Axial Dispersion Large Peclet¶
Axial Dispersion high peclet number assumption.
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class
rtdpy.ad_hi_peclet.AD_hi_peclet(tau, peclet, dt, time_end)[source]¶ Bases:
rtdpy.rtd.RTDCreate Axial Dispersion with small amount of Dispersion (Pe>100) Residence Time Distribution (RTD) model. [1]
\[E(t) = \frac{\sqrt{Pe}}{2\tau\sqrt{\pi}} \text{exp}\left[-\frac{Pe \left(1-t/\tau\right)^2} {4}\right]\]- Parameters
- tauscalar
L/U. Mean residence time.
tau>0- pecletscalar
Reactor Peclet number (L*U/D).
peclet>0- dtscalar
Time step for RTD.
dt>0- time_endscalar
End time for RTD.
time_end>0
References
- 1
Levenspiel O. (1999) “Chemical Reaction Engineering: Third Edition” John Wiley & Sons, Inc.
Examples
>>> import matplotlib.pyplot as plt >>> import rtdpy >>> for pe in [100, 1000]: ... a = rtdpy.AD_hi_peclet(tau=1, peclet=pe, dt=.01, time_end=3) ... plt.plot(a.time, a.exitage, label=f"peclet={pe}") >>> plt.xlabel('Time') >>> plt.ylabel('Exit Age Function') >>> plt.legend() >>> plt.show()
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property
dt¶ Time step for RTD
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property
exitage¶ Exit age distribution for RTD
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property
exitage_norm¶ Normalized Exit Age Distribtion for RTD
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frequencyresponse(omegas)¶ - Parameters
- omegasndarray
frequencies at which to evaluate magnitude response
- Returns
- magnitudendarray
frequency magnitude response at omegas
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funnelplot(times, disturbances)¶ Return maximum output signal due to square disturbances.
Uses method from [Garcia] . Also returns meshgrid for times and disturbance inputs for ease of plotting.
- Parameters
- timesarray_like, size m
Times to determine funnelplot
- disturbancesarray_like, size n
Disturbance magnitudes
- Returns
- x2D meshgrid size (mxn)
times
- y2D meshgrid size (mxn)
disturbances
- response2D meshgrid size (mxn)
maximum response at (x,y)
References
- Garcia
Garcia-Munoz S., Butterbaugh A., Leavesley I., Manley L.F., Slade D., Bermingham S. (2018) A flowhseet model for the development of a continuous process for pharmaceutical tablets: An industrial perspective. “AIChE Journal”, 64(2), 511-525.
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integral()¶ Integral of RTD.
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mrt()¶ Mean residence time of RTD.
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output(inputtime, inputsignal)¶ Convolves input signal with RTD
- Parameters
- inputtimendarray
Times of input signal, which must have same dt as RTD. Size m
- inputsignalndarray
Input signal. Size n
- Returns
- outputsignalndarrary
Output signal at same dt. Size m + n -1
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property
peclet¶ Peclet Number
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sigma()¶ Variance of RTD.
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property
stepresponse¶ Step respose of RTD
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property
stepresponse_norm¶ Normalized step respose of RTD
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property
tau¶ Mean residence time, Tau.
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property
theta¶ Dimensionless Time.
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property
time¶ Time points for exitage function.
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property
time_end¶ Last time point for RTD