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STABILITY IN HIGH-POWERED SOUNDING ROCKETS. ROAR - Robot On A Rocket. Hannah Thoreson , ASU/NASA Space Grant Mentor: Dr. James Villarreal. Payload Separation and Deployment.

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stability in high powered sounding rockets

STABILITY IN HIGH-POWEREDSOUNDING ROCKETS

ROAR - Robot On A Rocket

Hannah Thoreson, ASU/NASA Space Grant

Mentor: Dr. James Villarreal

payload separation and deployment
Payload Separation and Deployment
  • OBJECTIVES: Ensure the integrity of the payload during separation from the launch vehicle and deployment of the robotics component of the project. Bring payload in for landing, deployment, and recovery at a velocity that guarantees the safety of bystanders.
specifications
Specifications
  • Payload should be able to withstand the force of separation
  • 17 ft/s landing velocity
  • Proper orientation of robotics payload upon ground landing
optimization of impulse mitigation plans
Optimization of Impulse Mitigation Plans
  • Spring-damper dashpot system
  • Matlab program to calculate and plot oscillations from impulse of parachute deployment
  • User inputs values for the mass of the combined payload and housing cabinet, the spring constant, and the damping constant
design outcomes pt i
Design Outcomes, Pt. I
  • Use of a “slider” to slow the speed of parachute deployment
design outcomes pt ii
Design Outcomes, Pt. II
  • Five parachutes, sized to bring craft in at safe landing velocity of 17 fps
  • “No right side” robot to avoid issues with uncertain landing orientation
regression rate analysis
Regression Rate Analysis
  • New project begun in late March with graduate students
  • Will attempt to predict where combustion instabilities from pressure fluctuations inside the rocket will occur
  • Without prediction, there will never be resolution
experimental set up
Experimental Set-Up

The paoad, in expanded form after leaving te rocket casing.

the fourier transform
The Fourier Transform

fs = 960   % Sample frequency

[data fs] = csvread('data.csv'); % Reads in data from CSV file

t = linspace(0,length(data)/fs,length(data)); % Time

plot(t,data)

xlabel('Time (seconds)')

ylabel('Pressure Amplitude')

title('Time Domain Plot of Pressure')

y = fft(data); % FFT of the data

f_Nyquist = fs/2; % Nyquist frequency

[y_max index] = max(y); % Principle frequency

f = (0:t-1)*(fs/t); % Frequency range

plot(x,y)

xlabel('Frequency (Hz)')

ylabel('Pressure')

title('FFT Output')