References of "Wright, Mark"
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See detailA DEM modeling of biomass fast pyrolysis in a double auger reactor
Qi, Fenglei UL; Wright, Mark

in International Journal of Heat and Mass Transfer (2020), 150

Thermochemical conversion of biomass via fast pyrolysis is a proven pathway to product low-carbon crude bio-oils. In this research, an extended discrete element method (DEM) is proposed for simulating ... [more ▼]

Thermochemical conversion of biomass via fast pyrolysis is a proven pathway to product low-carbon crude bio-oils. In this research, an extended discrete element method (DEM) is proposed for simulating biomass fast pyrolysis reacting granular flows in a double auger reactor, in which particle hydrodynamics and interparticle heat transfer processes are involved and coupled with chemical reactions in solid particles. An adaptive time step algorithm is proposed to achieve a stable coupling between the integration of reaction ordinary differential equations and the DEM solver, and the algorithm is proven computationally efficient. A multi-component fast pyrolysis kinetics is adopted and its modeling accuracy is assessed by carrying out simulations of benchmark biomass pyrolysis experiments and comparing the prediction results with experimental data. The predicted product yields of bio-oil, char and non-condensable gas from the simulation of the biomass fast pyrolysis in the auger reactor are in satisfactory agreement with experimental measurements. The decomposition rates of biomass components in the reactor are revealed from the simulation and the pyrolysis number Py is calculated from the decomposition rate of biomass and the heat transfer coefficient. The Py number illustrates that the biomass fast pyrolysis process is limited by the heat transfer process at particle size of 2 mm. [less ▲]

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See detailParticle scale modeling of heat transfer in granular flows in a double screw reactor
Qi, Fenglei UL; Wright, Mark

in Powder Technology (2018), 335

Heat transfer in granular flows plays an important role in particulate material processing such as food production, pharmaceuticals and biorenewable energy production. Better understanding of the ... [more ▼]

Heat transfer in granular flows plays an important role in particulate material processing such as food production, pharmaceuticals and biorenewable energy production. Better understanding of the thermodynamics in granular flows is essential for equipment design and product quality control. In this research, a particle-scale heat transfer model was developed within the frame of traditional Discrete Element Method (DEM), which considers both conductive heat transfer and radiative heat transfer among particles. A particle-wall heat transfer model was also proposed for resolving particle-wall conductive and radiative heat transfer. The developed thermal DEM model was validated by modeling heat transfer in packed beds and comparing simulation predictions with experimental measurements. The thermal DEM model was successfully applied to the simulation of heat transfer in binary component granular flows in a double screw reactor designed for biomass fast pyrolysis to gain better understanding of the heat transfer in the system. The existence of both spatial and temporal temperature oscillations is observed in the double screw reactor. The effects of the operating conditions on the average temperature profile, biomass particle temperature probability distribution, heat flux and heat transfer coefficient are analyzed. Results indicate that the particle-fluid-particle conductive heat transfer pathways are the dominant contributors to the total heat flux, which accounts for approximately 70%–80% in the total heat flux. Radiative heat transfer contributes 14%–26% to the total heat flux and the conductive heat transfer through contact surface takes only 1%–5% in the total heat flux. The total heat transfer coefficient in the double screw reactor is also reported, which varies from 70 to 110 W / (m 2 • K) depending on the operating conditions. [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: 127 (3 UL)