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A New Interface Identification Technique Based on Absolute Density Gradient for Violent Flows

Yan Zhou1, Qingwei Ma*

School of Mathematics, Computer Science and Engineering, City University London , Northampton Square, London, EC1V 0HB.

*Corresponding Author: Qingwei Ma. Email: email.

Computer Modeling in Engineering & Sciences 2018, 115(2), 131-147. https://doi.org/10.3970/cmes.2018.00249

Abstract

An identification technique for sharp interface and penetrated isolated particles is developed for simulating two-dimensional, incompressible and immiscible two-phase flows using meshless particle methods in this paper. This technique is based on the numerically computed density gradient of fluid particles and is suitable for capturing large interface deformation and even topological changes such as merging and breaking up of phases. A number of assumed particle configurations will be examined using the technique, including these with different level of randomness of particle distribution. The tests will show that the new technique can correctly identify almost all the interface and isolated particles, and also show that it is better than other existing popular methods tested.

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Cite This Article

APA Style
Zhou, Y., Ma, Q. (2018). A new interface identification technique based on absolute density gradient for violent flows. Computer Modeling in Engineering & Sciences, 115(2), 131-147. https://doi.org/10.3970/cmes.2018.00249
Vancouver Style
Zhou Y, Ma Q. A new interface identification technique based on absolute density gradient for violent flows. Comput Model Eng Sci. 2018;115(2):131-147 https://doi.org/10.3970/cmes.2018.00249
IEEE Style
Y. Zhou and Q. Ma, “A New Interface Identification Technique Based on Absolute Density Gradient for Violent Flows,” Comput. Model. Eng. Sci., vol. 115, no. 2, pp. 131-147, 2018. https://doi.org/10.3970/cmes.2018.00249



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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