Numerical Solution of Batch Crystallization Models

被引:0
|
作者
Qamar, S. [1 ]
Seidel-Morgenstern, A. [1 ]
机构
[1] Max Planck Inst Dynam Complex Tech Syst, D-39106 Magdeburg, Germany
关键词
Batch crystallization; nucleation and growth; fines dissolution; time-delay; method of characteristics; Duhamel's principle;
D O I
暂无
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
An efficient and accurate numerical technique is introduced for the simulation of a batch crystallizer equipped with a fines dissolution unit incorporating a time-delay. The dissolution of small crystals (fines dissolution) improves the product quality and facilitates the downstream processes. The proposed method follows two steps. In the first step, a coupled system of ordinary differential equations (ODEs) for moments and solute mass is numerically solved in the time domain of interest, giving the discrete values of growth and nucleation rates. In the second step, theses discrete values are used along with the initial crystal size distribution (CSD) to construct the final CSD. The method of characteristics and Duhamel's principle are employed for deriving an expression for CSD from the given population balance model (PBM). An alternative quadrature method of moments (QMOM) is introduced for approximating integrals in the ODE system of moments and mass balance. In this technique, orthogonal polynomials, obtained from the lower order moments, are used to find the quadrature abscissas and weights. The numerical results of our scheme are validated against the results of high resolution finite volume scheme results. Our scheme was found to be efficient, accurate, and free from numerical dissipation and dispersion.
引用
收藏
页码:745 / 750
页数:6
相关论文
共 50 条
  • [21] SIMULATION OF BATCH CRYSTALLIZATION
    MELIKHOV, IV
    BERLINER, LB
    [J]. CHEMICAL ENGINEERING SCIENCE, 1981, 36 (06) : 1021 - 1034
  • [22] OPTIMIZE BATCH CRYSTALLIZATION
    MOORE, WP
    [J]. CHEMICAL ENGINEERING PROGRESS, 1994, 90 (09) : 73 - 79
  • [23] Quantitative identification of nucleation and crystal growth stages in batch crystallization from solution
    Huang, P
    Huang, DC
    Xu, NP
    Shi, J
    [J]. CHEMICAL JOURNAL OF CHINESE UNIVERSITIES-CHINESE, 2004, 25 (03): : 504 - 508
  • [24] Parallel Solution of Robust Nonlinear Model Predictive Control Problems in Batch Crystallization
    Cao, Yankai
    Kang, Jia
    Nagy, Zoltan K.
    Laird, Carl D.
    [J]. PROCESSES, 2016, 4 (03)
  • [25] General systems modeling of multi-phase batch crystallization from solution
    Borissova, Antonia
    [J]. CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION, 2009, 48 (01) : 268 - 278
  • [26] Numerical solutions of population balance models in preferential crystallization
    Qamar, S.
    Ashfaq, A.
    Angelov, I.
    Elsner, M. P.
    Warnecke, G.
    Seidel-Morgenstern, A.
    [J]. CHEMICAL ENGINEERING SCIENCE, 2008, 63 (05) : 1342 - 1352
  • [27] NUMERICAL SOLUTION OF NONLINEAR PLANNING MODELS
    KENDRICK, D
    TAYLOR, L
    [J]. ECONOMETRICA, 1970, 38 (03) : 453 - +
  • [28] Numerical Solution of Dynamic Quantile Models *
    de Castro, Luciano
    Galvao, Antonio F.
    Muchon, Andre
    [J]. JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2023, 148
  • [29] Numerical Solution of Cloud Servicing Models
    Georgiev, Vasil
    [J]. 2014 INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCES AND IN INDUSTRY (MCSI 2014), 2014, : 22 - 26
  • [30] Numerical solution of random differential models
    Cortes, J. -C.
    Jodar, L.
    Villafuerte, L.
    Company, R.
    [J]. MATHEMATICAL AND COMPUTER MODELLING, 2011, 54 (7-8) : 1846 - 1851