2 research outputs found
Equivalent Reactor Network Model for the Modeling of Fluid Catalytic Cracking Riser Reactor
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
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