Articles online

Direct Simulation Monte Carlo Method for Acoustic Agglomeration under Standing Wave Condition

Category: Control Techniques and Strategy

Volume: 17 | Issue: 4 | Pages: 1073-1083
DOI: 10.4209/aaqr.2016.07.0322
PDF | RIS | BibTeX

Fengxian Fan 1,2, Mingjun Zhang1,2, Zhengbiao Peng3, Jun Chen1,2, Mingxu Su1,2, Behdad Moghtaderi3, Elham Doroodchi3

  • 1 School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 2 Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 3 Discipline of Chemical Engineering, School of Engineering, The University of Newcastle, NSW 2308, Australia


Acoustic agglomeration of PM2.5 in the standing wave acoustic field is modeled.
The effects of mutual radiation pressure and acoustic wake are taken into account.
The DSMC method reveals “orthokinetic drift” in particle agglomeration.
The DSMC method predicts the detailed evolution of particle size distribution.
The simulations provide the influence of key parameters on acoustic agglomeration.


Acoustic agglomeration proves promising for preconditioning fine particles (i.e., PM2.5) as it significantly improves the efficiency of conventional particulate removal devices. However, a good understanding of the mechanisms underlying the acoustic agglomeration in the standing wave is largely lacking. In this study, a model that accounts for all of the important particle interactions, e.g., orthokinetic interaction, gravity sedimentation, Brownian diffusion, mutual radiation pressure effect and acoustic wake effect, is developed to investigate the acoustic agglomeration dynamics of PM2.5 in the standing wave based on the framework of direct simulation Monte Carlo (DSMC) method. The results show that the combination of orthokinetic interaction and gravity sedimentation dominates the acoustic agglomeration process. Compared with Brownian diffusion and the mutual radiation pressure effect, the acoustic wake plays a relatively more important role in governing the particle agglomeration. The phenomenon of particle agglomeration becomes more pronounced when the acoustic frequency and intensity are increased. The model is shown to be capable of accurately predicting the dynamic acoustic agglomeration process in terms of the detailed evolution of particle size and spatial distribution, which in turn allows for the visualization of important features such as “orthokinetic drift”. The prediction results are in good agreement with the experimental data.


Fine particles (PM2.5) Acoustic agglomeration Standing wave Direct simulation Monte Carlo (DSMC) method Numerical simulation

Related Article

Impacts of Upstream Building Height and Stack Location on Pollutant Dispersion from a Rooftop Stack

Yuan-Dong Huang , Ye Song, Xuan Xu, Wen-Rong He, Chang-Nyung Kim
Volume: 17 | Issue: 7 | Pages: 1837-1855
DOI: 10.4209/aaqr.2016.04.0151

Performance Evaluation of the WRF-Chem Model with Different Physical Parameterization Schemes during an Extremely High PM2.5 Pollution Episode in Beijing

Dongsheng Chen , Xin Xie, Ying Zhou, Jianlei Lang, Tingting Xu, Nan Yang, Yuehua Zhao, Xiangxue Liu
Volume: 17 | Issue: 1 | Pages: 262-277
DOI: 10.4209/aaqr.2015.10.0610

Improved Photocatalytic Air Cleaner with Decomposition of Aldehyde and Aerosol-Associated Influenza Virus Infectivity in Indoor Air

Kimiyasu Shiraki , Hiroshi Yamada, Yoshihiro Yoshida, Ayumu Ohno, Teruo Watanabe, Takafumi Watanabe, Hiroyuki Watanabe, Hidemitsu Watanabe, Masao Yamaguchi, Fumio Tokuoka, Shigeatsu Hashimoto, Masakazu Kawamura, Norihisa Adachi
Volume: 17 | Issue: 11 | Pages: 2901-2912
DOI: 10.4209/aaqr.2017.06.0220

High Selectivity of Visible-Light-Driven La-doped TiO2 Photocatalysts for NO Removal

Yu Huang, Jun-Ji Cao, Fei Kang, Sheng-Jie You, Chia-Wei Chang, Ya-Fen Wang
Volume: 17 | Issue: 10 | Pages: 2555-2565
DOI: 10.4209/aaqr.2017.08.0282