Abstract
Turbulent boundary layer profiles on the aircraft surface were characterized by pitot-rake measurements conducted in flight experiments at high subsonic Mach number ranges. Due to slight variations in atmospheric air conditions or aircraft attitudes, such as angles of attack and absolute flight speeds at different flights even under the same premised flight conditions, the boundary layer profiles measured at different flights can exhibit different shape and velocity values. This concern leads to difficulty in evaluating the efficiency of using some kind of drag-controlling device such as riblets in the flight test, since the evaluation would be conducted by comparing the profiles measured with and without using riblets at different flights. An approach was implemented to interpolate the boundary layer profile for a flight condition of interest based on the response surface method, in order to eliminate the influence of the flight conditional difference. Results showed that the interpolation with the 3rd-degree response surface model with a combination of two independent variables of flight Mach number and total pressure successfully eliminated the influence of the flight conditional difference, and interpolated the boundary layer profiles measured at different flights within an inaccuracy of 4.1% for the flight Mach number range of 0.5 to 0.78.
Highlights
Along with the increase in air travel, the demand for economical and environmentally friendly aircraft is growing
In this study, based on the measured U-velocity using the pitot-rakes in the boundary layer region on the aircraft surface in flight conditions, the accuracy of the proposed interpolation method based on the response surface methodology applied to the flight experimental data was evaluated and is reported
C p f it where C p f it is a vector of the parameter being reconstructed by the fitting dataset for interpolation, X is the matrix of values of the design variables at each flight condition, A is the vector of tuning parameters, and ε is a vector of errors inherent in the curve fitting using the response surface model (equivalent to the one expressed in Equation (10)). n is the total number of experimental cases and k is the total number of variables
Summary
Hidemi Takahashi 1, * , Mitsuru Kurita 2 , Hidetoshi Iijima 2 and Monami Sasamori 2. Research and Development Directorate, Japan Aerospace Exploration Agency, Kakuda, Miyagi 981-1525, Japan. Received: 5 October 2018; Accepted: 16 November 2018; Published: 21 November 2018
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