References of "Qi, Fenglei 50027079"
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See detailA DEM approach for modeling biomass fast pyrolysis in a double auger reactor
Qi, Fenglei UL

Scientific Conference (2019, July)

Thermochemical conversion of biomass via fast pyrolysis process is a promising way to produce renewable fuels and chemicals. In this paper, an extended discrete element method (DEM) is developed to ... [more ▼]

Thermochemical conversion of biomass via fast pyrolysis process is a promising way to produce renewable fuels and chemicals. In this paper, an extended discrete element method (DEM) is developed to predict the biomass fast pyrolysis process in a double auger reactor, which is described as a reacting granular flow. The thermodynamic state of each particle is properly predicted with an addition of a heat transfer model and a reaction model on top of the traditional DEM method. The results suggest that the predictions of the thermochemical decomposition kinetics of biomass components are consistent with the experimental observations. The results also indicate that the fast pyrolysis in the reactor is controlled by the heat transfer process. Any operating condition variation in favor of enhancing heat transfer is beneficial to the fast pyrolysis process and vice versa. [less ▲]

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See detail2017 AIChE Annual Meeting
Qi, Fenglei UL; Wright, Mark

in Qi, Fenglei; Wright, Mark (Eds.) A DEM modeling of biomass fast pyrolysis in a double screw reactor (2017, October 31)

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See detailNumerical study of particle mixing in a lab-scale screw mixer using the discrete element metod
Qi, Fenglei UL; Heindel, Theodore; Wright, Mark

in Powder Technology (2017), 308

This study employs the discrete element method (DEM) to simulate particulate flow and investigate mixing performance of a lab-scale double screw mixer. The simulation employs polydispersed biomass and ... [more ▼]

This study employs the discrete element method (DEM) to simulate particulate flow and investigate mixing performance of a lab-scale double screw mixer. The simulation employs polydispersed biomass and glass bead particles based on experiments conducted in previous studies. Visual examination of particle distribution and statistical analysis of particle residence times of experimental data served as model validation. Statistical analysis indicates a maximum 9.8% difference between the experimental and simulated biomass particle mean residence time, and visual observations suggest the simulation captures the particle mixing trends observed in the experiments. Results indicate that the particle mean mixing time, non-dimensionalized by ideal flow time in the plug flow reactor, varies between 1.008 and 1.172, and it approaches 1 with increasing biomass feed rate. The mixing index profile in the axial direction shows a mixing-demixing-mixing oscillation pattern. Increasing screw pitch length is detrimental to mixing performance; decreasing the solid particle feed rate reduces the mixing degree; and increasing the biomass to glass bead size ratio decreases mixing performance. A comparison of a binary, single-sized biomass and glass particles mixture to a multicomponent mixture indicates that the binary system has similar mixing pattern as a multicomponent system. These findings demonstrate that DEM is a valuable tool for the design and simulation of double screw mixing systems. [less ▲]

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See detailA novel optimization approach to estimating kinetic parameters of the enzymatic hydrolysis of corn stover
Qi, Fenglei UL; Wright, Mark

in AIMS Energy (2016), 4(1), 52-67

Detailed reference viewed: 62 (3 UL)