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2020
DOI: 10.1002/aic.16931
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On the fast modeling of species transport in fluidized beds using recurrence computational fluid dynamics

Abstract: 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 methodolo… Show more

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Cited by 8 publications
(18 citation statements)
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“…Similarly to our recent work in Dabbagh et al, 33 the short‐term non‐reactive simulation (here using the cgTFM), is employed to investigate, a priori the recurrence properties of the system. Namely, the recurrence time step Δ t rec is decided basing on the pseudo‐periodicity of the system (bubbles evolution) at which the flow can almost be repeated.…”
Section: Transport‐based Recurrence Cfd Algorithmmentioning
confidence: 99%
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“…Similarly to our recent work in Dabbagh et al, 33 the short‐term non‐reactive simulation (here using the cgTFM), is employed to investigate, a priori the recurrence properties of the system. Namely, the recurrence time step Δ t rec is decided basing on the pseudo‐periodicity of the system (bubbles evolution) at which the flow can almost be repeated.…”
Section: Transport‐based Recurrence Cfd Algorithmmentioning
confidence: 99%
“…Namely, the recurrence time step Δ t rec is decided basing on the pseudo‐periodicity of the system (bubbles evolution) at which the flow can almost be repeated. Following the time histories of active fields such as, ɛ¯s and bold-italicu¯s, taken inside the bed at the probe { T 0 } (see Figure 1a), and shown in Figure 2a, the proper determination of Δ t rec reads 0.03 s (≡ 60Δ t ), with, 33 normalΔtrec〈〉φ2〈〉trueφ˙2,0.60emwhere0.60emtrueφ˙()t=false‖φ()t+normalΔtφ()tfalse‖normalΔt. …”
Section: Transport‐based Recurrence Cfd Algorithmmentioning
confidence: 99%
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“…[ 15 ] Further details with regard to the modeling of physical diffusion are given in the literature. [ 18,19 ] At this place, we therefore just present the main modeling features and abstain from a detailed description of the rCFD methodology.…”
Section: Modeling: Rcfd Simulationmentioning
confidence: 99%
“…Although rCFD is still in development, different versions of rCFD have already been applied successfully to turbulent single‐phase flow, [ 15–18 ] bubble columns, [ 12 ] and fluidized beds. [ 14,19,20,21 ]…”
Section: Introductionmentioning
confidence: 99%