A new framework for numerical modeling of population balance equations: Solving for the inverse cumulative distribution function

被引:5
作者
Peterson, Joseph D. [1 ]
Bagkeris, Ioannis [2 ]
Michael, Vipin [3 ]
机构
[1] Univ Cambridge, Ctr Math Sci, DAMTP, Wilberforce Rd, Cambridge CB3 0WA, England
[2] Unilever R&D, Port Sunlight Lab, Quarry Rd East, Bebington CH63 3JW, England
[3] Univ Manchester, Dept Mech Aerospace & Civil Engn, Manchester M139PL, England
关键词
Population Balance Equations; Numerical Analysis; Convergence; Emulsions; Analytic Methods; Moments; LOW-ORDER METHODS; QUADRATURE METHOD; BREAKAGE; MOMENTS; AGGREGATION; DISCRETIZATION; EMULSIONS;
D O I
10.1016/j.ces.2022.117781
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Population balance equations (PBE) are a class of integro-partial differential equations with applications spanning a broad range of engineering disciplines. When the state of a population (e.g. droplet size distribution) dictates the mechanical properties of its transporting fluid, modeling tools for solving PBEs must provide good accuracy at very low computational cost. The quadrature method of moments scheme (QMOM) is a popular numerical strategy for many applications, but it has a number of significant weaknesses including the possibility of converging to an incorrect solution. Motivated by limitations of QMOM, this paper introduces a new numerical framework, miCDF, in which standard PBE equations are transformed to solve for the inverse cumulative distribution function. This transformation is straightforward, making use of the triple product rule, and it can be implemented using simple finite difference methods. Through sample calculations, we discuss the advantages and limitations of miCDF relative to QMOM. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
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页数:15
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