contribution of this study is to provide a decision-support tool to help pipeline constructors enhance the profitability of natural gas transmission pipelines. The optimization method used is simple to use for design engineers during a feasibility study.Originality/valueThe present study presents one step to fill the gap concerning the question of balancing the trade-off between cost savings and structural reliability in high-strength steel pipelines during the early stages of feasibility studies. The optimal design and operations parameters ensuring cost savings on total life cycle costs are identified via an optimization method. The impact of selected optimal parameters on the long-term pipeline service life was estimated via a structural reliability analysis.

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