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In the current research, a high-pressure submerged cavitation jet is investigated numerically. A cavitation model is created considering the effect of shear stress on cavitation formation. As such, this model is developed to predict the cavitation jet, and then the numerical results are validated by high-speed photography experiment. The turbulence viscosity of the renormalization group (RNG) k-ε turbulence model is used to provide a flow field for the cavitation model. Furthermore, this model is modified using a filter-based density correction model (FBDCM). The characteristics of the convergent-divergent cavitation nozzle are investigated in detail using the current CFD simulation method. It is found that shear stress plays an important role in the cavitation formation in the high-pressure submerged jet. In the result predicted by the Zwart-Gerber-Belamri (ZGB) cavitation model, where critical static pressure is used for the threshold of cavitation inception, the cavitation bubble only appears at the nozzle outlet and the length of the cavity is much shorter than the actual length captured by the high-speed photography experiment. When the shear stress term is added to the critical pressure, the length of the predicted cavity is close to the experimental result and three phenomena of the jet are captured, namely, growth, shedding, and collapsing, which agrees well with the experimental high-speed image. According to the orthogonal analysis based on the simulation result, when the jet power is unchanged, the main geometry parameter of the divergent-convergent nozzle that affects the jet performance is the divergent angle. For the nozzle with three different divergent angles of 40°, 60°, and 80°, the one with the medium angle generates the most intensive cavitation cloud, while the small one shows the weakest cavitation performance. The obtained simulation result is confirmed by cavitation erosion tests of the Al1060 plate using these three nozzles.

The multi-phase flow of air and bio-particulate matter exists in many biological and environmental systems such as aerodynamic separating devices, fluidized bed combustion, and feed processing machinery. Integration of the computational fluid dynamics (CFD) and discrete element method (DEM) codes was performed to study bio-particle loading ratios' effect on the cyclone device performance. Every individual particle's behavior was captured by a DEM model using Newton's equations of motion, in which CFD modeled the continuum airflow for every computational cell scale through the Navier-Stokes equation. According to the high turbulence and chaotic behavior of the continuum airflow inside the cyclone separator, Reynolds stress turbulence model (RSM) was used. The particles used for testing and modeling were conducted on two mixture types of real-heterogeneous particulate matter, namely jojoba seeds and jojoba leaves, without any fly ash. The particles were geometrically modeled using their actual dimensions and shapes, considered the first head start research approach in the cyclonic separation and purification field. The influence of the interacting particle-particle and particle-boundary forces was taken into consideration. The numerical simulation results successfully predicted the cyclone performance at the designed conditions, which showed the best experimental data trend. These data are useful in future studies to modify the cyclone design and optimize bio-systems' operating conditions for separating the macroscopic particulate matter. Keywords Air-particle flow • Cyclonic separation • Computational fluid dynamics • Discrete element method List of symbols C d Drag coefficient C ij Fluid convection ds n Change in normal overlap at current time, s d v Spherical particle diameter, m d p Particle diameter, m D Domain diameter, m