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Preliminary Design Review (PDR) The University Of Michigan 2011

Detailed review of vehicle design considerations, materials, safety plan, recovery scheme, aerodynamics, controls, and testing plans for a high-performance rocket. Includes static stability analysis and motor selection.

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Preliminary Design Review (PDR) The University Of Michigan 2011

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  1. Preliminary Design Review (PDR) • The University Of Michigan • 2011 1

  2. Vehicle: i. 2

  3. Vehicle: ii. Nose Main Chute Separation Bay Main Chute Separation 3

  4. Vehicle: iii. Main Chute Seperation Aviation Bay Aviation Bay Access Cut Apogee Separation Bay Apogee Separation 4

  5. Vehicle: iv. Apogee Separation Apogee Separation Bay Motor 5

  6. Vehicle Dimensions • Body Tube • 5.5 in dia. • Can • 2.0 in dia. 6

  7. Launch Vehicle Verification • Vehicle/Payload design justification • Static stability analysis • Materials/system justification (discussed in further detail in proceeding slides) 7

  8. Vehicle Design Justification • Different ideas for reducing drag • Requirements • Stable • Fast • Precise • Consistent • Highly variable 8

  9. Vehicle Materials • Nosecone Polystyrene Plastic • Body Blue Tube (Apogee Comp.) • Cans Blue Tube (Apogee Comp.) • Fins G10 fiberglass 9

  10. Material Justifications • Phenolic Tubing • Cured paper fibers • Cheapest, strong, brittle • Blue Tube 2.0 • High-density paper • More expensive, durable, dense • Carbon Fiber • Strands of woven carbon • Most expensive, strongest, labor-intensive 10

  11. Static Stability Margin • 1.5 in neutral configuration pre-launch • 2.4 after engine burnout • Drag mechanism actuated • RockSim estimated CP/CG locations • On the unstable side • Add mass to nose of rocket 11

  12. Recovery Scheme • Two Separations • Apogee • Drogueless • 500 Feet • Main Parachute • Double Redundancy • Flight computer • Altimeter 500 Feet Apogee 12

  13. Vehicle Safety Verification Plan This matrix shows detrimental failures in red, recoverable failures in yellow, and failures with a minimal effect in green 13

  14. Testing Plans • Ground test proper body tube separation during E-Charge ignition • Use a multimeter to measure the current the Flight Computer sends to each E-Charge during ground simulations • Servo selection through torque testing on flap from collected simulation/wind tunnel data 14

  15. Motor Selection • Motor Manufacturer: Loki • Motor Designation: L1482-SM • Total Impulse: 868.7 lb-s • Mass pre/post burn: Pre:7.8 lb • Post:3.8 lb 15

  16. Thrust-To-Weight Ratio 16

  17. Rail Exit Velocity • Rail Exit Velocity: 85.1 ft/s • Rail Length: 10 ft 17

  18. Recovery Avionics • Raven Flight Computer • Competition Altimeter • 4 Total E-Charges • 2 from Flight Computer • 2 from Altimeter • 1 Main Apogee Charge • @ 5280 feet • 1 Backup • 1 Main Chute Charge • @ 400 feet • 1 Backup Apogee TB 9V Batteries AvBay Flight Computer Competition Altimeter Positive TB Main Chute TB 18

  19. Aerodynamics-Linear Flaps: i. • Flap Geometry • 0% closed corresponds to the position where the flap is not exposed to air flow • 100% closed corresponds to where the flap is fully extended into the flow 19

  20. Aerodynamics-Linear Flaps: ii. Flap B Flap A 20

  21. Aerodynamics-Linear Flaps: iii. Flap C Flap D 21

  22. Aerodynamics-Linear Flaps: iv. • Drag data from cases run at 300 m/s *NOTE: All flap data is for one flap and all rocket data is for half-body 22

  23. Aerodynamics-Rotating Flaps: i. • Moment Concerns with the y component of the force generated by the flap at various angles • Analyzed at the most extreme case (largest can and flap size at 45 ̊) • Force in the y direction caused by the flap angle deflection is negated by the force it creates on the wall of the can *NOTE: All data is from a simulated wind speed of 300 m/s 23

  24. Aerodynamics-Rotating Flaps: ii. ANSYS Fluent CFD mesh sizes were refined in areas of interest such as the flap and the interior wall for optimal results. 24

  25. Structures-Can Analysis • Analyzed the worst case scenario (flaps 100% closed) • Pressure forces in front of the valve are not a concern • Low pressure pockets behind the valve are not a concern 25

  26. Controls: i. • Proportional Integral Derivative (PID) controller that will induce pressure drag as a means of regulating vehicle altitude • Drag is calculated dynamically during flight • Controller should respond to physical system changes in no more than 50 milliseconds and recover within 2% of the goal altitude 26

  27. Controls-System Model: ii. Dynamic Apogee-Rectifying Targeting (DART) Control System Dynamic Target: Used to aid in assuring the mean energy path solution is followed Restrained Controller: Proportional Integral Derivative (PID) derived controller with physical limits Physics Plant: Simulation of vehicle-environment interaction given controller commands Instrument Uncertainty: Propagation of instrument uncertainty into system values Alt. Projection: Projection of rocket apogee altitude with same physics plant model for consistency 27

  28. Controls – Dynamic Target

  29. Controls – Restrained Controller

  30. Controls - Physics

  31. Controls –Instrument Uncertainty

  32. Controls – Apogee Calculation

  33. Flight Avionics Drag Servo • Competition Altimeter • Drag Computer • Drag Servo Drag Computer 9V Batteries Competition Altimeter 33

  34. Propulsion • Select a motor such that it will allow our rocket to exceed one mile in our minimum drag configuration 34

  35. Payload Design • Drag Control System • Actuating flaps located within side cans to control drag • Control system will activate under specific altitude and/or velocity conditions 35

  36. Payload Test Plan i. • Flap Drag Testing • Simulations/flow characterization using compressible flow in ANSYS Fluent CFD over a range of Mach numbers • Test drag flap mechanism in various configurations to confirm results from simulated model • Produce a function for control system relative to drag, flow speed and flap deflection 36

  37. Payload Test Plan ii. Drag Flap Control System Testing • 4 constants to vary (Kp, Ki, Kd, Dt) • N^4 simulations for N possible different constants • Parallel processing in Matlab to tackle Monte Carlo simulation • NYX / FLUX supercomputers from UM Center for Advance Computing used to tune constants for best performance 37

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