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首页> 外文期刊>International journal of nonlinear sciences and numerical simulation >On Time-Averaged CFD Modeling of Circulating Fluidized Beds
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On Time-Averaged CFD Modeling of Circulating Fluidized Beds

机译:循环流化床的时间平均CFD建模

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CFD simulations of single-phase flows are regularly performed as steady-state utilizing closure models of varying complexity. On the contrary, dense gas-solid flows are usually computed as time dependent. These simulations commonly require a small time step and a fine mesh resulting in costly and time-consuming computations. In case of large industrial circulating fluidized beds (CFB), the steady-state CFD modeling would be an attractive alternative for the transient simulations, if reliable closure models for the time-averaged transport equations were available. The multiphase closure models developed for time-dependent CFB computations are not as such applicable to the steady-state approach. For instance, the fraction of the momentum transfer expressed by the velocities is significantly smaller in the steady-state models than in the transient ones. Therefore, the steady-state simulations rely more on the closure relations and especially on the models for inter-phase momentum transfer and for the Reynolds stress terms. Several attempts to develop closure models for coarse-mesh and steady-state simulations have been presented in the literature. In this paper, a novel steady-state simulation approach for a CFB process and a corresponding CFD model are introduced. A successful steady-state simulation for a test case is presented. Compared to the time-dependent simulations, the computing time is reduced by a factor of an order of 1000.
机译:利用复杂度各异的闭合模型,通常以稳态执行单相流的CFD模拟。相反,稠密的气固流动通常被计算为时间依赖性。这些模拟通常需要较小的时间步长和精细的网格,从而导致成本高昂且耗时的计算。在大型工业循环流化床(CFB)的情况下,如果可获得用于时间平均传输方程的可靠封闭模型,则稳态CFD模型将是瞬态模拟的一种有吸引力的替代方法。为基于时间的CFB计算而开发的多相闭合模型不适用于稳态方法。例如,在稳态模型中,由速度表示的动量传递分数要比在瞬态模型中小得多。因此,稳态仿真更多地依赖于闭合关系,尤其是相间动量传递模型和雷诺应力项模型。在文献中已经提出了几种尝试来开发用于粗网格和稳态模拟的闭合模型。本文介绍了一种新颖的CFB过程稳态仿真方法和相应的CFD模型。提出了一个成功的测试用例的稳态仿真。与时间相关的仿真相比,计算时间减少了约1000倍。

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