Red cross Python coding Be sure to include two figures in your memo to the Red Cross. One figure showing the fit of the linear model to the original data and the other figure showing the fit of the power law model to the data. Finally, be sure to include your Python code in the appendix. Please make sure its your own work and word. 132
| 7 Regression
Strain rate (1/s)
Shear stress (dynes/cm2)
The first model proposed by the Red Cross is the linear (or Newtonian)
where t is the shear stress and j the strain rate. The second model is the
power law model:
Use least-squares regression (e.g., the curve_fit() function in Scipy)
to determine the optimal value(s) for the unknown parameter(s) in each
model (i.e., u in the linear model or k and n in the power law model).
Generate a plot showing the data and the optimal regression curve for
each model. Finally, assess the quality of the fit in your report to the Red
7.4 There is much debate about the proper approach for characterizing the
rheology of blood. A particularly important aspect of this problem is
blood. The shear stress is a measure of the shear force per area applied
establishing a relationship between the shear stress and strain rate for
to blood. Imagine a person sliding on a waterslide, the shear stress is the
force per area that the person is applying to the water underneath them.
The strain rate represents the rate (or time period) at which the fluid
deforms. The magnitude of the deformation is usually normalized by the
original size (or thickness) of the fluid so that the strain rate has units of
You have been hired by the Red Cross to fit strain rate and shear stress data
from a blood sample to two different models, and then assess the quality
of the models for fitting the data. The rheological data is from .
Strain rate (1/s)
Shear stress (dynes/cm2)
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