Article: Accuracy control in Monte Carlo simulations of particle breakage Journal: International Journal of Modelling, Identification and Control (IJMIC) 2019 Vol.31 No.3 pp.278 - 291 Abstract: Monte Carlo (MC) methods are an important tool for the numerical solution of the population balance equation, allowing the optimisation and control of particulate processes on laboratory or plant scales. We investigate in this work a family of MC methods for particle breakage proposed by Kotalczyk et al. (2017, pp.417-429). The authors reported that specific breakage schemes (defined by a combination factor <i>R</i>) allow rendering the full particle size distribution. They also showed that specific ranges of the combination factor <i>R</i> might lead to severe systematic errors, but did not investigate measures of control or prevention. In this paper, a strategy which allows estimating the magnitude of the systematic error from the simulation data is presented. It is also shown how the simulation parameters can be set in order to keep the systematic error at an acceptable level. Inderscience Publishers - linking academia, business and industry through research

Title: Accuracy control in Monte Carlo simulations of particle breakage

Authors: Jherna Devi; Gregor Kotalczyk; Frank Einar Kruis

Addresses: Institute of Technology for Nanostructures (NST); Centre for Nanointegration Duisburg – Essen (CENIDE), University Duisburg-Essen, Duisburg, D-47057, Germany; Department of Information Technology, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Sindh 67480, Pakistan ' Institute of Technology for Nanostructures (NST); Centre for Nanointegration Duisburg – Essen (CENIDE), University Duisburg-Essen, Duisburg, D-47057, Germany ' Institute of Technology for Nanostructures (NST); Centre for Nanointegration Duisburg – Essen (CENIDE), University Duisburg-Essen, Duisburg, D-47057, Germany

Abstract: Monte Carlo (MC) methods are an important tool for the numerical solution of the population balance equation, allowing the optimisation and control of particulate processes on laboratory or plant scales. We investigate in this work a family of MC methods for particle breakage proposed by Kotalczyk et al. (2017, pp.417-429). The authors reported that specific breakage schemes (defined by a combination factor R) allow rendering the full particle size distribution. They also showed that specific ranges of the combination factor R might lead to severe systematic errors, but did not investigate measures of control or prevention. In this paper, a strategy which allows estimating the magnitude of the systematic error from the simulation data is presented. It is also shown how the simulation parameters can be set in order to keep the systematic error at an acceptable level.

Keywords: Monte Carlo; population balance; weighted particles; simulation; GPU; breakage; optimisation; control.

DOI: 10.1504/IJMIC.2019.098774

International Journal of Modelling, Identification and Control, 2019 Vol.31 No.3, pp.278 - 291

Received: 06 Jul 2017
Accepted: 07 Mar 2018
Published online: 02 Apr 2019 *

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Title: Accuracy control in Monte Carlo simulations of particle breakage

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