Numerical Modeling and Evaluation of Pigging in Pipeline Using SPH Method with Performance Optimization Approach

Document Type : Original Article

Authors

1 School of Mechanical Engineering, Yazd University, Yazd, Iran

2 School of Mechanical Engineering, Sirjan University, Sirjan, Iran

Abstract

Due to importance of pigging operations for purposes such as monitoring-cleaning, which leads to an increase in the service life of pipeline networks, management, and optimization of energy consumption in oil and gas industries, providing accurate numerical models is a research need that has been very vital. Considering advantages of meshless methods, for the first time in this research a model is presented for evaluating the flow around the pig using the smooth particle hydrodynamics (SPH) method and the standard k-ε model to simulate the turbulence of the flow. Besides, the performance of the model based on the experimental study has been evaluated and validated. The results showed that the average error rate of the SPH model compared to the laboratory model was less than 5%, which indicated the research model's high accuracy and acceptable performance. After validating the performance of the research model, the simulation of the flow around the stationary and mobile pig was modeled, and the results were compared and evaluated with the existing numerical results. In addition, by using a meta-heuristic algorithm of gray wolves optimization (GWO), studies wereconducted on the relative diameter parameter of the bypass pig to achieve optimal values of this parameter. The results of the optimization model showed that the optimal relative diameter of the bypass pig was equal to d⁄D=0.418. The results of this research showed that the presented model had an acceptable accuracy in modeling the flow around the bypass pig in the pipe, and it could also be used as a reference model based on the SPH method for modeling the flow around the bypass pig.

Keywords

Main Subjects

References

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Energy Engineering and Management
Volume 13, Issue 2
September 2023
Pages 140-161

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