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A hydrofoil is a fundamental structure in fluid machinery, and it is widely applied to the fields of propellers, blades of axial flow pumps and underwater machinery. To reveal that the geometric structure of the leading-edge of a hydrofoil is the mechanism that affects the transient cavitating flow, we regard the three fish-type leading-edge structures of mackerel, sturgeon and small yellow croaker as the research objects and use high-precision non-contact 3D scanners to establish three bionic hydrofoils (Mac./Stu./Cro.). We use large eddy simulation to simulate the transient cavitating flow of hydrofoils numerically and compare and analyze their lift–drag characteristics, the transient behavior of unsteady cavitation and the vortex evolution. The numerical simulation results are in good agreement with the experimental results. The warping of leading-edge structure will cause a change in lift–drag characteristics, and the Cro. hydrofoil has a good lift-to-drag ratio. When the leading-edge structure is tilted upward (Cro. hydrofoil), the position of the attached cavity will move forward, which will accelerate the cavitation evolution and improve the velocity fluctuation of the trailing edge. When the leading-edge structure is tilted downward (Stu. hydrofoil), the change in the vortex stretching and dilatation terms will be complex, and the influence area of the vortex will widen.

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.

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.

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.