Enhancing hydrodynamic forces through miniaturized control of square cylinders using the lattice Boltzmann method.

This study investigates the influence of small control cylinders on the fluid dynamics around a square cylinder using the Lattice Boltzmann Method (LBM). Varying the gaps (L) between the main and control cylinders from 0 to 6, four distinct flow regimes are identified: the solo body regime (SBR), shear layer reattachment (SLR), suppressed fully developed flow (SFDF), and intermittent shedding (IS). The presence of control cylinders results in significant reductions in flow-induced forces, with drag coefficient (CD) and root mean square values of drag and lift coefficients (CD and CL) decreasing by approximately 31%, 90%, and 81%, respectively. The SFDF flow regime exhibits the lowest fluid forces compared to other regimes. The effects of tiny control cylinders on the fluid flow characteristics of a square cylinder are examined using the Lattice Boltzmann Method (LBM) in this research work. The gaps (L) between the main and control cylinders are varied in the range from 0 to 6. The size of each control cylinder is equal to one-fifth of the primary cylinder. According to the findings, there are four distinct flow regimes as the gap spacing varies: solo body regime (SBR), shear layer reattachment (SLR), suppressed fully developed flow (SFDF), and intermittent shedding (IS) for gap spacing ranges 0 ≤ L ≤ 0.2, 0.3 ≤ L ≤ 0.9, 1 ≤ L ≤ 3, and 3.2 ≤ L ≤ 6, respectively. Additionally, it has been noted that the amplitude of variable lift force is reduced when the gap separation between the main and control cylinders is increased. When compared to solo cylinder values, it is found that the presence of small control cylinders in the flow field results in a considerable reduction of flow-induced forces. The SFDF flow regime was determined to have the lowest fluid forces compared to the other flow regimes studied. Our findings highlight the efficacy of small control cylinders in mitigating flow-induced forces and controlling flow characteristics. The LBM proves to be a valuable computational technique for such fluid flow problems.