Widespread use of microwave technology requires quantitative scale-up models. Currently, microwave models are typical qualitative in nature. This work focuses on rendering models quantitative and elucidating the scale-up behavior of microwave heating using numerical simulations. A commonly used bench-scale microwave reactor from the CEM Corp. (CEM Discover SP) is used for benchmarking. To enable quantitative modeling, microwave heating experiments are conducted and compared to COMSOL calculations to develop a calibration curve for the set point vs the actually delivered microwave power. Using the validated computational model, microwave-heating of various liquids in a wide range of vial sizes is investigated. The computational study shows that during the scale-up, the volumetric power absorbed passes through a maximum, whereas the energy efficiency and heating uniformity exhibit strongly nonlinear behavior. This work introduces a method for quantitative microwave models and insights into the scale-up of commercial microwave reactors.
Selective heating of different phases of multiphase systems via microwaves can result in energy savings and suppression of side reactions. However, materials properties and operating conditions that maximize temperature gradients are poorly understood. Here we utilize computational fluid dynamics (CFD) computations and temperature measurements in structured flow reactors (monoliths) in a monomodal microwave cavity to assess the temperature difference between the walls and the fluid and develop a simple lumped model to estimate when temperature gradients exist. We also explore the material's thermal and electrical properties of structured reactors for isothermal catalyst conditions. We propose that CFD simulations can be used as a nonintrusive, predictive tool of temperature homogeneity. Importantly, we demonstrate that localized heating in the bed under several conditions rather than selective heating is responsible for the selectivity enhancement. Our results indicate that structured beds made of high thermal conductivity materials avoid arcing and enable temperature homogeneity and low electrical conductivity materials allow microwaves to penetrate the domain.
Computational
fluid dynamics (CFD) tools are increasingly gaining
importance to obtain detailed insight into biomass gasification. A
major shortcoming of the current CFD tools to study biomass gasification
is the lack of computationally affordable chemical kinetic models,
which allows detailed predictions of the yield and composition of
various gas and tar species in complex reactor configurations. In
this work, a detailed mechanism is assembled from the literature and
reduced to a compact model describing the gas-phase reactions of biomass
gasification in the absence of oxygen. The reduction procedure uses
a graph-based method for unimportant kinetic pathways elimination
and quasi-steady-state species selection. The resulting reduced model
contains 39 gas species and 118 reactions and is validated against
the detailed model and two experimental configurations: the pyrolysis
of volatile species, such as levoglucosan, in a tubular reactor, and
the fast pyrolysis of biomass particles in a drop tube reactor. The
reduced model predicts the evolution of major gas products (e.g.,
CO, CO2, CH4, H2) and various classes
of tar (e.g., single-ring aromatics, oxygenated aromatics, PAHs) produced
during biomass gasification. The capability of the reduced model to
adequately capture the chemical process in a complex reactor geometry
at an acceptable computational cost is demonstrated by employing it
in a simulation of a pseudo two-dimensional laboratory-scale fluidized
bed reactor.
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