The prediction model of erosion rates of surface pipelines on deepwater test platforms
The surface pipelines of deepwater test platforms are susceptible to erosion damage from high-pressure sand-carrying media,and accurate prediction of erosion rate is crucial for ensuring operation and maintenance safety.However,the commonly used Tulsa erosion prediction model primarily focuses on carbon steel and aluminum,rendering it unsuitable for erosion prediction of the special low alloy steel AISI4130.Therefore,a new finite element model has been developed using the display dynamics method to enhance the prediction accuracy,taking into account the effects of impact velocity for particles and impact angle on the key parameters,and the key parameters in the Tulsa model were improved.The results show that:①The particle impact will lead to cutting and deformation wear of the erosion target.The erosion rate initially increases and then decreases as the impact angle increases,reaching the maximum value at an angle of 30°;The erosion rate exhibits a positive correlation with the impact velocity,following a power function.②By simulating the scenario of particles impacting the target material from multiple angles,a more accurate segmented polynomial function for particle impact on the target material was obtained.Compared with the original Tulsa model,which was only used 10° and 15° impact angles for experiments,this study expanded the applicability of the Tulsa model in predicting the erosion rate of surface pipelines on deepwater test platforms.The new segmented angle is 30°,corresponding to the angle at which the maximum erosion rate occurs.③When the particle impact velocity is greater than 10 m/s,the improved prediction model demonstrates superior calculation accuracy compared to the Tulsa model,with a reduction in relative error as impact velocity increases,indicating that the proposed prediction model is suitable for the high-speed flow condition in deep water test platforms.
deepwater test platformpipeline erosionTulsa modelfinite element analysiserosion rate prediction modelimpact parameters
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