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render.py
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# -*- coding: utf-8 -*-
"""
Created on Mon Sep 24 11:50:05 2018
@author: bizgi
"""
import numpy as np
import matplotlib.pyplot as plt
import scipy.interpolate as interpolate
import csv
import pandas as pd
import matplotlib.lines as mlines
def getCase(path, caseTemp, caseVel, caseTime):
#read csv file and stroe values
df = pd.read_csv(path).astype(str)
delta = pd.DataFrame.from_records(df)
# Case velosity
qVel = delta['caseVel'].str.contains(caseVel)
velFiltered = delta[qVel]
# Case Temperature
qTemp = velFiltered ['caseTemp'].str.contains(caseTemp)
tempFiltered = velFiltered[qTemp]
# Case time
qTime = tempFiltered ['caseTime'].str.contains(caseTime)
timeFiltered = tempFiltered[qTime]
# print (timeFiltered['T'])
head = list(timeFiltered)
# data = np.array(timeFiltered).astype(float)
return head, timeFiltered
def plot(path, plotThis):
# path = plotThis['path']
trace = plotThis['trace']
caseVel= ['0.1', '0.2', '0.4', '0.6', '0.8']
caseTemp = ['318', '323', '328', '333', '338']
caseTime = ['d5', 'd10','d15', 'd20', 'd25', 'd30']
label = plotThis['legend']
time = [0, 0.166666667, 0.333333333, 0.5, 0.666666667, 0.833333333, 1]
marker = ['D', '<', '+', '>', 'o', '*', '1', '2', '3', 'v', '^', 'h', 'd']
xLabel = plotThis['xLabel']
yLabel = plotThis['yLabel']
plt.figure()
xData = []
yData = []
if (plotThis['yVal'] == 'Tout'):
if (plotThis['trace'] == 'caseTemp'):
yData = []
xData = []
for i in range (len(plotThis[trace])):
yd = [float(caseTemp[i])]
for j in range(len(plotThis['caseTime'])):
pdata = getCase(path, plotThis['caseTemp'][i], plotThis['caseVel'], plotThis['caseTime'][j])
x = time[j]
y = np.array(pdata[1][plotThis['yVal']]).astype(float)[0]
yd.append(y)
ydD = np.interp(yd, (288, 338), (0 ,1))
yData.append(ydD)
# xData.append([5, 10, 15, 20, 25, 30])
# print (x, y)
print('vel = ', plotThis['caseVel'])
saveName = 'tToutGr'
for n in range(len(yData)):
x = makeSpline(time, yData[n])[0]
y = makeSpline(time, yData[n])[1]
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
elif (plotThis['trace'] == 'caseVel'):
yData = []
xData = []
for i in range (len(plotThis[trace])):
yd = [float(plotThis['caseTemp'])]
for j in range(len(plotThis['caseTime'])):
pdata = getCase(path, plotThis['caseTemp'], plotThis[trace][i], plotThis['caseTime'][j])
x = time[j]
y = np.array(pdata[1][plotThis['yVal']]).astype(float)[0]
yd.append(y)
ydD = np.interp(yd, (288, float(plotThis['caseTemp'])), (0 ,1))
yData.append(ydD)
# xData.append([5, 10, 15, 20, 25, 30])
# print (x, y)
# xData.append([5, 10, 15, 20, 25, 30])
# print (x, y)
print('Temp = ', plotThis['caseTemp'])
saveName = 'tToutRe'
for n in range(len(yData)):
x = makeSpline(time, yData[n])[0]
y = makeSpline(time, yData[n])[1]
# print(y)
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
else:
for i in range(len(plotThis[trace])):
if (trace == 'caseVel'):
pdata = getCase(path, plotThis['caseTemp'], plotThis['caseVel'][i], plotThis['caseTime'])
saveName = 'T=' + plotThis['caseTemp'] + ' t=' + plotThis['caseTime']
# print(pdata)
elif (trace == 'caseTemp'):
pdata = getCase(path, plotThis[trace][i], plotThis['caseVel'], plotThis['caseTime'])
saveName = 'v=' + plotThis['caseVel'] + ' t=' + plotThis['caseTime']
# print(pdata)
elif (trace == 'caseTime'):
pdata = getCase(path, plotThis['caseTemp'], plotThis['caseVel'], plotThis[trace][i])
saveName = 'T=' + plotThis['caseTemp'] + ' v=' + plotThis['caseVel']
# print(pdata)
x = np.array(pdata[1][plotThis['xVal']]).astype(float)
y = np.array(pdata[1][plotThis['yVal']]).astype(float)
# print(x,y)
if (plotThis['non-dimensional'] == 'True'):
# make data non-dimensional
xx = np.interp(x, (x.min(), x.max()), (0 ,1))
if (trace == 'caseTemp'):
flTrace = np.array([float(j) for j in plotThis[trace]])
yy = np.interp(y, (y.min(), flTrace.max() ), (0 ,1))
else:
yy = np.interp(y, (y.min(), (float(plotThis['caseTemp'])+0.15)), (0 ,1))
x1 = makeSpline(xx, yy)[0]
y1 = makeSpline(xx, yy)[1]
plt.plot(x1, y1, marker=marker[i], label = plotThis['legend'][i], markevery=40)
xData.append(xx)
yData.append(yy)
else:
x1 = makeSpline(x, y)[0]
y1 = makeSpline(x, y)[1]
plt.plot(x1, y1, marker=marker[i], label = plotThis['legend'][i], markevery=40)
xData.append(x)
yData.append(y)
# t, c, k = interpolate.splrep(x , y, s=0, k=2)
# xSmooth = np.linspace(min(x), max(x), 200)
# spline = interpolate.BSpline(t, c, k, extrapolate=False)
# plt.plot(xSmooth, spline(xSmooth), label = plotThis['legend'][i], marker=marker[i], markevery=20)
plt.legend(loc=0)
plt.xlabel(xLabel)
plt.ylabel(yLabel)
plt.tight_layout()
if (plotThis['savePlot'] == 'True'):
plt.savefig('.\savedPlots\\' + trace + '-' + saveName+'.png', format='png', dpi=plotThis['saveDpi'])
return xData, yData, xLabel, yLabel, label
# -------------- Plot All Cases -----------------------------------------------
def plotAll():
caseTemp= ['318', '323', '328', '333', '338']
caseVel = ['0.1', '0.2', '0.4', '0.6', '0.8']
caseTime = ['d5', 'd10','d15', 'd20', 'd25', 'd30']
for i in range(len(caseTemp)):
for j in range(len(caseTime)):
plotZTRe = {
'path': 'engelli.csv',
'trace': 'caseVel',
'caseTemp': caseTemp[i],
'caseVel': ['0.1', '0.2', '0.4', '0.6', '0.8'],
'caseTime': caseTime[j],
'xVal': 'Z',
'yVal': 'T',
'legend' : ['Re=210', 'Re=335', 'Re=625', 'Re=1000', 'Re=1270'],
'non-dimensional' : 'True',
'xLabel' : 'Z* [-]',
'yLabel': 'T* [-]'
}
plotZTGR = {
'path': 'engelli.csv',
'trace': 'caseTemp',
'caseTemp': ['318', '323', '328', '333', '338'],
'caseVel': caseVel[i],
'caseTime': caseTime[j],
'xVal': 'Z',
'yVal': 'T',
'legend' : ['Gr=3.1E10', 'Gr=3.7E10', 'Gr=4.2E10', 'Gr=4.7E10', 'Gr=5.2E10'],
'non-dimensional' : 'True',
'xLabel' : 'Z* [-]',
'yLabel': 'T* [-]'
}
plot(plotZTRe)
plot(plotZTGR)
for i in range(len(caseTemp)):
for j in range(len(caseVel)):
plotZTt = {
'path': 'engelli.csv',
'trace': 'caseTime',
'caseTemp': caseTemp[i],
'caseVel': caseVel[j],
'caseTime': ['d5', 'd10','d15', 'd20', 'd25', 'd30'],
'xVal': 'Z',
'yVal': 'T',
'legend' : ['t=5 m', 't=10 m', 't=15 m', 't=20 m', 't=25 m', 't=30 m'],
'non-dimensional' : 'True',
'xLabel' : 'Z* [-]',
'yLabel': 'T* [-]'
}
plot(plotZTt)
#------------------------------------------------------------------------------
#-------------Calculate and Plot Stratification Number ------------------------
def St(path, sData):
pth = path
trace = sData['trace']
caseTemp = sData['caseTemp']
caseVel = sData['caseVel']
caseTime = sData['caseTime']
xLabel = sData['xLabel']
yLabel = sData['yLabel']
label = sData['legend']
tankH = sData['tankHigh']
nodes = sData['numberOfNodes']
marker = ['D', '*', '+', 'v', 'o', '<', '1', '2', '3', 'v', '^', 'h', 'd']
time = [0, 0.166666667, 0.333333333, 0.5, 0.666666667, 0.833333333, 1]
plt.figure()
if (trace == 'caseVel'):
strNumber = []
xData = []
for i in range(len(caseVel)):
strNo = [0]
for j in range(len(caseTime)):
pdata = getCase(pth, caseTemp, caseVel[i], caseTime[j])
T = np.array(pdata[1]['T']).astype(float)
# print('------------------')
zg = []
for k in range(len(T)-1):
# print(k)
zGrad = (T[k+1] - T[k]) / (tankH/(nodes-1))
zg.append(zGrad)
# print(zGrad)
strat = ( np.sum(zg[0:]) / (nodes-1) ) / (float(caseTemp)- 288)
strNo.append(strat)
# print(strat)
print(strNo)
strNumber.append(strNo)
# print('------------------')
# print(strNumber)
for n in range(len(strNumber)):
x = makeSpline(time, strNumber[n])[0]
y = makeSpline(time, strNumber[n])[1]
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
plt.legend(loc=0)
plt.xlabel(xLabel)
plt.ylabel(yLabel)
plt.tight_layout()
yData = strNumber
if (sData['savePlot'] == 'True'):
plt.savefig('.\savedPlots\\' + trace + '- Str' +'.png', format='png', dpi=sData['saveDpi'])
return xData, yData, xLabel, yLabel, label
elif (trace == 'caseTemp'):
strNumber = []
xData = []
for i in range(len(caseTemp)):
strNo = [0]
for j in range(len(caseTime)):
pdata = getCase(pth, caseTemp[i], caseVel, caseTime[j])
T = np.array(pdata[1]['T']).astype(float)
# print(T)
zg = []
for k in range(len(T)-1):
zGrad = (T[k+1] - T[k]) / (tankH/(nodes-1))
zg.append(zGrad)
# print(zGrad)
strat = ( np.sum(zg[0:]) / (nodes-1)) / (float(caseTemp[i])- 288)
strNo.append(strat)
# print(strat)
print(strNo)
strNumber.append(strNo)
# print(strNumber)
for n in range(len(strNumber)):
x = makeSpline(time, strNumber[n])[0]
y = makeSpline(time, strNumber[n])[1]
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
plt.legend(loc= 0)
plt.xlabel(xLabel)
plt.ylabel(yLabel)
plt.tight_layout()
yData = strNumber
if (sData['savePlot'] == 'True'):
plt.savefig('.\savedPlots\\' + trace + '- Str' +'.png', format='png', dpi=sData['saveDpi'])
return xData, yData, xLabel, yLabel, label
#------------------------------------------------------------------------------
#-------------------- Calculate Richardson Number -----------------------------
def Ri(path, sData):
pth = path
trace = sData['trace']
caseTemp = sData['caseTemp']
caseVel = sData['caseVel']
caseTime = sData['caseTime']
xLabel = sData['xLabel']
yLabel = sData['yLabel']
label = sData['legend']
marker = ['D', '*', '+', 'v', 'o', '<', '1', '2', '3', 'v', '^', 'h', 'd']
time = [0, 0.166666667, 0.333333333, 0.5, 0.666666667, 0.833333333, 1]
# Ri = g * Beta * H * (Ttop - Tbottom) / v^2
g = 9.81
H = sData['tankHigh']
betas = {
'318' : 2.86e-4,
'323' : 3.07e-4,
'328' : 3.26e-4,
'333' : 3.46e-4,
'338' : 3.64e-4
}
plt.figure()
if (trace == 'caseVel'):
RiNumber = []
xData = []
for i in range(len(caseVel)):
RiN = [0]
for j in range(len(caseTime)):
pdata = getCase(pth, caseTemp, caseVel[i], caseTime[j])
T = np.array(pdata[1]['T']).astype(float)
Ttop = T[-1]
Tbottom = T[0]
print(Ttop)
print(Tbottom)
beta = betas[caseTemp]
Ri = g * beta * H * (Ttop - Tbottom) / (float(caseVel[i])**2)
print(Ri)
RiN.append(Ri)
RiNumber.append(RiN)
# print (RiNumber)
for n in range(len(RiNumber)):
x = makeSpline(time, RiNumber[n])[0]
y = makeSpline(time, RiNumber[n])[1]
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
plt.legend(loc='upper right')
plt.xlabel(xLabel)
plt.ylabel(yLabel)
plt.tight_layout()
yData = RiNumber
if (sData['savePlot'] == 'True'):
plt.savefig('.\savedPlots\\' + trace + '- Ri' +'.png', format='png', dpi=sData['saveDpi'])
return xData, yData, xLabel, yLabel, label
if (trace == 'caseTemp'):
RiNumber = []
# print(RiNumber)
xData = []
for i in range(len(caseTemp)):
RiN = [0]
print('----' + caseTemp[i])
for j in range(len(caseTime)):
pdata = getCase(pth, caseTemp[i], caseVel, caseTime[j])
T = np.array(pdata[1]['T']).astype(float)
Ttop = T[-1]
Tbottom = T[0]
# print(Ttop)
# print(Tbottom)
beta = betas[caseTemp[i]]
Ri = g * beta * H * (Ttop - Tbottom) / (float(caseVel)**2)
print(Ri)
RiN.append(Ri)
RiNumber.append(RiN)
# print (RiNumber)
for n in range(len(RiNumber)):
x = makeSpline(time, RiNumber[n])[0]
y = makeSpline(time, RiNumber[n])[1]
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
plt.legend(loc='upper right')
plt.xlabel(xLabel)
plt.ylabel(yLabel)
plt.tight_layout()
yData = RiNumber
if (sData['savePlot'] == 'True'):
plt.savefig('.\savedPlots\\' + trace + '- Ri' +'.png', format='png', dpi=sData['saveDpi'])
return xData, yData, xLabel, yLabel, label
#------------------------------------------------------------------------------
#-------------- Discharge Efficiency ------------------------------------------
# Olfa Abdelhak et all. 10.1007/s12273-015-0216-9
# etha = Q_out(t) / Q_st (t=0)
# Q_out (t) = (rho * V * Cp )_out * (Tout - Tin)
# Q_st (t=0) = rho * V * Cp * (Tini - Tin)
def disEff(path, sData):
pth = path
trace = sData['trace']
caseTemp = sData['caseTemp']
caseVel = sData['caseVel']
caseTime = sData['caseTime']
xLabel = sData['xLabel']
yLabel = sData['yLabel']
label = sData['legend']
marker = ['D', '*', '+', 'v', 'o', '<', '1', '2', '3', 'v', '^', 'h', 'd']
times = [300, 600, 900, 1200, 1500, 1800]
time = [ 0.166666667, 0.333333333, 0.5, 0.666666667, 0.833333333, 1]
rhos = {
'318' : 995.2,
'323' : 994.3,
'328' : 993.3,
'333' : 992.3,
'338' : 991.2
}
rho = rhos[caseTemp]
Cps = {
'318' : 4180,
'323' : 4180,
'328' : 4181,
'333' : 4181,
'338' : 4182
}
Cp = Cps[caseTemp]
plt.figure()
if (trace == 'caseTime'):
DisEff = []
xData = []
for i in range(len(caseTime)):
print('-------' + caseTime[i])
Deff = []
for j in range(len(caseVel)):
pdata = getCase(pth, caseTemp, caseVel[j], caseTime[i])
T = np.array(pdata[1]['Tout']).astype(float)
Tm = np.array(pdata[1]['ToutManto']).astype(float)
Tin = 288.15
Tout = T[0]
ToutManto = Tm[0]
H = 1 # m
D = 0.45 # m
volTank = (np.pi * D**2 / 4 ) * H
volOut = float(caseVel[j]) * (np.pi * 0.02**2 / 4) * float(times[i])
volOutManto = 0.02 * (np.pi * 0.02**2 / 4) * float(times[i])
print(Tout)
Qout = volOut * rho * Cp * (Tout - Tin)
Qst =volTank * rho * Cp * (float(caseTemp) + 0.15 - Tin) + (volOutManto*rho * Cp * (float(caseTemp) + 0.15 - ToutManto))
etha = Qout / Qst
print (etha)
Deff.append(etha)
DisEff.append(Deff)
# print (DisEff)
for n in range(len(DisEff)):
plt.plot([210, 335, 625, 1000, 1270], DisEff[n], marker = marker[n], label = label[n])
xData.append([210, 335, 625, 1000, 1270])
plt.legend(loc='lower left')
plt.xlabel(xLabel)
plt.ylabel(yLabel)
yData = DisEff
return xData, yData, xLabel, yLabel, label
if (trace == 'caseVel'):
DisEff = []
xData=[]
for i in range(len(caseVel)):
Deff = []
print('-------' + caseVel[i])
for j in range(len(caseTime)):
pdata = getCase(pth, caseTemp, caseVel[i], caseTime[j])
T = np.array(pdata[1]['Tout']).astype(float)
Tm = np.array(pdata[1]['ToutManto']).astype(float)
Tin = 288.15
Tout = T[0]
ToutManto = Tm[0]
Tini = float(caseTemp)
H = 1 # m
D = 0.45 # m
volTank = (np.pi * D**2 / 4 ) * H
volOut = float(caseVel[i]) * (np.pi * 0.02**2 / 4) * float(times[j])
volOutManto = 0.02 * (np.pi * 0.02**2 / 4) * float(times[j])
# Qmanto = volOutManto * rho * Cp * (Tini +0.15 - ToutManto)
#
# Qout = volOut * rho * Cp * (Tout - Tin)
# Qst = volTank * rho * Cp * (Tini + 0.15 - Tin)
Qmanto = volOutManto * rho * Cp * (Tini +0.15 - ToutManto)
Qout = volOut * rho * Cp * (Tout - Tin)
Qst = volTank * rho * Cp * (Tini + 0.15 - Tin)
print (Qmanto, Qout, Qst)
etha = Qout / (Qst + Qmanto)
print (etha)
Deff.append(etha)
DisEff.append(Deff)
# print (DisEff)
for n in range(len(DisEff)):
x = makeSpline(time, DisEff[n])[0]
y = makeSpline(time, DisEff[n])[1]
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
plt.legend(loc='lower left')
plt.xlabel(xLabel)
plt.ylabel(yLabel)
yData = DisEff
return xData, yData, xLabel, yLabel, label
#------------------------------------------------------------------------------
###############################################################################
# ---- MIX Number -------------------------------------------------------------
###############################################################################
# MIX = (M_str - M_act) / (M_str - M_fullMix)
# Rho = -0.0039*T^2+2.087*T+721.2 -- 288.15 - 338.15
# Cp = 0.0118*T^2-7.3162*T+5313.1-- 288.15 - 338.15
def rho(T):
Rho = -0.0039 * T**2 + 2.087 * T + 721.2
return Rho
def cp(T):
Cp = 0.0118 * T**2 - 7.3162 * T + 5313.1
return Cp
def Mix(path, sData):
pth = path
trace = sData['trace']
caseTemp = sData['caseTemp']
caseVel = sData['caseVel']
caseTime = sData['caseTime']
xLabel = sData['xLabel']
yLabel = sData['yLabel']
label = sData['legend']
marker = ['D', '*', '+', 'v', 'o', '<', '1', '2', '3', 'v', '^', 'h', 'd']
time = [ 0.166666667, 0.333333333, 0.5, 0.666666667, 0.833333333, 1]
# Number of volumes : 15
# each volume
pi = np.pi
H = sData['tankHigh'] # m
D = sData['tankD'] # m
nVol = sData['numberOfVolume']
vol_i = (pi * D**2 / 4 ) * (1/15)
vol = (pi * D**2 / 4 ) * H
# print (vol_i)
if (trace == 'caseVel'):
MixNumber = []
xData = []
for i in range(len(caseVel)):
MixN = []
print('-----', caseVel[i])
for j in range(len(caseTime)):
pdata = getCase(pth, caseTemp, caseVel[i], caseTime[j])
T = np.array(pdata[1]['T']).astype(float)
#-- E_act - M_act --------------------------------------------
TvolAve = []
yi = H/(2*nVol)
yii = [0.016666667, 0.066666667, 0.133333333, 0.2, 0.266666667, 0.333333333, 0.4, 0.466666667, 0.533333333, 0.6, 0.666666667, 0.733333333, 0.8, 0.866666667, 0.9, 0.983333333 ]
E_acti = []
M_acti = []
for k in range(len(T)-1):
# print('kk-------------------', k)
if ( k == 0 ):
vol_i2 = vol_i / 2
Tv = (T[k+1]*vol_i + T[k]*vol_i2) / (vol_i + vol_i2)
Tv=T[k]
elif (k==14):
vol_i2 = vol_i / 2
# Tv = (T[k+1]*vol_i2 + T[k]*vol_i) / (vol_i + vol_i2)
Tv = (T[k+1] + T[k]) / 2
# Tv=T[k+1]
else:
Tv = (T[k+1] + T[k]) / 2
vol_i2 = vol_i
# Tv=T[k+1]
# Tv = (T[k+2] + T[k+1] + T[k]) / 3
TvolAve.append(Tv)
# print('-----')
# print('----------------------', vol_i2)
# E_act = vol_i * rho(Tv) * cp(Tv) * Tv
# M_act = M_act + vol_i * rho(Tv) * cp(Tv) * Tv * yi
E_acti.append(vol_i * rho(Tv) * cp(Tv) * Tv)
M_acti.append(vol_i * rho(Tv) * cp(Tv) * Tv * yi)
yi = yi + H/nVol
# print ('yi ------------------------------ ', yi)
E_act = sum(E_acti)
M_act = sum(M_acti)
# print(TvolAve)
# print('-------' , E_act, '--' , M_act)
# -- E_fullMix - M_fullMix----------------------------------------
Tave_full_mix = np.average(TvolAve)
E_fullMix = vol * rho(Tave_full_mix) * cp(Tave_full_mix) * Tave_full_mix
M_fullMix = 0.5 * E_fullMix
# print(M_fullMix, '--', E_fullMix)
# -- E_str -- M_str -----------------------------------------------
Tcold = np.min(TvolAve)
Thot = np.max(TvolAve)
# E_str = Vcold * rho(Tcold) * cp(Tcold) * Tcold + Vhot * rho(Thot) * cp(Thot) * Thot
# vol = Vcold + Vhot
# two linear eq. solve for Vcold and Vhot
E_str = E_act
A = np.array([[rho(Tcold) * cp(Tcold) * Tcold, rho(Thot) * cp(Thot) * Thot], [1, 1]])
B = np.array([E_str, vol])
sol = np.linalg.solve(A,B)
Vcold = sol[0]
Vhot = sol[1]
ycold = ((Vcold/vol) * H )/ 2
yhot = (Vcold/vol) * H + ((Vhot/vol) * H) / 2
M_str = ycold * Vcold * rho(Tcold) * cp(Tcold) * Tcold + yhot * Vhot * rho(Thot) * cp(Thot) * Thot
Mix = (M_str - M_act) / (M_str - M_fullMix)
# Mix =100* (1 -( (M_str - M_act) / (M_str - M_fullMix) ))
print(Mix)
MixN.append(Mix)
MixNumber.append(MixN)
plt.figure()
for n in range(len(MixNumber)):
x = makeSpline(time, MixNumber[n])[0]
y = makeSpline(time, MixNumber[n])[1]
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
plt.legend(loc='upper left')
plt.xlabel(xLabel)
plt.ylabel(yLabel)
plt.tight_layout()
yData = MixNumber
if (sData['savePlot'] == 'True'):
plt.savefig('.\savedPlots\\' + trace + '- Mix' +'.png', format='png', dpi=sData['saveDpi'])
return xData, yData, xLabel, yLabel, label
if (trace == 'caseTemp'):
MixNumber = []
xData = []
for i in range(len(caseTemp)):
MixN = []
print('-----', caseTemp[i])
for j in range(len(caseTime)):
pdata = getCase(pth, caseTemp[i], caseVel, caseTime[j])
T = np.array(pdata[1]['T']).astype(float)
#-- E_act - M_act --------------------------------------------
TvolAve = []
yi = H/(2*nVol)
yii = [0.016666667, 0.066666667, 0.133333333, 0.2, 0.266666667, 0.333333333, 0.4, 0.466666667, 0.533333333, 0.6, 0.666666667, 0.733333333, 0.8, 0.866666667, 0.9, 0.983333333 ]
E_act = 0
M_act = 0
for k in range(len(T)-1):
Tv = (T[k+1] + T[k]) / 2
# Tv = T[k]
# if (k == 0):
# vol_i = vol_i/ 2
#
# if (k==15):
# vol_i = vol_i / 2
# print (vol_i)
TvolAve.append(Tv)
# print('-----')
# print(yi)
E_act = E_act + vol_i * rho(Tv) * cp(Tv) * Tv
M_act = M_act + vol_i * rho(Tv) * cp(Tv) * Tv * yi
yi = yi + H/nVol
# print (yi)
# print(TvolAve)
# print('-------' , E_act, '--' , M_act)
# -- E_fullMix - M_fullMix----------------------------------------
Tave_full_mix = np.average(TvolAve)
E_fullMix = vol * rho(Tave_full_mix) * cp(Tave_full_mix) * Tave_full_mix
M_fullMix = 0.5 * E_fullMix
# print(M_fullMix, '--', E_fullMix)
# -- E_str -- M_str -----------------------------------------------
Tcold = np.min(TvolAve)
Thot = np.max(TvolAve)
# E_str = Vcold * rho(Tcold) * cp(Tcold) * Tcold + Vhot * rho(Thot) * cp(Thot) * Thot
# vol = Vcold + Vhot
# two linear eq. solve for Vcold and Vhot
E_str = E_act
A = np.array([[rho(Tcold) * cp(Tcold) * Tcold, rho(Thot) * cp(Thot) * Thot], [1, 1]])
B = np.array([E_str, vol])
sol = np.linalg.solve(A,B)
Vcold = sol[0]
Vhot = sol[1]
ycold = ((Vcold/vol) * H )/ 2
yhot = (Vcold/vol) * H + ((Vhot/vol) * H) / 2
M_str = ycold * Vcold * rho(Tcold) * cp(Tcold) * Tcold + yhot * Vhot * rho(Thot) * cp(Thot) * Thot
Mix = (M_str - M_act) / (M_str - M_fullMix)
# Mix =100* (1 -( (M_str - M_act) / (M_str - M_fullMix) ))
print(Mix)
MixN.append(Mix)
MixNumber.append(MixN)
plt.figure()
for n in range(len(MixNumber)):
x = makeSpline(time, MixNumber[n])[0]
y = makeSpline(time, MixNumber[n])[1]
plt.plot(x, y, marker = marker[n], label = label[n], markevery=40)
xData.append(time)
plt.legend(loc='upper left')
plt.xlabel(xLabel)
plt.ylabel(yLabel)
plt.tight_layout()
yData = MixNumber
if (sData['savePlot'] == 'True'):
plt.savefig('.\savedPlots\\' + trace + '- Mix' +'.png', format='png', dpi=sData['saveDpi'])
return xData, yData, xLabel, yLabel, label
#------------------------------------------------------------------------------
def makeSpline(x, y):
t, c, k = interpolate.splrep(x , y, s=0, k=2)
xSmooth = np.linspace(min(x), max(x), 200)
# spline = interpolate.BSpline(t, c, k, extrapolate=False)
spline = interpolate.CubicSpline(x , y, bc_type='natural')
ySmooth = spline(xSmooth)
# print(ySmooth)
ys2 = []
# for i in range(len(ySmooth)) :
# if (ySmooth[i] < 0):
# yy = 0
## yy = 0.9999
# else:
# yy = ySmooth[i]
#
## print(yy)
# ys2.append(yy)
return xSmooth, ySmooth
def validate():
# path = 'knutsen-val.csv'
path = 'zachar-val.csv'
df = pd.read_csv(path).astype(str)
delta = pd.DataFrame.from_records(df)
q1 = delta['C'].str.contains('CFD')
case1 = delta[q1]
q2 = delta['C'].str.contains('Exp')
case2 = delta[q2]
# print(case1X, case1Y)
x1 = np.array(case1['T']).astype(float)
y1 = np.array(case1['Z']).astype(float)
# print(y1)
x2 = np.array(case2['T']).astype(float)
y2 = np.array(case2['Z']).astype(float)
# plt.figure(figsize=(5,8))
fig, ax1 = plt.subplots(figsize=(5,8))
# plt.tight_layout()
plt.rcParams.update({'font.size': 12})
# SMALL_SIZE = 13
# plt.rc('font', size=12)
# plt.rc('axes', titlesize=14)
# plt.rc('axes', labelsize=14)
# plt.rc('xtick', labelsize=14)
# plt.rc('ytick', labelsize=14)
# ax2 = ax1.twinx()
ax1.plot(x1, y1, label='CFD Model', color = 'C0')
ax1.scatter(x2, y2, color = 'C2', label = 'Experiment (Knudsen, S., 2004)')
# ax2.scatter(x2, yy, color='C8', label='Mesh')
# ax2.set_ylabel('s')
ax1.legend(loc=0)
ax1.set_xlabel('T* [-]')
ax1.set_ylabel('Z* [-]')
# plot.legend(loc=0)
sName = 'validate-kun'
# plt.savefig('.\img\\'+ sName + '.png', format='png', dpi=300)
#validate()
def meshInd():
# path = 'knutsen-val.csv'
path = 'zachar-mesh-ind.csv'
df = pd.read_csv(path).astype(str)
delta = pd.DataFrame.from_records(df)
q1 = delta['C'].str.contains('m1')
case1 = delta[q1]
q2 = delta['C'].str.contains('m2')
case2 = delta[q2]
q3 = delta['C'].str.contains('m3')
case3 = delta[q3]
q4 = delta['C'].str.contains('m4')
case4 = delta[q4]
q5 = delta['C'].str.contains('m5')
case5 = delta[q5]
q6 = delta['C'].str.contains('Exp')
case6 = delta[q6]
q7 = delta['C'].str.contains('Num')
case7 = delta[q7]
# print(case1X, case1Y)
y = np.array(case1['Z']).astype(float)
x1 = np.array(case1['T']).astype(float)
x2 = np.array(case2['T']).astype(float)
x3 = np.array(case3['T']).astype(float)
x4 = np.array(case4['T']).astype(float)
x5 = np.array(case5['T']).astype(float)
y0 = np.array(case6['Z']).astype(float)
x0 = np.array(case6['T']).astype(float)
y01 = np.array(case7['Z']).astype(float)
x01 = np.array(case7['T']).astype(float)
# print(y0, x0)
plt.figure(figsize=(5,8))
# fig, ax1 = plt.subplots(figsize=(5,8))
plt.rcParams.update({'font.size': 12})
# SMALL_SIZE = 13
# plt.rc('font', size=12)
plt.rc('axes', titlesize=12)
plt.rc('axes', labelsize=12)
plt.rc('xtick', labelsize=14)
plt.rc('ytick', labelsize=14)
# ax2 = ax1.twinx()
plt.scatter(x0, y0, label='Experiment (Zachar, A., 2003)', color = 'C2')
plt.plot(x1, y, label='CFD - 43768 Mesh', color = 'C0', dashes=[1,1])
plt.plot(x2, y, label='CFD - 101557 Mesh', color = 'C1', dashes=[2,2])
plt.plot(x3, y, label='CFD - 208067 Mesh', color = 'C3')
plt.plot(x4, y, label='CFD - 441111 Mesh', color = 'C5', dashes=[5,1])
plt.plot(x5, y, label='CFD - 686656 Mesh', color = 'C7', dashes=[9,4])
plt.plot(x01, y01, label='Numerical (Zachar, A., 2003)', color = 'C9')
plt.text(0.7 , 0.05, ' $T_{ini}$ = 41 $^oC$ \n $T_{in}$ = 20 $^oC$ \n Q = 1.6 L/min \n t = 1500 s')
# plt.scatter(x0, y0, label='Experiment (Knudsen, S., 2004)', color = 'C0')
#
# plt.plot(x1, y, label='CFD - 70171 Mesh', color = 'C2', dashes=[1,1])
# plt.plot(x2, y, label='CFD - 101507 Mesh', color = 'C1', dashes=[2,2])
# plt.plot(x3, y, label='CFD - 132071 Mesh', color = 'C3')
# plt.plot(x4, y, label='CFD - 154933 Mesh', color = 'C5', dashes=[5,1])
# ax2.scatter(x2, yy, color='C8', label='Mesh')
# ax2.set_ylabel('s')
plt.legend(loc=0)
plt.xlabel('T* [-]')
plt.ylabel('Z* [-]')
plt.tight_layout()
# plot.legend(loc=0)
sName = 'validate-mesh-zac'
# plt.savefig('.\img\\'+ sName + '.png', format='png', dpi=300)
#------ MIX Number Cases ------------------------------------------------------