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On the fast modeling of species transport in fluidized beds using recurrence computational fluid dynamics
AIChE Journal ( IF 3.5 ) Pub Date : 2020-02-10 , DOI: 10.1002/aic.16931
Firas Dabbagh 1 , Stefan Pirker 2 , Simon Schneiderbauer 1, 2
Affiliation  

Due to variety of scale dynamics evolved in gas–solid flows, most of its numerical description is limited to expensive short durations. This has made the slow processes therein, such as the chemical species conversion, to be out of an appropriate reach. In this work, an application of the transport‐based recurrence computational fluid dynamics (CFD) has been introduced for the fast modeling of passive scalar transport, which is considered as species conversion and heat transfer in fluidized beds. The methodology discloses the recurrent dynamics during a short‐term full CFD simulation as Lagrangian shift operations upon which a passive scalar can infinitely be traced. Apart from convecting, a proper approach based on the turbulent kinetic energy of tracked dynamics is introduced for modeling the physical diffusion of the scalar transported. Our outcomes have revealed a subtle chasing to the full CFD species simulation with a speed‐up up to 1,600.

中文翻译:

基于递归计算流体动力学的流化床中物种迁移的快速建模

由于气体-固体流中演化出各种尺度动力学,其大部分数值描述仅限于昂贵的短时间。这使得其中的缓慢过程(例如化学物质转化)不在适当的范围内。在这项工作中,引入了基于运输的递归计算流体动力学(CFD)的应用,用于被动标量运输的快速建模,这被认为是流化床中的物质转化和传热。该方法公开了在短期完整CFD仿真过程中的循环动力学,作为拉格朗日平移操作,可以在其上无限次跟踪无源标量。除了对流之外,还引入了一种基于跟踪动力学的湍动能的适当方法,用于对所传输标量的物理扩散进行建模。
更新日期:2020-04-21
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