Development of an Analytical SparkJet Model

Abstract

A variety of active flow control (AFC) methods have been successfully applied to low speed flows; however, AFC techniques available for high-speed, supersonic applications are very limited. Under the Air Force Office of Scientific Research sponsorship, The Johns Hopkins University Applied Physics Laboratory is investigating a device intended for highspeed flow control called the SparkJet actuator, which manipulates high-speed flows without active mechanical components. Actuator characterization to date has included computational and experimental techniques, including parametric studies and flow visualization over a variety of operating conditions. This paper focuses on the development of an analytical model accompanied by experimental acquisition of the pressure inside the SparkJet cavity. Previous experimental efforts included the use of high-resolution particle image velocimetry and digital speckle tomography to measure the plume velocities and temperature distribution, respectively, in the core of the SparkJet plume. While these tests gave high-resolution results, the results were incomplete and the high velocity core remains difficult to quantify experimentally. Therefore, attention turned to internal chamber pressure measurements to help validate computational fluid dynamics and analytical models. The analytical model presented previously has been expanded to include the unchoked portion of the discharge and preliminary model development of the refresh stage has begun. Experimental testing includes variations in electrode configuration and power supply design intended to improve SparkJet performance. This preliminary characterization study resulted in an actuator design 3.5 times more efficient as previous actuator designs. As a result of this work, a maximum efficiency factor of 35% has been demonstrated so far for the SparkJet actuator based on the experimental peak pressure inside the SparkJet cavity. Future work will include improving SparkJet efficiency further, expanding the model to predict high-frequency actuation performance of a single actuator and testing various SparkJet configurations to enhance the model validation and understand the model limitations.