Issue |
MATEC Web Conf.
Volume 333, 2021
The 18th Asian Pacific Confederation of Chemical Engineering Congress (APCChE 2019)
|
|
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Article Number | 06003 | |
Number of page(s) | 6 | |
Section | Process Systems Engineering | |
DOI | https://doi.org/10.1051/matecconf/202133306003 | |
Published online | 08 January 2021 |
Verification of CFD Prediction Accuracy of Particle and Droplet Induced Erosion Rate for Engineering Applications
EN Technology Center, JGC Corporation, 2-3-1, Minato Mirai, Nishi-ku, Yokohama 220-6001, Japan
* Corresponding author: qian.shaoxiang@jgc.com
The solid particles or liquid droplets entrained by multi-phase flow in process plants can cause erosion resulting in pipe wall thinning. Hence, it is essential to evaluate erosion rate for determining design margin and taking counter-measures. Many models have been proposed for prediction of erosion induced by particles and droplets, but there is significant difference in their prediction accuracy. The present study aims at verifying prediction accuracy of some major erosion models using the published experimental data, for engineering applications. CFD benchmark simulations were conducted for different flow velocities and piping geometries to investigate prediction accuracy of particle-induced erosion rates for five major erosion models, using the experimental data in literature. CFD results show that the erosion rates predicted by Grant and Tabakoff model are closest to the experimental results with acceptable prediction accuracy for engineering applications. At the same time, CFD benchmark simulations were also carried out to verify the prediction accuracy of droplet induced erosion rates for three erosion models, using the published experimental data. CFD results show that the erosion rates predicted by Haugen model for all the water impingement velocities are closest to the experimental results with acceptable prediction accuracy for engineering applications.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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