An assessment of low-order methods for solving the breakage equation

The population balance is a necessary vehicle for modeling processes that involve size reduction due to fragmentation (grinding) of solid particles. The online control and optimization of such processes require efficient algorithms for the numerical solution of the breakage equation. However, the plethora of available methods, relying on discretization of the integrodifferential breakage equation, is characterized by computational inefficiency in tackling complicated spatially dependent problems. For such cases, the method of moments, which transforms the continuous breakage equation to one with a few degrees of freedom, seems to be advantageous. The accuracy of several versions of the method of moments is examined in the present work by comparing them with analytical solutions of the breakage equation for typical cases. The results of this work allow the selection of the best method for a particular problem and the a priori estimation of the error associated with the use of a specific method. Finally, by revealing the weaknesses of the existing methods, the present results set the basis for pursuing improvements.

[1]  Robert M. Ziff,et al.  New solutions to the fragmentation equation , 1991 .

[2]  P. C. Kapur,et al.  Self-preserving size spectra of comminuted particles , 1972 .

[3]  K. W. Lee,et al.  Conservation of particle size distribution parameters during Brownian coagulation , 1985 .

[4]  Kangtaek Lee,et al.  Simultaneous coagulation and break-up using constant-N Monte Carlo , 2000 .

[5]  R. C. Everson,et al.  Spline method for solving continuous batch grinding and similarity equations , 1997 .

[6]  D. Ramkrishna,et al.  On the solution of population balance equations by discretization—II. A moving pivot technique , 1996 .

[7]  J. C. Barrett,et al.  Improving the accuracy of the moments method for solving the aerosol general dynamic equation , 1996 .

[8]  Friedrich Srienc,et al.  Solutions of population balance models based on a successive generations approach , 1997 .

[9]  Doraiswami Ramkrishna Drop-breakage in agitated liquid—liquid dispersions , 1974 .

[10]  William H. Press,et al.  Numerical recipes , 1990 .

[11]  S. Katz,et al.  Some problems in particle technology: A statistical mechanical formulation , 1964 .

[12]  N. Amundson,et al.  Breakage and Coalescence in Dispersed Phase Systems , 1966 .

[13]  D. Ramkrishna,et al.  Solution of inverse problems in population balances. II: Particle break-up , 1995 .

[14]  T. Tsang,et al.  Comparison of Different Numerical Schemes for Condensational Growth of Aerosols , 1988 .

[15]  Ka Ming Ng,et al.  Statistics of multiple particle breakage , 1996 .

[16]  Steven G. Thoma,et al.  Ultrasonic fragmentation of agglomerate powders , 1993 .

[17]  Noncommutative torus from Fibonacci chains via foliation , 2000, math-ph/0008028.

[18]  Thomas W. Peterson,et al.  Similarity Solutions for the Population Balance Equation Describing Particle Fragmentation , 1986 .

[19]  Jian-Ming Jin,et al.  Computation of special functions , 1996 .

[20]  R. Botet,et al.  A simple soluble model of discrete sequential fragmentation , 1996 .

[21]  R. Ziff,et al.  "Shattering" transition in fragmentation. , 1987, Physical review letters.

[22]  K. Shinohara,et al.  Fine-grinding characteristics of hard materials by attrition mill , 1999 .

[23]  On the breakage problem with a homogeneous erosion type kernel , 2001 .

[24]  C. Frances,et al.  Fine wet grinding of an alumina hydrate in a ball mill , 1998 .

[26]  John A. Dodds,et al.  Prediction of the product size distribution in associations of stirred bead mills , 1998 .

[27]  Kazunori Sato,et al.  Breakage of coals in ring-roller mills Part I. The breakage properties of various coals and simulation model to predict steady-state mill performance , 1996 .

[28]  Marco Vanni Discretization procedure for the breakage equation , 1999 .

[29]  J. C. Barrett,et al.  A comparison of some approximate methods for solving the aerosol general dynamic equation , 1998 .

[30]  Tibor Blickle,et al.  A simulation model for analysis and design of continuous grinding mills , 1998 .

[31]  A. Karabelas,et al.  On the attainment of steady state in turbulent pipe flow of dilute dispersions , 1998 .

[32]  Robert McGraw,et al.  Description of Aerosol Dynamics by the Quadrature Method of Moments , 1997 .

[33]  M. Lensu CORRELATIONS BETWEEN FRAGMENT SIZES IN SEQUENTIAL FRAGMENTATION , 1997 .

[34]  Anastasios J. Karabelas Particle attrition in shear flow of concentrated slurries , 1976 .

[35]  Benjamin J. McCoy,et al.  Time evolution to similarity solutions for polymer degradation , 1998 .

[36]  Ka Ming Ng,et al.  New discretization procedure for the breakage equation , 1995 .

[37]  Ville Alopaeus,et al.  Simulation of the population balances for liquid-liquid systems in a nonideal stirred tank. Part 1: Description and qualitative validation of the model , 1999 .

[38]  Robert M. Ziff,et al.  Kinetics of polymer degradation , 1986 .

[39]  K. J. Reid A solution to the batch grinding equation , 1965 .

[40]  M. Kostoglou Mathematical analysis of polymer degradation with chain-end scission , 2000 .

[41]  Kazunori Sato,et al.  Breakage of coals in ring-roller mills Part 2. An unsteady-state simulation model , 1998 .

[42]  R. Treat ON THE SIMILARITY SOLUTION OF THE FRAGMENTATION EQUATION , 1997 .

[43]  On the modified gamma distribution for representing the size spectra of coagulating aerosol particles , 1985 .

[44]  Bijay K. Mishra Monte Carlo simulation of particle breakage process during grinding , 2000 .