Processing your ADCP data using structure function techniques: Difference between revisions

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Created page with "== Structure Function Processing Steps == # Extract or compute the along-beam distance of the center of each bin [zb] and bin center separation [r0] # Calculate the along-be..."
 
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== Structure Function Processing Steps ==
== Structure Function Processing Steps ==


# Extract or compute the along-beam distance of the center of each bin [zb] and bin center separation [r0]  
# Extract or compute the along-beam distance of the center of each bin [z<sub>b</sub>] and bin center separation [r0]  
# Calculate the along-beam velocity fluctuations in each bin [v’(zb)]  
# Calculate the along-beam velocity fluctuations in each bin [v’(z<sub>b</sub>)]  
## If using burst sampling, calculations are done over the length of the burst if stationary   
## If using burst sampling, calculations are done over the length of the burst if stationary   
## If using continuous sampling, a time interval must be selected in which the flow can assumed to be stationary  
## If using continuous sampling, a time interval must be selected in which the flow can assumed to be stationary  
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### ''A linear detrend of the time interval''  
### ''A linear detrend of the time interval''  
### ''A low pass filtered signal''  
### ''A low pass filtered signal''  
# Select the maximum distance over which to compute the structure function based on conditions of the flow (e.g., expected max overturn) [rmax]  
# Select the maximum distance over which to compute the structure function based on conditions of the flow (e.g., expected max overturn) [r<sub>max</sub>]  
# Start at the first bin where zb >= rmax/2  
# Start at the first bin where z<sub>b</sub> >= r<sub>max</sub>/2  
# Compute the centered difference of v’ along the beam for the first pair of bins on either side: v’(z+r0)-v’(z-r0)  
# Compute the centered difference of v’ along the beam for the first pair of bins on either side: v’(z+r<sub>0</sub>)-v’(z-r<sub>0</sub>)  
# Compute the second order structure function D(z,r) = mean-square of the velocity fluctuation difference:  D(z,2*r0) = mean(v’(z+r0)-v’(z-r0))2  
# Compute the second order structure function D(z,r) = mean-square of the velocity fluctuation difference:  D(z,2*r0) = mean(v’(z+r<sub>0</sub>)-v’(z-r<sub>0</sub>))2  
# Repeat steps 5-6 for all pairs of bins where the separation distance between bins r <= rmax
# Repeat steps 5-6 for all pairs of bins where the separation distance between bins r <= r<sub>max</sub>
# With these data points, fit a line to the form D(z,r) = N + Ar2/3 to estimate values for A and N where A = Cv2e2/3  and N is an estimate of the uncertainty due to noise.  
# With these data points, fit a line to the form D(z,r) = N + Ar<sup>2</sup>/3 to estimate values for A and N where A = Cv<sup>2</sup>ε<sup>2</sup>/3  and N is an estimate of the uncertainty due to noise.  
# Solve for e using Cv2 = 2.1  
# Solve for ε using Cv<sup>2</sup> = 2.1  
# Repeat the steps in (5) – (9) for each bin until zb + rmax/2 >= end of profile
# Repeat the steps in (5) – (9) for each bin until z<sub>b</sub> + r<sub>max</sub>/2 >= end of profile

Revision as of 13:33, 22 September 2021

Structure Function Processing Steps

  1. Extract or compute the along-beam distance of the center of each bin [zb] and bin center separation [r0]
  2. Calculate the along-beam velocity fluctuations in each bin [v’(zb)]
    1. If using burst sampling, calculations are done over the length of the burst if stationary
    2. If using continuous sampling, a time interval must be selected in which the flow can assumed to be stationary
    3. You can calculate the fluctuations around:
      1. The mean of the time interval
      2. A linear detrend of the time interval
      3. A low pass filtered signal
  3. Select the maximum distance over which to compute the structure function based on conditions of the flow (e.g., expected max overturn) [rmax]
  4. Start at the first bin where zb >= rmax/2
  5. Compute the centered difference of v’ along the beam for the first pair of bins on either side: v’(z+r0)-v’(z-r0)
  6. Compute the second order structure function D(z,r) = mean-square of the velocity fluctuation difference: D(z,2*r0) = mean(v’(z+r0)-v’(z-r0))2
  7. Repeat steps 5-6 for all pairs of bins where the separation distance between bins r <= rmax
  8. With these data points, fit a line to the form D(z,r) = N + Ar2/3 to estimate values for A and N where A = Cv2ε2/3 and N is an estimate of the uncertainty due to noise.
  9. Solve for ε using Cv2 = 2.1
  10. Repeat the steps in (5) – (9) for each bin until zb + rmax/2 >= end of profile
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