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Title: Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models

Abstract

Stochastic particle-resolved methods have proven useful for simulating multi-dimensional systems such as composition-resolved aerosol size distributions. While particle-resolved methods have substantial benefits for highly detailed simulations, these techniques suffer from high computational cost, motivating efforts to improve their algorithmic efficiency. Here we formulate an algorithm for accelerating particle removal processes by aggregating particles of similar size into bins. We present the Binned Algorithm for particle removal processes and analyze its performance with application to the atmospherically relevant process of aerosol dry deposition. We show that the Binned Algorithm can dramatically improve the efficiency of particle removals, particularly for low removal rates, and that computational cost is reduced without introducing additional error. In simulations of aerosol particle removal by dry deposition in atmospherically relevant conditions, we demonstrate about 50-times increase in algorithm efficiency.

Authors:
 [1];  [2];  [1];  [2];  [3]
  1. Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, 105 S. Gregory St., Urbana, IL 61801 (United States)
  2. Department of Computer Science, University of Illinois at Urbana–Champaign, 201 North Goodwin Avenue, Urbana, IL 61801 (United States)
  3. Department of Mechanical Science and Engineering, University of Illinois at Urbana–Champaign, 1206 W. Green St., Urbana, IL 61801 (United States)
Publication Date:
OSTI Identifier:
22572359
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Computational Physics; Journal Volume: 322; Other Information: Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; AEROSOLS; ALGORITHMS; DEPOSITION; EFFICIENCY; ERRORS; PARTICLES; SIMULATION; STOCHASTIC PROCESSES

Citation Formats

Curtis, J.H., Michelotti, M.D., Riemer, N., Heath, M.T., and West, M., E-mail: mwest@illinois.edu. Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models. United States: N. p., 2016. Web. doi:10.1016/J.JCP.2016.06.029.
Curtis, J.H., Michelotti, M.D., Riemer, N., Heath, M.T., & West, M., E-mail: mwest@illinois.edu. Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models. United States. doi:10.1016/J.JCP.2016.06.029.
Curtis, J.H., Michelotti, M.D., Riemer, N., Heath, M.T., and West, M., E-mail: mwest@illinois.edu. Sat . "Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models". United States. doi:10.1016/J.JCP.2016.06.029.
@article{osti_22572359,
title = {Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models},
author = {Curtis, J.H. and Michelotti, M.D. and Riemer, N. and Heath, M.T. and West, M., E-mail: mwest@illinois.edu},
abstractNote = {Stochastic particle-resolved methods have proven useful for simulating multi-dimensional systems such as composition-resolved aerosol size distributions. While particle-resolved methods have substantial benefits for highly detailed simulations, these techniques suffer from high computational cost, motivating efforts to improve their algorithmic efficiency. Here we formulate an algorithm for accelerating particle removal processes by aggregating particles of similar size into bins. We present the Binned Algorithm for particle removal processes and analyze its performance with application to the atmospherically relevant process of aerosol dry deposition. We show that the Binned Algorithm can dramatically improve the efficiency of particle removals, particularly for low removal rates, and that computational cost is reduced without introducing additional error. In simulations of aerosol particle removal by dry deposition in atmospherically relevant conditions, we demonstrate about 50-times increase in algorithm efficiency.},
doi = {10.1016/J.JCP.2016.06.029},
journal = {Journal of Computational Physics},
number = ,
volume = 322,
place = {United States},
year = {Sat Oct 01 00:00:00 EDT 2016},
month = {Sat Oct 01 00:00:00 EDT 2016}
}