HYBRID CONTINUOUS TIME-MONTE CARLO SIMULATION OF DISPERSE SYSTEMS

被引:0
|
作者
Lakatos, Bela G. [1 ]
Barkanyi, Agnes [1 ]
Nemeth, Sandor [1 ]
机构
[1] Univ Pannonia, Dept Proc Engn, H-8200 Veszprem, Hungary
来源
EUROPEAN SIMULATION AND MODELLING CONFERENCE 2013 | 2013年
关键词
Disperse system; Multidimensional population balance equation; Hybrid continuous time-Monte Carlo algorithm; Simulation; Suspension polymerization; Micro-mixing; POPULATION BALANCE-EQUATIONS; STOCHASTIC SIMULATION; COAGULATION; DISCRETIZATION; MODEL;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A hybrid continuous time-Monte Carlo method for solution of equations of a detailed population balance model is presented for two phase disperse systems perfectly mixed on macrolevel. The dispersed phase is described by a population balance equation including aggregation or coalescence and breakage of particles, as well as collision induced exchange of mass of species and heat between the particles. The resulted population balance equation is solved by coupling the deterministic continuous time computation of heat and mass balances and chemical reactions with the random discrete time events of particles population using Monte Carlo simulation. Applicability of the method is illustrated by simulation of a suspension polymerization reactor and a continuous stirred tank coalescence/redispersion reactor.
引用
收藏
页码:13 / 20
页数:8
相关论文
共 50 条
  • [1] Monte Carlo Simulation of γ→α Transformation during Continuous Cooling
    Fang, Zhao
    Yamaguchi, Tomiko
    Ikeda, Hideyuki
    Nishio, Kazumasa
    JOURNAL OF THE JAPAN INSTITUTE OF METALS, 2009, 73 (07) : 495 - 501
  • [2] Hybrid Monte Carlo with LAMMPS
    Guo, Jingxiang
    Haji-Akbari, Amir
    Palmer, Jeremy C.
    JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY, 2018, 17 (03)
  • [3] Monte Carlo Simulation of Bacterial Disinfection: Nonlinear and Time-Explicit Intensity of Transition
    Argoti, Andres
    Fan, L. T.
    Chou, S. T.
    BIOTECHNOLOGY PROGRESS, 2010, 26 (05) : 1486 - 1493
  • [4] Continuous-time Monte Carlo renormalization group
    Wu, Yantao
    Car, Roberto
    PHYSICAL REVIEW B, 2020, 102 (01)
  • [5] Monte Carlo Simulation of Coarse Grain Polymeric Systems
    Detcheverry, Francois A.
    Pike, Darin Q.
    Nealey, Paul F.
    Mueller, Marcus
    de Pablo, Juan J.
    PHYSICAL REVIEW LETTERS, 2009, 102 (19)
  • [6] Forecasting Cryptocurrency Investment Return Using Time Series and Monte Carlo Simulation
    Zornic, Nikola
    Markovic, Aleksandar
    Cavoski, Sava
    CENTRAL EUROPEAN CONFERENCE ON INFORMATION AND INTELLIGENT SYSTEMS (CECIIS 2018), 2018, : 153 - 160
  • [7] Fractional Monte Carlo time steps for the simulation of coagulation for parallelized flowsheet simulations
    Kotalczyk, G.
    Kruis, F. E.
    CHEMICAL ENGINEERING RESEARCH & DESIGN, 2018, 136 : 71 - 82
  • [8] Hybrid Auxiliary Field Quantum Monte Carlo for Molecular Systems
    Chen, Yixiao
    Zhang, Linfeng
    Weinan, E.
    Car, Roberto
    JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2023, 19 (14) : 4484 - 4493
  • [9] Conditional Monte Carlo With Intermediate Estimations for Simulation of Markovian Systems
    Cancela, Hector
    Murray, Leslie
    Rubino, Gerardo
    ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE, 2016, 321 : 3 - 21
  • [10] Parallel Monte Carlo Simulation of Aerosol Dynamics
    Zhou, Kun
    He, Zhu
    Xiao, Ming
    Zhang, Zhiquan
    ADVANCES IN MECHANICAL ENGINEERING, 2014,