Communications in Information and Systems

Volume 17 (2017)

Number 3

SPH-based simulation of liquid wetting across textile materials

Pages: 147 – 169

DOI: https://dx.doi.org/10.4310/CIS.2017.v17.n3.a2

Authors

Aihua Mao (School of Computer Science and Engineering, South China University of Technology, Guangzhou, China)

Mingle Wang (School of Computer Science and Engineering, South China University of Technology, Guangzhou, China)

Yong-Jin Liu (Department of Computer Science and Technology, Tsinghua University, Beijing, China)

Huamin Wang (Department of Computer Science and Engineering, Ohio State University, Columbus, Oh., U.S.A.)

Guiqing Li (School of Computer Science and Engineering, South China University of Technology, Guangzhou, China)

Abstract

This paper presents a simulation framework for liquid wetting across porous textiles with anisotropic inner structure. The textile is composed by intersected fibers and forms capillary pores in the void space, which provides an important force to drive the diffusion by capillary action. The influence of the properties of the textile on the wetting process, such as contact angle, hygroscopicity and porosity, is considered into the liquid wetting process in detail. By liquid-textile coupling, the wetting process is simulated through liquid absorption/desorption by fiber and liquid diffusion in the means of inner fiber, intersected fibers and capillary action. The second Fick’s law is used to describe the non-steady wetting process. Based on the SPH method for fluid simulation, this framework can simulate the liquid wetting across the porous textile by dripping single or multiple drops of water. We also demonstrate the wetting process with the influence of different properties of the textile.

Full Text (PDF format)

Aihua Mao’s research was supported by NSF of Guangdong Province under Grant 2016A03 0313499, The Science and Technology Planning Project of Guangdong Province under Grant 2015A030401030 and the Fundamental Research Funds for the Central Universities under Grant2017ZD054.

Yong-jin Liu’s research was supported by the Natural Science Foundation of China (61725204, 61661130156) and Beijing Higher Institution Engineering Research Center of Visual Media Intelligent Processing and Security.

Published 7 February 2018