Implementation of A Comprehensive Mechanistic Model for The Prediction of Erosive Wear in Pipelines Due to Solid Particles Impact
Keywords:
Erosive model, ANSYS fluent, Impact angle, Particles velocity, Eroded CraterAbstract
In this paper, implementation of a comprehensive mechanistic model for the prediction of erosive wear in pipelines due to solid particles impact was investigated. The aim of this study is to develop a mechanistic model coupled with CFD model to predict the rate of inner-wall erosive wear of pipeline due to the presence of solid particles. This mechanistic model was developed based on Hertzian contact, and Du and Wang elastoplastic impact models; taking the deformation of the erodent particles and the effective impact angle into consideration. The developed models were compared with experimental data from three different sources and with built-in erosion models in FLUENT. The outcome of the simulation show that the developed model is 92% accurate when compared with the experimental values. The mechanistic model of this study shows a good agreement with the existing models. The trend of variation of erosive wear rate with impact angle, particle velocity, and mass flow rate was the same for all the tested models and a robust improvement in the newly developed models. Erosion of coal-liquid slurry in pipelines was also studied in FLUENT using the developed model UDF. The results of the study show that coal-liquid slurry causes erosion in both bent and straight pipe. The point of dense erosion was observed to have drifted along the straight pipeline as the velocity increases, which implies that little or no erosion will be observed when a very high velocity slurry flows through a short straight pipe spool. It is expected that the results of this work will be of significant help for the strengthening of the application of mechanistic models for predicting inner-wall erosive wear. This model can be effectively applied in oil and gas industries worldwide for accurate prediction of inner-wall erosive wear.
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