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A probability model of predicting the sand erosion in elbows for annular flow.

Authors :
Kang, Rong
Liu, Haixiao
Source :
Wear. Mar2019, Vol. 422, p167-179. 13p.
Publication Year :
2019

Abstract

Abstract Annular flow is a common flow pattern in oil and gas pipelines for its stability and efficiency. During the oil and gas production, sand particles are inevitably carried by annular flow to continuously impact on elbows, and thus make the sand erosion in elbows a notable problem. In the present work, both the first and second collisions are taken into account in the collision probability analysis. The decay effects of liquid film on particles are considered in calculating the impact velocities of particles, and the particle impact information is introduced into erosion correlations to estimate the erosion ratio. By combining the collision probability models and the erosion correlations, a novel probability model for annular flow is developed to predict the sand erosion in elbows. Numerous experiments are employed to examine the accuracy of the present model, and the applicability and efficiency of the probability model are demonstrated by comparing with other erosion models. Finally, the effects of first and second collisions on the formation of erosion profiles, as well as the relations between the erosion profile and the superficial gas velocity, superficial liquid velocity and curvature of elbow, are investigated in detail to acquire more knowledge of the sand erosion in elbows under annular flow conditions. Highlights • A probability model for annular flow is developed to predict the sand erosion in elbows. • Decay effects of liquid film on particle velocities are firstly introduced in theoretical analysis. • The erosion caused by second collision in annular flow is considered in analysis. • Maximum penetration rates and entire erosion profiles can be directly calculated. • The model shows advantages in both applicability and accuracy of prediction. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00431648
Volume :
422
Database :
Academic Search Index
Journal :
Wear
Publication Type :
Academic Journal
Accession number :
134821575
Full Text :
https://doi.org/10.1016/j.wear.2019.01.059