Liquid Evaporation from Nanochannel with Rough Wall Surface by Direct Simulation Monte Carlo

50 Pages Posted: 2 Apr 2025

See all articles by Ran Li

Ran Li

Beijing University of Technology

Ziqing Yan

Beijing University of Technology

Xiupeng Cheng

Beijing University of Technology

Yinuo Wang

Beijing University of Technology

Guodong Xia

Beijing University of Technology

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Abstract

Roughness in nanoscale channels has profound influences on liquid flow and evaporation from the channel which is relevant in many cutting-edge applications. The direct simulation Monte Carlo (DSMC) method was employed to numerically study the effects of roughness shape, size and interval distance on the liquid evaporation rate from a nanochannel. It was found that the inclination angle of roughness elements plays a vital role in determining the liquid evaporation resistance of nanochannel. Under sparse roughness condition, the rectangle roughness with larger inclination angle leads to higher evaporation resistance. Under dense roughness condition, the vapor was inhibited from entering the gap between rectangle roughness and the velocity sink effect was weakened. The evaporation resistance for rectangle roughness declined as the roughness interval continued to reduce, while triangle and semicircle roughness with smaller inclination angle could retain the increase of evaporation resistance. Larger roughness size leads to higher evaporation resistance for the three roughness shapes. A phenomenological model was proposed to correlate the computed evaporation resistance; the model accounted for roughness inclination angle and had different behaviors under sparse and dense roughness conditions. The evaporation resistance was well correlated to the newly defined model with error being around ± 5%.

Keywords: Liquid evaporation, Nanochannel, roughness, Direct simulation Monte Carlo, Evaporation resistance

Suggested Citation

Li, Ran and Yan, Ziqing and Cheng, Xiupeng and Wang, Yinuo and Xia, Guodong, Liquid Evaporation from Nanochannel with Rough Wall Surface by Direct Simulation Monte Carlo. Available at SSRN: https://ssrn.com/abstract=5201698 or http://dx.doi.org/10.2139/ssrn.5201698

Ran Li (Contact Author)

Beijing University of Technology ( email )

100 Ping Le Yuan
Chaoyang District
Beijing, 100020
China

Ziqing Yan

Beijing University of Technology ( email )

100 Ping Le Yuan
Chaoyang District
Beijing, 100020
China

Xiupeng Cheng

Beijing University of Technology ( email )

100 Ping Le Yuan
Chaoyang District
Beijing, 100020
China

Yinuo Wang

Beijing University of Technology ( email )

100 Ping Le Yuan
Chaoyang District
Beijing, 100020
China

Guodong Xia

Beijing University of Technology ( email )

100 Ping Le Yuan
Chaoyang District
Beijing, 100020
China

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