Abstract
Gas pipeline pressure-flow problem are affected by varieties of factors notably frictional pressure drop and other pressure drops components. These problems inevitably result in the reduction of the operating efficiency of gas pipelines by virtue of reduction in the line throughput and increased pressure drop along the line. It has been established that increased pressure drop will ultimately lead to increased pump power as well as higher cost of design, construction and operations of gas pipelines. These prevailing factors prompts the need to ascertain the stability and reliability of the optimal flow results. The develop sensitivity model prediction was hinged around ∆L/L (%) being zero. It invariably confirmed that the results of optimal flow capacity are more sensitive to changes in upstream and downstream pressures. It was least sensitive to pressure gradients. The governing conditions being that changes in pipe diameter, ∆D/D (%) and flow capacity, ∆Q/Q (%) were in the order of 5%.
Highlights
Gas pipeline pressure-flow problem are affected by varieties of factors notably frictional pressure drop and other pressure drops components
These problems inevitably result in the reduction of the operating efficiency of gas pipelines by virtue of reduction in the line throughput and increased pressure drop along the line
ANALYSIS OF RESULTS All considerations subject to ∆L/L(%) being zero, confirmed that the allowable pressure drop along a Natural gas pipeline network system could be contained within the limit of 19.057bar and 54.34nar
Summary
Gas pipeline pressure-flow problem are affected by varieties of factors notably frictional pressure drop and other pressure drops components. These problems inevitably result in the reduction of the operating efficiency of gas pipelines by virtue of reduction in the line throughput and increased pressure drop along the line. The research work in view is an empirical approach to sensitivity of optimal flows to changes in control variables. In brevity, this will clearly portray the dependency of the line pressure drop to changes in other governing control variables
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