Mass Transfer in a Porous Particle – MCMC Assisted Parameter Estimation of Dynamic Model under Uncertainties

Timo Suominen, Teuvo Kilpiö, Tapio Salmi

    Research output: Contribution to journalArticleScientificpeer-review


    In this paper a method based on Markov Chain Monte Carlo simulations to estimate kinetic parameters for a chemical reaction within a porous particle is presented. It uses distributions for parameter values rather than a single value, like average particle values which are thought to be representative values for a large population of particles. The results show how the variance in parameters affect the time needed to reach steady-state operation and in extreme cases even the proportion of the catalytic material which does not participate in catalysis due to mass transfer limitations. This helps in recognizing possible process conditions for heterogeneously catalyzed reactions. The work illustrates how hard it is to identify single, representative parameter values for phenomena which include non-homogenous material properties.
    Original languageUndefined/Unknown
    Pages (from-to)277–282
    JournalComputer Aided Chemical Engineering
    Publication statusPublished - 2014
    MoE publication typeA1 Journal article-refereed


    • Markov chain Monte Carlo
    • parameter estimation
    • Mass transfer

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