Numerical methodology for simulating particle deposition on superhydrophobic surfaces with randomly distributed rough structures

被引:0
|
作者
Pan, Anjian [1 ]
Cai, Rong-Rong [1 ]
Zhang, Li-Zhi [1 ,2 ]
机构
[1] Key Laboratory of Enhanced Heat Transfer and Energy Conservation of Education Ministry, School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou,510640, China
[2] State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou,510640, China
关键词
Contact forces - Energy - Fast fourier transformation method - Lattice Boltzmann method - Particle surface - Particles depositions - Randomly distributed - Rough surfaces - Standard deviation - Super-hydrophobic surfaces;
D O I
暂无
中图分类号
学科分类号
摘要
Superhydrophobic coatings with a rough structure and low surface energy have been regarded as new high-efficiency anti-dust solutions. However, current research on the anti-dust mechanism of superhydrophobic materials is still insufficient. Main obstacles are the difficulty in determining the contact state between the dust particle and the rough structure and calculating the contact force accurately. Herein, a new methodology that introduces rough surface discretization and extends the Johnson-Kendall-Roberts (JKR) model to solve the adhesive contact forces of a particle-rough surface was proposed. Further, the lattice Boltzmann method coupled with the JKR-based discrete element method was employed to study the particle deposition characteristics on superhydrophobic surfaces with randomly distributed rough structures. Surfaces with different rough structures were reconstructed using the fast Fourier transformation method. The particle-airflow and rough surface-airflow interactions were calculated using the immersed moving boundary method. The coupling models and computation scheme were validated by comparing the simulation results with those recorded by a high-speed camera. The effects of the particle diameter, airflow inlet velocity, surface energy, and surface structures (characterized by skewness, kurtosis and standard deviation) on particle migration, deposition morphology and deposition rate were compared and analyzed. The results indicate that smaller particles with larger velocities are less likely to be deposited on superhydrophobic surface. Increasing the surface energy of the rough surface can significantly enhance the particle deposition rate owing to the strong particle–surface adhesion force. Further, appropriate surface roughness can reduce particle–surface adhesion and particle energy dissipation during collision, thereby leading to a deposition reduction. However, excessive peaks and deep valleys on the rough surface would hinder the rolling and translation of the particles, thereby resulting in particle accumulation on the surface. Finally, using superhydrophobic surfaces with a skewness of 0 and kurtosis of approximately 5.0, and appropriately reducing the standard deviation of the rough-surface structures can significantly enhance the effect of superhydrophobic surfaces on anti-dust performance. © 2021 Elsevier B.V.
引用
收藏
相关论文
共 50 条
  • [1] Numerical methodology for simulating particle deposition on superhydrophobic surfaces with randomly distributed rough structures
    Pan, Anjian
    Cai, Rong-Rong
    Zhang, Li-Zhi
    APPLIED SURFACE SCIENCE, 2021, 568
  • [2] Lattice Boltzmann Simulation of Droplets Impacting on Superhydrophobic Surfaces with Randomly Distributed Rough Structures
    Yuan, Wu-Zhi
    Zhang, Li-Zhi
    LANGMUIR, 2017, 33 (03) : 820 - 829
  • [3] Dynamic behaviors and heat transfer characteristics of impacting droplets on heated superhydrophobic surfaces with randomly distributed rough structures: Numerical simulation and theoretical analysis
    Zhang, Shusheng
    Zhang, Li-Zhi
    PHYSICS OF FLUIDS, 2024, 36 (01)
  • [4] Wenzel to Cassie Transition in Superhydrophobic Randomly Rough Surfaces
    Bottiglione, Francesco
    Di Mundo, Rosa
    Soria, Leonardo
    Carbone, Giuseppe
    NANOSCIENCE AND NANOTECHNOLOGY LETTERS, 2015, 7 (01) : 74 - 78
  • [5] Evaporative Particle Deposition on Superhydrophobic Surfaces
    Dicuangco, Mercy
    Dash, Susmita
    Weibel, Justin A.
    Garimellal, Suresh V.
    PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2013, VOL 10, 2014,
  • [6] Statistical theory of wetting of liquid drops on superhydrophobic randomly rough surfaces
    Afferrante, L.
    Carbone, G.
    PHYSICAL REVIEW E, 2015, 92 (04):
  • [7] Particle deposition onto rough surfaces
    Lo Iacono, Giovanni
    Reynolds, Andy M.
    Tucker, Paul G.
    JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME, 2008, 130 (07): : 0745011 - 0745015
  • [8] Prediction of particle deposition on to rough surfaces
    Reynolds, AM
    AGRICULTURAL AND FOREST METEOROLOGY, 2000, 104 (02) : 107 - 118
  • [9] A lattice Boltzmann simulation of coalescence-induced droplet jumping on superhydrophobic surfaces with randomly distributed structures
    Zhang, Li-Zhi
    Yuan, Wu-Zhi
    APPLIED SURFACE SCIENCE, 2018, 436 : 172 - 182
  • [10] Adhesive contact of randomly rough surfaces: experimental and numerical investigations
    Violano, G.
    Chateauminois, A.
    Afferrante, L.
    49TH ITALIAN ASSOCIATION FOR STRESS ANALYSIS CONFERENCE (AIAS 2020), 2021, 1038