There is a critical lack of quantitative data regarding the mechanism of brownout cloud formation. Recognizing this, tests were conducted during the Air Force Research Lab 3D-LZ Brownout Test at the US Army Yuma Proving Ground. Photogrammetry was utilized during two rounds of flight tests with an instrumented EH-60L Black Hawk to determine if this technique could quantitatively measure the formation and evolution of a brownout cloud. Specific areas of interest include the location, size, and average convective velocity of the cloud, along with the characteristics of any defined structures within it. Following the first flight test, photogrammetric data were validated through comparison with onboard vehicle data. Lessons learned from this test were applied to the development of an improved photogrammetry system. A second flight test, utilizing the improved system, demonstrated that obtaining quantitative measurements of the brownout cloud are possible. Results from these measurements are presented in the paper. Flow visualization with chalk dust seeding was also tested. It was observed that pickup forces of the brownout cloud appear to be very low. Overall, these tests demonstrate the viability of photogrammetry as a means for quantifying brownout cloud formation and evolution.
The application of statistical Design of Experiments (DOE) to helicopter wind tunnel testing was explored during two powered rotor wind tunnel entries during the summers of 2012 and 2013. These tests were performed jointly by the U.S. Army Aviation Development Directorate Joint Research Program Office and NASA Rotary Wing Project Office, currently the Revolutionary Vertical Lift Project, at NASA Langley Research Center located in Hampton, Virginia. Both entries were conducted in the 14-by 22-Foot Subsonic Tunnel with a small portion of the overall tests devoted to developing case studies of the DOE approach as it applies to powered rotor testing. A 16-47 times reduction in the number of data points required was estimated by comparing the DOE approach to conventional testing methods. The average error for the DOE surface response model for the OH-58F test was 0.95% and 4.06% for drag and download, respectively. The DOE surface response model of the Active Flow Control test captured the drag within 4.1% of measured data. The operational differences between the two testing approaches are identified, but did not prevent the safe operation of the powered rotor model throughout the DOE test matrices.
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