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Siddhi Arya

Publications and source records attributed to Siddhi Arya.

2 recordsLinked to original sources

Role of gravity on preferential clustering of microparticles in unsteady wake flows

Direct numerical simulations are carried out for particle-laden flow over the cylinder to investigate preferential clustering of particles in an unbounded vertical channel flow. The flow is examined at Reynolds numbers Re=100 and 200 for varying particle Stokes number, particle loadings and Froude numbers to quantify the combined influence of particle inertia and gravitational settling on particle motion. The unladen flow exhibits the classical vortex shedding pattern observed in flow over bluff bodies at both Reynolds numbers. Reynolds number dependent wake width, wake recovery, and velocity-deficit evolution are observed, characterizing the coherent flow structures that govern particle dynamics. In particle-laden unsteady wake flows, the non-uniform particle distribution leads to formation of coherent voids and clusters, whose shape are directly correlated with background flow dynamics. Gravity modifies particle-fluid interaction, which leads to an increase in slip velocity, weakens vortex-induced particle clustering and promotes them to travel through vortices, resulting in a transition of the void shape from individual leaf-like structure to snake-like void zone and eventually into a nearly vertical void structure. In upstream region infront of the cylinder, inertial particles form a bow-shock-like structure whose extent increases with increase in Stokes number and finite Froude conditions. Voronoi based analysis combined with local Q values is used to investigate effect of gravity and inertia on particle distribution. The dimensionless settling velocity, St/Fr^2, is identified as the governing parameter controlling the evolution of void shape, normalized void cell area and the probability distribution of Voronoi cell areas. The effect of wake dynamics, particle inertia, and gravity is reported to jointly govern preferential clustering in bluff-body wakes.

physics.flu-dyn

Effect of channel dimensions and Reynolds numbers on the turbulence modulation for particle-laden turbulent channel flows

The addition of particles to turbulent flows changes the underlying mechanism of turbulence and leads to turbulence modulation. Different temporal and spatial scales for both phases make it challenging to understand turbulence modulation via one parameter. The important parameters are particle Stokes number, mass loading, particle Reynolds number, fluid bulk Reynolds number, etc., that act together and affect the fluid phase turbulence intensities. In the present study, we have carried out the large eddy simulations for different system sizes (2δ/dp = 54, 81, and 117) and fluid bulk Reynolds numbers (Re_b = 5600 and 13750) to quantify the extent of turbulence attenuation. Here, δ is the half-channel width, dp is the particle diameter, and Re_b is the fluid Reynolds number based on the fluid bulk velocity and channel width. The point particles are tracked with the Lagrangian approach. The scaling analysis of the feedback force shows that system size and fluid bulk Reynolds number are the two crucial parameters that affect the turbulence modulation more significantly than the other. The streamwise turbulent structures are observed to become lengthier and fewer with an increase in system size for the same volume fraction and fixed bulk Reynolds number. However, the streamwise high-speed streaks are smaller, thinner, and closely spaced for higher Reynolds numbers than the lower ones for the same volume fraction. In particle statistics, it is observed that the scaled particle fluctuations increase with the increase in system size while keeping the Reynolds number fixed. However, the scaled particle fluctuations decrease with the increase in fluid bulk Reynolds number for the same volume fraction and fixed system size. The present study highlights the scaling issue for designing industrial equipment for particle-laden turbulent flows.

physics.flu-dyn