An analytical solution of the population balance equation for simultaneous Brownian and shear coagulation in the continuum regime

2020 ◽  
Vol 31 (5) ◽  
pp. 2128-2135
Author(s):  
Kaiyuan Wang ◽  
Suyuan Yu ◽  
Wei Peng
2015 ◽  
Vol 80 ◽  
pp. 1-10 ◽  
Author(s):  
Mingzhou Yu ◽  
Xiaotong Zhang ◽  
Guodong Jin ◽  
Jianzhong Lin ◽  
Martin Seipenbusch

Particuology ◽  
2015 ◽  
Vol 18 ◽  
pp. 194-200 ◽  
Author(s):  
Mingzhou Yu ◽  
Jianzhong Lin ◽  
Junji Cao ◽  
Martin Seipenbusch

2016 ◽  
Vol 20 (3) ◽  
pp. 921-926 ◽  
Author(s):  
Mingliang Xie ◽  
Jin Li ◽  
Tingting Kong ◽  
Qing He

An improved moment model is proposed to solve the population balance equation for Brownian coagulation in the continuum-slip regime, and it reduces to a known one in open literature when the non-linear terms in the slip correction factor are ignored. The present model shows same asymptotic behavior as that in the continuum regime.


Author(s):  
Zehra Pınar ◽  
Abhishek Dutta ◽  
Mohammed Kassemi ◽  
Turgut Öziş

AbstractThis study presents a novel analytical solution for the Population Balance Equation (PBE) involving particulate aggregation and breakage by making use of the appropriate solution(s) of the associated complementary equation of a nonlinear PBE via Fibonacci and Lucas Approximation Method (FLAM). In a previously related study, travelling wave solutions of the complementary equation of the PBE using Auxiliary Equation Method (AEM) with sixth order nonlinearity was taken to be analogous to the description of the dynamic behavior of the particulate processes. However, in this study, the class of auxiliary equations is extended to Fibonacci and Lucas type equations with given transformations to solve the PBE. As a proof-of-concept for the novel approach, the general case when the number of particles varies with respect to time is chosen. Three cases i. e. balanced aggregation and breakage and when either aggregation or breakage can dominate are selected and solved for their corresponding analytical solution and compared with the available analytical approaches. The solution obtained using FLAM is found to be closer to the exact solution and requiring lesser parameters compared to the AEM and thereby being a more robust and reliable framework.


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