02_greg_larson2 - Flight Conditions M = 0.56 25000...

Info icon This preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Overview of Experiment Flight Conditions M = 0.56, 25000 feet (Subsonic condition) M = 0.86, 36000 feet (Transonic condition) Nose-To-Tail (N2T) Distances – 20, 55 , 110 and 190 feet Nomenclature X-direction (longitudinal) Y-direction (lateral) Z-direction (vertical) The subsonic flight condition (M=0.56, h=25000 feet) was selected to match pre-existing data from vortex-effect prediction codes. These codes needed to be validated to determine their utility on future applications of AFF. Since a possible future application of AFF is for transport airplane, flight data were also acquired at M=0.86 and h =36000 feet. This transonic flight condition is representative for that class of vehicle. The vortex effects were also mapped at different longitudinal distances behind the leader airplane. These Nose-To-Tail (N2T) distances were monitored by the control room and maintained by the pilots through periodic radio calls. Only the results from the subsonic condition, 55’ N2T will be presented here. 55’ is equal to the length of the F/A-18. The reference axis system was as shown above. It should be noted that although Z is positive down, this presentation will refer to positions above the lead airplane (or high ) as positive and positions below the lead airplane (or low ) as negative. Page 1 Autonomous Formation Flight Program NAS4-00041 TO-104
Image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Page 2 Autonomous Formation Flight Program NAS4-00041 TO-104 Lift and Drag Analysis Flight Test Database Engine Data Air Data INS Data In-Flight Thrust Model F G , F RAM , FE DRAG Wind Axis Accelerations A XW , A YW , A ZW Air Data Computations Gross Weight, V inf , P o D est. = T Trail. - J Lead Performance Model D = cos( D est ) F G – F RAM – FE DRAG - F EX C L , C D , C Di = C D – C D0 Vortex Effect = Vortex – Baseline % ' C D , % ' C Di , % ' WFT Predicted Performance (outside vortex influence) C L , C D , C D0 F EX =GW*A XW Performance data was determined using classical techniques. A force balance along the flight path was used to determine drag while a force balance perpendicular to that was used to determine lift: D = cos( D est) FG – FRAM – FEDRAG-(GW*AXW); L = sin( D est) FG + (GW*NXW). Three primary data reduction areas feed the performance mode; 1) Air Data, 2) IFT, and 3) Accelerations. The Air Data model computes gross weight (GW) using empty weight and the remaining total fuel accounting for crew weight. It also includes a calculation of an estimated alpha, D est, which is based on the trailing aircraft’s pitch angle and the lead aircraft’s flight path angle ( D est = qtrail- J lead). This was required because the trailing aircraft’s alpha probes are unusable during formation flight due to localized upwash influences of the lead aircraft. Because the lead aircraft flew at steady-state conditions (constant speed and altitude), the flight path angle, J lead, was always close to zero.
Image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern