Literature DB >> 31395987

Effects of Sweeping Jet Actuator Parameters on Flow Separation Control.

Mehti Koklu1.   

Abstract

A parametric experimental study was performed with sweeping jet actuators (fluidic oscillators) to determine their effectiveness in controlling flow separation on an adverse pressure gradient ramp. Actuator parameters that were investigated include blowing coefficients, operation mode, pitch and spreading angles, streamwise location, and size. Surface pressure measurements and surface oilflow visualization were used to characterize the effects of these parameters on the actuator performance. 2D Particle Image Velocimetry measurements of the flow field over the ramp and hot-wire measurements of the actuator's jet flow were also obtained for selective cases. In addition, the sweeping jet actuators were compared to other well-known flow control techniques such as micro-vortex generators, steady blowing, and steady vortex-generating jets. The results confirm that the sweeping jet actuators are more effective than steady blowing and steady vortex-generating jets for this ramp configuration. The results also suggest that an actuator with a wider jet spreading (110 vs. 70 degrees) placed closer (2.3 vs. 7 boundary layer thickness upstream) to the flow separation location provides better performance. Different actuator sizes obtained by scaling down the actuator geometry produced different jet spreading. Scaling down the actuator (based on the throat dimensions) from 6.35 × 3.18 mm to 3.81 × 1.9 mm resulted in similar flow control performance; however, scaling down the actuator further to 1.9 × 0.95 mm reduced the actuator efficiency by reducing the jet spreading considerably. The results of this study provide insight that can be used to design and select the optimal sweeping jet actuator configuration for flow control applications.

Year:  2018        PMID: 31395987      PMCID: PMC6687328          DOI: 10.2514/1.J055796

Source DB:  PubMed          Journal:  AIAA J        ISSN: 0001-1452            Impact factor:   2.127


  1 in total

1.  Multifidelity computing for coupling full and reduced order models.

Authors:  Shady E Ahmed; Omer San; Kursat Kara; Rami Younis; Adil Rasheed
Journal:  PLoS One       Date:  2021-02-11       Impact factor: 3.240

  1 in total

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