def test_srinivasan_T(self):
"""
Test calculators.srinivasan_T().
"""
# Make sure to use values of Z such that calculators.srinivasan_T() doesn't use the
# perfect gas law but the correlation, because that is what we're interested in testing.
# Requires that Z > 0.25, which can be ensured by choosing p high enough.
# Use Thermodynamics of Air applet at http://www.engapplets.vt.edu/ to obtain values
# to test against.
p0 = constants.p0
p = 10. * p0
rho0 = constants.rho0
rho = rho0
T_calculated = calculators.srinivasan_T(p, rho)
T_known = 2.6989E3
tolerance = 0.02 * T_known
self.assertTrue(numpy.abs(T_known - T_calculated) < tolerance)
p = 50. * p0
T_calculated = calculators.srinivasan_T(p, rho)
T_known = 8.7745E3
tolerance = 0.02 * T_known
self.assertTrue(numpy.abs(T_known - T_calculated) < tolerance)
def create_figures(u1_list_feet, engauge_list, figure_name, figure_type):
"""
Create one temperature figure and one density ratio figure (like in figures 14.4 and 14.5b
in Anderson pages 609 and 610), for a given input of upstream velocity absicca values.
:param u1_list_feet: A numpy array of upstream velocity values, in ft/s, to use as abscissa values
on the figures. Each line in the array corresponds to the velocity range of a single curve.
:param engauge_list: A list of n by 2 numpy arrays, where each array has n datapoints, generated by
Engauge, for one curve.
:param figure_type: 'temperature' or 'density' depending on which type of figure is to be plotted.
:param figure_name: The name of the output png file (excluding the .png ending).
"""
# Note: Altitude is in ft.
altitude = constants.altitude
number_of_curves = len(altitude)
# Pressure and temperature values are obtained from tables from Huber 1963
# (Anderson reference [165]).
p1_vector = constants.p1_upstream
T1_vector = constants.T1_upstream
# We can assume perfect gas before shock to calculate upstream properties.
rho1_vector = p1_vector / (constants.R * T1_vector)
h1_vector = constants.c_p * T1_vector
density_increase_guess = 10.
rho2_guess_vector = density_increase_guess * rho1_vector
# Need upstream velocity values in m/s to use in calculations.
# Also create a list of vectors to store computation results for temperature and density ratio.
# Since each curve has a different range of upstream velocities the number of values
# computed for temperature and density ratios is different for different curves.
u1_list = []
T2_list = []
rho_ratio_list = []
for i, u1_vector_feet in enumerate(u1_list_feet):
u1_vector = u1_vector_feet * constants.feet_to_m
u1_list.append(u1_vector)
vector_length = len(u1_vector_feet)
T2_vector = numpy.empty(vector_length)
T2_list.append(T2_vector)
rho_ratio_vector = numpy.empty(vector_length)
rho_ratio_list.append(rho_ratio_vector)
# Outer loop decides at what altitude we are at on the figure and so data for one curve is
# created for each passing through the outer loop.
# T2_array = numpy.empty([number_of_curves, vector_length])
# rho_ratio_array = numpy.empty([number_of_curves, vector_length])
for u1_vector, p1, rho1, h1, rho2_guess, T2_vector, rho_ratio_vector in \
zip(u1_list, p1_vector, rho1_vector, h1_vector, rho2_guess_vector, T2_list, rho_ratio_list):
# The inner loop loops over all the u1 velocities on the abscissa of the figure.
for j, u1 in enumerate(u1_vector):
out_dict = calculators.calculate_p_rho_h(u1, p1, rho1, h1, rho2_guess)
p2 = out_dict['pressure']
rho2 = out_dict['density']
T2 = calculators.srinivasan_T(p2, rho2)
T2_vector[j] = T2
rho_ratio_vector[j] = rho2 / rho1
if figure_type == 'temperature':
figure = pyplot.figure()
axes = figure.add_subplot(111)
for u1_vector_feet, T2_vector in zip(u1_list_feet, T2_list):
pyplot.plot(u1_vector_feet, T2_vector, 'b')
for engauge_array in engauge_list:
pyplot.plot(engauge_array[:,0], engauge_array[:,1], 'r')
# for i in range(engauge_list.shape[1]-1):
# curve_index = i+1
# pyplot.plot(engauge_list[:,0], engauge_list[:,curve_index], 'r')
xlabel = r'$u_{1}, ft/s$'
axes.set_xlabel(xlabel)
ylabel = r'$T_{2}, K$'
axes.set_ylabel(ylabel)
print 'Figure ' + figure_name + '.png' + ' has been created.'
pylab.savefig(figure_name+'.png')
if figure_type == 'density':
figure = pyplot.figure()
axes = figure.add_subplot(111)
for u1_vector_feet, rho_ratio_vector in zip(u1_list_feet, rho_ratio_list):
pyplot.plot(u1_vector_feet, rho_ratio_vector, 'b')
for engauge_array in engauge_list:
pyplot.plot(engauge_array[:,0], engauge_array[:,1], 'r')
xlabel = r'$u_{1}, ft/s$'
axes.set_xlabel(xlabel)
ylabel = r'$\frac{\rho_{2}}{\rho_{1}}$'
axes.set_ylabel(ylabel, rotation='horizontal')
print 'Figure ' + figure_name + '.png' + ' has been created.'
pylab.savefig(figure_name+'.png')
