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Introducing a fluid microjet into the boundary layer to increase fluid momentum and hence delay separation is a method for actively controlling a flow separation region. The present work numerically analyzed the control of a separation bubble behind a ramp. For this purpose, we first verified the steady-state numerical results for a flow (without a jet) over the ramp against reliable experimental studies from the literature. Next, the effects of introducing a microjet to the flow were also verified. A jet was then placed at three different distances above the ramp to study its impact on various parameters, including velocities, Reynolds stresses, pressure, vorticity, streamlines, and the separation bubble size. As the jet was moved further back, the jet-induced upwash region grew considerably. Finally, the effects of using three identical jets were studied and compared against those of a single jet. The results indicated that using a three-jet array shrank the separation bubble. Using an array with d/ D = 15 (distance between microjets over microjet diameter) can limit laterally the separation bubble about 2.75 times smaller than a single jet in the z-direction. Also, the employment of the jet managed to decrease the length of the separation zone in the x-direction up to 78%, in the case of Lx/ L1 = 0.0143 (longitudinal distance of microjet from above the ramp over ramp length) and d/ D = 10.
Introducing a fluid microjet into the boundary layer to increase fluid momentum and hence delay separation is a method for actively controlling a flow separation region. The present work numerically analyzed the control of a separation bubble behind a ramp. For this purpose, we first verified the steady-state numerical results for a flow (without a jet) over the ramp against reliable experimental studies from the literature. Next, the effects of introducing a microjet to the flow were also verified. A jet was then placed at three different distances above the ramp to study its impact on various parameters, including velocities, Reynolds stresses, pressure, vorticity, streamlines, and the separation bubble size. As the jet was moved further back, the jet-induced upwash region grew considerably. Finally, the effects of using three identical jets were studied and compared against those of a single jet. The results indicated that using a three-jet array shrank the separation bubble. Using an array with d/ D = 15 (distance between microjets over microjet diameter) can limit laterally the separation bubble about 2.75 times smaller than a single jet in the z-direction. Also, the employment of the jet managed to decrease the length of the separation zone in the x-direction up to 78%, in the case of Lx/ L1 = 0.0143 (longitudinal distance of microjet from above the ramp over ramp length) and d/ D = 10.
The control of flow and heat transfer has recently been of great interest to engineering researchers in light of computational technology advances. Microjets are used as control solutions to avoid flow separation and increase heat transfer. The present study evaluates a microjet over a ramp at microjet velocity ratios (jet to inflow velocity) of = 1, 2, and 4 and heat flux ratios (heat flux to based heat flux) of = 1, 2, and 3 to examine the flow separation area and heat transfer improvement numerically. The numerical velocity and temperature gradients were compared to earlier numerical and experimental works. Then, the flow over the ramp was analyzed at the aforementioned microjet velocity and heat flux ratios. Moreover, streamlines, bed pressure, fluid temperature, and bed Nusselt number were evaluated. It was found that a microjet with the optimal velocity could not only diminish the separation bubble but also improve heat transfer. A rise in the velocity ratio from 2 to 4 led to a nearly 33% decrease in the separation bubble and an approximately 20% rise in the Nusselt number. In addition, the microjets enhanced heat transfer by up to 50%.
The present work studied various models for predicting turbulence in the problem of injecting a fluid microjet into the boundary layer of a turbulent flow. For this purpose, the one-equation Spalart–Allmaras (SA), two-equation k–ε and k–ω, multi-equation transition k-kL–ω, transition shear stress transport (SST), and Reynolds stress models were used for solving the steady microjet into the turbulent boundary layer, and their results are compared with experimental results. Comparing the results indicated that the steady solution methods performed sufficiently we for this problem. Furthermore, it was found that the four-equation transition SST model was the most accurate method for predicting turbulence in this problem. This model predicted the velocity along the x-axis in near- and far-jet locations with about 1% and 5% average errors, respectively. It also outperformed the other methods in predicting Reynolds stresses, especially at the center (nearly 5% error). Moreover, the modified four-equation transition SST model has improved the system's performance in predicting the studied parameters by utilizing Sørensen correlations in predicting Reθt (the transition momentum thickness Reynolds number), Flength (an empirical correlation that controls the length of the transition region), and Reθc (the critical Reynolds number where the intermittency first starts to increase in the boundary layer).
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