Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling
Abstract
The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes:more »
- Publication Date:
- Research Org.:
- Univ. of Memphis, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Fusion Energy Sciences (FES); USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF)
- OSTI Identifier:
- 1783173
- Alternate Identifier(s):
- OSTI ID: 1815098
- Grant/Contract Number:
- SC0021206; 1903432
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Aerosol Science
- Additional Journal Information:
- Journal Volume: 155; Journal ID: ISSN 0021-8502
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; Langevin dynamics; Collision rate constant; Trajectory simulations; Single particle mass transfer; Transition regime processes; Diffusional transport kinetics
Citation Formats
Suresh, Vikram, and Gopalakrishnan, Ranganathan. Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling. United States: N. p., 2021.
Web. doi:10.1016/j.jaerosci.2021.105746.
Suresh, Vikram, & Gopalakrishnan, Ranganathan. Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling. United States. https://doi.org/10.1016/j.jaerosci.2021.105746
Suresh, Vikram, and Gopalakrishnan, Ranganathan. Sun .
"Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling". United States. https://doi.org/10.1016/j.jaerosci.2021.105746. https://www.osti.gov/servlets/purl/1783173.
@article{osti_1783173,
title = {Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling},
author = {Suresh, Vikram and Gopalakrishnan, Ranganathan},
abstractNote = {The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.},
doi = {10.1016/j.jaerosci.2021.105746},
journal = {Journal of Aerosol Science},
number = ,
volume = 155,
place = {United States},
year = {Sun Feb 07 00:00:00 EST 2021},
month = {Sun Feb 07 00:00:00 EST 2021}
}
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