2 research outputs found

    Equivalent Reactor Network Model for the Modeling of Fluid Catalytic Cracking Riser Reactor

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    Modeling description of riser reactors is a highly interesting issue in design and development of fluid catalytic cracking (FCC) processes. However, one of the challenging problems in the modeling of FCC riser reactors is that sophisticated flow-reaction models with high accuracy require time-consuming computation, while simple flow-reaction models with fast computation result in low-accuracy predictions. This dilemma requires new types of coupled flow-reaction models, which should own time-efficient computation and acceptable model accuracy. In this investigation, an Equivalent Reactor Network (ERN) model was developed for a pilot FCC riser reactor. The construction procedure of the ERN model contains two main steps: hydrodynamic simulations under reactive condition and determination of the equivalent reactor network structure. Numerical results demonstrate that with the ERN model the predicted averaged error of the product yields at the riser outlet is 4.69% and the computation time is ∼5 s. Contrast to the ERN model, the predicted error with the plug-flow model is almost three times larger (12.79%), and the computational time of the CFD model is 0.1 million times longer (6.7 days). The superiority of the novel ERN model can be ascribed to its reasonably simplifying transport process and avoiding calculation divergences in most CFD models, as well as taking the back-mixing behavior in the riser into consideration where the plug-flow model does not do so. In summary, the findings indicate the capabilities of the ERN model in modeling description of FCC riser reactors and the possibilities of the model being applied to studies on the dynamic simulation, optimization, and control of FCC units in the future

    Novel Approach to Characterizing the Flow Regime and Fluid Dynamics in a Gas–Solid Fluidized Bed Based on Complex Network Theory

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    Understanding complex two-phase flow in gas–solid fluidization is crucial to the optimal design, rational scale-up, steady operation, and real-time control of a fluidized bed reactor. In this work, a novel approach based on the complex network theory is developed to characterize the flow regime transition and nonlinear fluid dynamics in a gas–solid fluidized bed. The constructed flow regime complex network (FRCN) consists of 56 nodes, with each featured by 14 quantities that are extracted from the simultaneous time-domain, frequency-domain, and state-space analyses on the in-bed pressure time series. Using the FRCN, various flow regimes in the gas–solid bed are recognized, with an accuracy of 98.2%. Besides, the constructed fluid dynamic complex networks present a scale-free characteristic of a degree distribution. The variation of the scale-free index is consistent with the complexity of the flow dynamics. Thus, it can be used as a descriptor to depict nonlinear fluid dynamics and flow regime evolution in gas–solid fluidization
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