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Modeling of Particle Concentration Distribution in a Fluidized Bed by Means of the Theory of Markov Chains

机译:基于马尔可夫链理论的流化床颗粒浓度分布模型

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A one-dimensional mathematical model of particulate solids fluidization based on the theory of Markov chains is proposed. Transition probabilities that form the matrix and control the migration of particles over the bed are subdivided into two types, convection and diffusion. The convection transition probabilities depend on the local particle concentration in cells of the chain and mainly define the bed expansion at certain hydrodynamic conditions. The diffusion transition probabilities form particle concentration distribution over the bed height. On the basis of the model, the heat exchange between gas and particulate solids is described. The batch fluidization model is generalized to the case of continuous fluidization that allows predicting a connection between throughput and hold-up, as well as particle residence time distribution in a bed. Some aspects of the approach are verified experimentally.
机译:提出了一种基于马尔可夫链理论的一维固体颗粒流化数学模型。形成矩阵并控制粒子在床上移动的跃迁几率可分为对流和扩散两种。对流转变概率取决于链中孔中的局部颗粒浓度,并且主要定义了在某些流体动力学条件下的床层膨胀。扩散转变概率形成床层高度上的颗粒浓度分布。基于该模型,描述了气体与固体颗粒之间的热交换。批料流化模型一般适用于连续流化的情况,这种情况可以预测产量和滞留量之间的联系以及颗粒在床中的停留时间分布。该方法的某些方面已通过实验验证。

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