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docalcHeat.py
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# -*- coding: cp936 -*-
import calcHeat
from numpy import *
import matplotlib.pyplot as plt
import pylab as pl
'''
I = calcHeat.electricCurrent(3.61)
print I
'''
ddtime = 0.001
time = 0
Qh = 0
Qc = 0
Jheat = 0
Q = 0
iend = 0
#定义数组用于画图
arrI = [0 for x in range(10000)]
arrB= [0 for x in range(10000)]
arrQh = [0 for x in range(10000)]
arrQc = [0 for x in range(10000)]
arrJheat = [0 for x in range(10000)]
arrQ = [0 for x in range(10000)]
arrtime = [0 for x in range(10000)]
print 'Qh Qc Jheat'
for i in range(10000):
dt = ddtime
#dt = (i)*ddtime 这种做法是使用退火算法加速计算的
time = time+dt
print ' i = ',i,' time = ',time
arrtime[i] = time
dIdt = abs(calcHeat.dIdt(time))
dBdt = calcHeat.dmagneticFieldStrenth(dIdt)
#磁滞损耗计算
Jc = 1000*10000 #此处应寻找表达式来算
deff = 80*10**(-6)
AscMultiLen = (80.42*416.9+52.78*487.6+30.16*1143.3+18.10*4350)*10**(-6)
dQh = (2*Jc*deff*AscMultiLen*dBdt/(3*pi))*dt
Qh = Qh + dQh
arrQh[i] = Qh
#耦合损耗计算
nt = 0.1 #耦合时间常数 预设为 0.1S
u0 = 4*pi*10**(-7)
Vsc = AscMultiLen
dQc = (Vsc*nt*(dBdt**2)/u0)*dt
Qc = Qc+dQc
arrQc[i] = Qc
#焦耳热的计算
I = calcHeat.electricCurrent(time) #四根线圈的总电流
arrI[i] = I
#troublelen = 400 #参数未知(失超长度)
#temp = 220 #参数未知（失超温度）
r = 2.1*10**(-9) #此处用朱加伍的平均值，实际需要公式 r = calcHeat.RofCu(temp) 来确定
#R = troublelen*r/Acu
s = pi*0.16*10**(-6) #单根铜细丝的截面积
Ra = r*416.9/(80*s) #线圈A中铜的电阻
Rb = r*487.6/(75*s)
Rc = r*1143.3/(120*s)
Rd = r*4350/(180*s)
R = 1/((1/Ra)+(1/Rb)+(1/Rc)+(1/Rd))
dJheat = (I**2)*R*dt
Jheat = Jheat + dJheat
arrJheat[i] = Jheat
Qlast = Q
print Qh,' ',Qc,' ',Jheat
Q = Q+dQh+dQc+dJheat
print Q
arrQ[i] = Q
B = calcHeat.Bvalue(I)
#print B
arrB[i] = B
if Q-Qlast<0.01*Q*dt:
iend = i
break
print 'have been static'
print 'time= ',time
print Q
print 'R = ',R
#画图部分
fig = plt.figure()
ax1 = fig.add_subplot(321)
ax2 = fig.add_subplot(322)
ax3 = fig.add_subplot(323)
ax4 = fig.add_subplot(324)
ax5 = fig.add_subplot(325)
ax6 = fig.add_subplot(326)
ax1.plot(arrtime[:iend],arrI[:iend])
ax2.plot(arrtime[:iend],arrB[:iend])
ax3.plot(arrtime[:iend],arrQh[:iend])
ax4.plot(arrtime[:iend],arrQc[:iend])
ax5.plot(arrtime[:iend],arrJheat[:iend])
ax6.plot(arrtime[:iend],arrQ[:iend])
plt.show()
fig.savefig("docalcHeat.pdf")