def coreZgtc(self, excite, frequency):
"""
'excite' is the excitation level in %
returns a complex impedance
based on empirical fits...this works wit ureal for x
"""
x = excite
inductance = (self.a1*GTC.log(x)+self.a2*x+self.a3)*1e-3
resistance = self.a4*GTC.log(x)+self.a5*x**2+self.a6/GTC.sqrt(x)
return resistance + 1j*2*math.pi*frequency*inductance
def Calculate_Wr(temp_C):
# constants for temperature range -259.3467 C to 0 C
A = [
-2.13534729, #A0
3.18324720, #A1
-1.80143597, #A2
0.71727204, #A3
0.50344027, #A4
-0.61899395, #A5
-0.05332322, #A6
0.28021362, #A7
0.10715224, #A8
-0.29302865, #A9
0.04459872, #A10
0.11868632, #A11
-0.05248134
] #A12
# constants for temperature range 0 C to 961.78 C
C = [
2.78157254, #C0
1.64650916, #C1
-0.13714390, #C2
-0.00649767, #C3
-0.00234444, #C4
0.00511868, #C5
0.00187982, #C6
-0.00204472, #C7
-0.00046122, #C8
0.00045724
] #C9
temp_K = Conv_celsius2kelvin(float(temp_C))
Wr = 1
if (temp_C >= -259.3467) and (temp_C < 0):
for i in range(13):
if i == 0:
sum = A[0]
else:
sum = sum + A[i] * GTC.pow(
(GTC.log(temp_K / 273.16) + 1.5) / 1.5, i)
Wr = GTC.exp(sum)
elif (temp_C >= 0) and (temp_C <= 961.78):
for i in range(10):
if i == 0:
sum = C[0]
else:
sum = sum + C[i] * GTC.pow((temp_K - 754.15) / 481, i)
Wr = sum
else:
print("temperature out of range")
print("Wr({})={}".format(temp_C, Wr))
return Wr
def calculate_Wr_unc(temp_C, verbose=False):
"""
Function calculate reference function Wr for temperature t with uncertainty as a urealtype
:param temp_C:
:param verbose:
:return:
"""
# constants for temperature range -259.3467 C to 0 C
A = [
-2.13534729, # A0
3.18324720, # A1
-1.80143597, # A2
0.71727204, # A3
0.50344027, # A4
-0.61899395, # A5
-0.05332322, # A6
0.28021362, # A7
0.10715224, # A8
-0.29302865, # A9
0.04459872, # A10
0.11868632, # A11
-0.05248134
] # A12
# constants for temperature range 0 C to 961.78 C
C = [
2.78157254, # C0
1.64650916, # C1
-0.13714390, # C2
-0.00649767, # C3
-0.00234444, # C4
0.00511868, # C5
0.00187982, # C6
-0.00204472, # C7
-0.00046122, # C8
0.00045724
] # C9
temp_C = float2GTC(temp_C)
temp_K = conv_celsius2kelvin(temp_C)
Wr = 1
if (temp_C.x >= -259.3467) and (temp_C.x < 0):
for i in range(13):
if i == 0:
sum = A[0]
else:
sum = sum + A[i] * GTC.pow(
(GTC.log(temp_K / 273.16) + 1.5) / 1.5, i)
Wr = GTC.exp(sum)
elif (temp_C.x >= 0) and (temp_C.x <= 961.78):
for i in range(10):
if i == 0:
sum = C[0]
else:
sum = sum + C[i] * GTC.pow((temp_K - 754.15) / 481, i)
Wr = sum
else:
print("temperature out of range")
if verbose:
print("Wr({}, unc std:{})={}, unc std:{}".format(
temp_C.x, temp_C.u, Wr.x, Wr.u))
return Wr
if __name__ == "__main__":
#use fitted impedance coefficients to define behviour of core impedance
this_core = [11.7204144319303, -0.0273771774408702, 29.7364068940134, 3.90272331971033, 0.000243735060998679, 5.8544055409592]
this_CT = CT(this_core)
#should look at GTC output when model inputs have uncertainty from the fits
a1 = GTC.ureal(11.7204144319303,0.346683597109428,34,label ='a1',dependent = True)
a2 = GTC.ureal(-0.0273771774408702,0.0136282110753501,34,label ='a2',dependent = True)
a3 = GTC.ureal(29.7364068940134,0.695696459888704,34,label ='a3',dependent = True)
GTC.set_correlation(-0.826126693986887, a1, a2)
GTC.set_correlation(-0.881067593505553, a1, a3)
GTC.set_correlation(0.551078899199967, a2, a3)
a4 = GTC.ureal(3.90272331971033,0.0859519946028212,34,label ='a4',dependent = True)
a5 = GTC.ureal(0.000243735060998679,0.0000527749402101903,34,label ='a5',dependent = True)
a6 = GTC.ureal(5.8544055409592,0.501146466659668,34,label ='a6',dependent = True)
GTC.set_correlation(-0.679730943215757, a4, a5)
GTC.set_correlation(-0.562016044432279, a4, a6)
GTC.set_correlation(0.303221134084321, a5, a6)
this_core_gtc = [a1,a2,a3,a4,a5,a6]
this_CT_gtc = CT(this_core_gtc)
print GTC.log(a1)
x = GTC.ureal(100,1)
answer = this_CT_gtc.coreZgtc(x, 50)
error = repr(answer.real)
print error
burden = GTC.ucomplex((0.186 + 0.12j),(0.0001,0.0001))
print(this_CT.burdenZgtc(burden, 5.0))