A preliminary version of this work was presented at 9th International Symposium on Dynamics and Control of Process Systems held in Leuven, Brussels in July 2010.
Process Systems Engineering
Automatic differentiation-based quadrature method of moments for solving population balance equations†
Article first published online: 18 MAY 2011
DOI: 10.1002/aic.12613
Copyright © 2011 American Institute of Chemical Engineers (AIChE)
Additional Information
How to Cite
Kariwala, V., Cao, Y. and K. Nagy, Z. (2012), Automatic differentiation-based quadrature method of moments for solving population balance equations. AIChE J., 58: 842–854. doi: 10.1002/aic.12613
- †
Publication History
- Issue published online: 6 FEB 2012
- Article first published online: 18 MAY 2011
- Accepted manuscript online: 17 MAR 2011 12:32PM EST
- Manuscript Revised: 16 FEB 2011
- Manuscript Received: 14 SEP 2010
Funded by
- Royal Society, UK. Grant Number: IV0871568
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Keywords:
- automatic differentiation;
- dynamic simulation;
- particulate processes;
- population balance equations;
- quadrature method of moments
Abstract
The quadrature method of moments (QMOM) is a promising tool for the solution of population balance equations. QMOM requires solving differential algebraic equations (DAEs) consisting of ordinary differential equations related to the evolution of moments and nonlinear algebraic equations resulting from the quadrature approximation of moments. The available techniques for QMOM are computationally expensive and are able to solve for only a few moments due to numerical robustness deficiencies. In this article, the use of automatic differentiation (AD) is proposed for solution of DAEs arising in QMOM. In the proposed method, the variables of interest are approximated using high-order Taylor series. The use of AD and Taylor series gives rise to algebraic equations, which can be solved sequentially to obtain high-fidelity solution of the DAEs. Benchmark examples involving different mechanisms are used to demonstrate the superior accuracy, computational advantage, and robustness of AD-QMOM over the existing state-of-the-art technique, that is, DAE-QMOM. © 2011 American Institute of Chemical Engineers AIChE J, 2012

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