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Balance Modeling (balance + modeling)

Distribution by Scientific Domains
Chemistry40%

Kinds of Balance Modeling

  • population balance modeling
    		•

    Selected Abstracts

    Coupled Single-Particle and Population Balance Modeling for Particle Size Distribution of Poly(propylene) Produced in Loop Reactors

    MACROMOLECULAR REACTION ENGINEERING, Issue 2 2010
    Zheng-Hong Luo
    Abstract A comprehensive model was developed for the PSD of PP produced in loop reactors. The polymeric multilayer model (PMLM) was first applied to calculate the single particle growth rate under intraparticle transfer limitations. In order to obtain the comprehensive model, the PMLM was solved together with a steady-state particle population equation to predict the PSD in the loop reactors. The simulated PSD data obtained under steady-state polymerization conditions agreed with the actual data collected from industrial scale plant. The comprehensive model was also used to predict the effects of some critical factors, including the intraparticle mass and heat transfer limitations, the feed catalyst particle size and the catalyst deactivation, etc., on the PSD. [source]

    A Simpler Approach to Population Balance Modeling in Predicting the Performance of Ziegler-Natta Catalyzed Gas-Phase Olefin Polymerization Reactor Systems

    MACROMOLECULAR REACTION ENGINEERING, Issue 2-3 2009
    Randhir Rawatlal
    Abstract In this work, an alternative formulation of the Population Balance Model (PBM) is proposed to simplify the mathematical structure of the reactor model. The method is based on the segregation approach applied to the recently developed unsteady state residence time distribution (RTD). It is shown that the model can predict the performance of a reactor system under unsteady flow and composition conditions. Case studies involving time-varying catalyst flowrates, reactor temperature and reactor pressure were simulated and found to predict reactor performance with reasonable accuracy. The model was used to propose a grade transition strategy that could reduce transition time by as much as two hours. [source]

    Population balance modeling of particle size distribution in monomer-starved semibatch emulsion polymerization

    AICHE JOURNAL, Issue 12 2009
    Shahriar Sajjadi
    Abstract The evolution of particle size distribution (PSD) in the monomer-starved semibatch emulsion polymerization of styrene with a neat monomer feed is investigated using a population balance model. The system under study ranges from conventional batch emulsion to semicontinuous (micro)emulsion polymerization depending on the rate of monomer addition. It is shown that, contrary to what is often believed, the broadness of PSD is not necessarily associated with the length of nucleation period. The PSDs at the end of nucleation are found to be independent of surfactant concentration. Simulation results indicate that at the completion of nucleation the particle size is reduced and the PSD narrows with decreasing rate of monomer addition despite nucleation time increasing. The broad distribution of particles frequently encountered in semibatch emulsion polymerizations is therefore attributed to stochastic broadening during the growth stage. The zero-one-two-three model developed in this article allows perceiving that the dominant kinetic mechanism may be different for particles with different sizes. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source]

    Population balance modeling of aggregation kinetics of recombinant human interleukin-1 receptor antagonist

    JOURNAL OF PHARMACEUTICAL SCIENCES, Issue 12 2005
    Eva Y. Chi
    Abstract The kinetics of benzyl alcohol-induced nonnative aggregation of recombinant human interleukin-1 receptor antagonist (rhIL-1ra) were investigated using a population balance model. Steady-state size distributions of rhIL-1ra aggregates formed in a continuous mixed suspension, mixed product removal (MSMPR) reactor were measured and used to extrapolate aggregate nucleation and growth rates parameters. Aggregate growth rate was size-dependent and a linear growth rate model was used to derive a population density function. Addition of 0.9 wt/v% benzyl alcohol increased the nucleation rate by approximately four orders of magnitude. The growth rate for aggregates, however, changed little as a function of benzyl alcohol concentration in the range of 0,0.9%. The addition of sucrose to buffer containing 0.9% benzyl alcohol decreased rhIL1-ra nucleation rate by orders of magnitude and had little impact on growth rate kinetics. The simplicity of the population balance model and the physical relevance of the information obtained from this model render it a useful tool to study protein aggregation kinetics and the effects of excipients on this process. © 2005 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 94:2735,2748, 2005 [source]

    Population balance modeling of the conidial aggregation of Aspergillus niger

    BIOTECHNOLOGY & BIOENGINEERING, Issue 2 2008
    P.-J. Lin
    Abstract Numerous biotechnological production processes are based on the submerse cultivation of filamentous fungi. Process design, however, is often hampered by the complex growth pattern of these organisms. In the morphologic development of coagulating filamentous fungi, like Aspergillus niger, conidial aggregation is the first step of filamentous morphogenesis. For a proper description of this phenomenon it is necessary to characterize conidial populations. Kinetic studies performed with an in-line particle size analyzer suggested that two distinct aggregation steps have to be considered. The first step of conidial aggregation starts immediately after inoculation. Both the rate constants of formation and disintegration of aggregates have been determined by measuring the concentration of conidia at the beginning of the cultivation and the concentration of particles at steady state during the first hours of cultivation. In contrast to the first aggregation step, where the collision of conidia is presumed to be responsible for the process, the second aggregation step is thought to be initiated by germination of conidia. Growing hyphae provide additional surface for the attachment of non- germinated conidia, which leads to a strong decrease in particle concentration. The specific hyphal length growth rate and the ratio of particle concentration to the growing adhesion hyphal surface are decisive matters of the second aggregation step. Both aggregation steps can be described by population dynamics and simulated using the program package PARSIVAL (PARticle SIze eVALution) for the treatment of general particle population balances. Biotechnol. Bioeng. 2008;99: 341,350. © 2007 Wiley Periodicals, Inc. [source]