def IterateFlow(flow, membrane, Js, Jw, side, vel):
[dA] = membrane.GetDimensions(["dAm"])
P = flow.data.get("P")
T = flow.data.get("T")
rho = flow.data.get("density")
rho_w = DensityWater(T)
pc_wt = flow.data.get("pc_wt")
m_w_i = flow.data.get("mass_water")
m_NaCl_i = flow.data.get("mass_NaCl")
if side == "draw":
m_w_f = m_w_i + Jw * 24 * dA * rho_w
m_NaCl_f = m_NaCl_i - Js * 24 * 1e-3 * dA
else:
m_w_f = m_w_i - Jw * 24 * dA * rho_w
m_NaCl_f = m_NaCl_i + Js * 24 * 1e-3 * dA
dP = PressureLoss(membrane, pc_wt, rho, side, vel)
next_flow = cl.flow({
"P": P - dP,
"T": T,
"mass_water": m_w_f,
"mass_NaCl": m_NaCl_f,
"mass_total": m_w_f + m_NaCl_f
})
next_flow.CalcPcWt()
next_flow.CalcOsmoticProperties()
next_flow.CalcFlow()
return next_flow
def SizePond(A, D, evaporation, infiltration_loss, m_brine_w, m_brine_NaCl,
rainfall, rho_w):
h = 0
while h < D:
H = [
cl.flow({
"P": P,
"T": T,
"mass_water": m_brine_w,
"mass_NaCl": m_brine_NaCl,
"mass_total": m_brine_w + m_brine_NaCl
})
]
H[0].CalcPcWt()
H[0].CalcOsmoticProperties()
H[0].CalcFlow()
d = 243 #1st September
hh = np.array(H[0].data["flow"] / A)
pc_wts = np.array([H[0].data["pc_wt"]])
iterations = 0
while (h < D and pc_wts[len(pc_wts) - 1] < 0.265):
d += 1
previous_day = H[len(H) - 1]
dd = d % 365
m_NaCl = previous_day.data["mass_NaCl"]
m_w = previous_day.data["mass_water"]
rho = previous_day.data.get("density")
pc_wt = pc_wts[len(pc_wts) - 1]
brine_water = m_brine_w
brine_NaCl = m_brine_NaCl
rain = rainfall[dd] * A * rho_w #kg
evap = evaporation[dd] * A * rho_w #kg
soil_loss_water = A * infiltration_losses[dd] * rho * (
1 - pc_wt) if h > 0 else 0
seepage_NaCl = A * infiltration_losses[
dd] * rho * pc_wt if h > 0 else 0
m_w += max(brine_water + rain - evap - soil_loss_water, 0)
m_NaCl += max(brine_NaCl - soil_loss_water, 0)
m_t = m_w + m_NaCl
pond = cl.pond({
"P": P,
"T": T,
"mass_water": m_w,
"mass_NaCl": m_NaCl,
"mass_total": m_t
})
pond.CalcPcWt()
pc_wts = np.append(pc_wts, pond.data["pc_wt"])
pond.CalcOsmoticProperties()
pond.CalcVolume()
H.append(pond)
V = pond.data["V"] / 1 #L
h = V / A
hh = np.append(hh, h)
iterations += 1
A *= 0.95
print(h, iterations, A)
return [d, hh, iterations, pc_wts]
import MembraneFlow as mf
import numpy as np
import pandas as pd
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
import Reporting as r
T = 298.15
P = 1.01325
RO = {
"recovery_rate": 0.4
}
RO_water = cl.flow({
"pc_wt": 0.0001,
"P": P,
"T": T,
"flow": 128e6 #L/d
})
seawater = cl.flow({
"pc_wt": 0.035,
"P": P,
"T": T,
"flow": RO_water.data["flow"] / RO["recovery_rate"] #MLD
})
seawater.CalcOsmoticProperties()
seawater.CalcMassRate()
RO_water.CalcOsmoticProperties()
RO_water.CalcMassRate()
RO_brine = cl.flow({
"P": P,
"T": T,
import json
fs = open('environmental_data.json', 'r')
data = json.loads(fs.read())
rainfall = data.get("rainfall")
rainfall_avg = data.get("rainfall_avg")
evaporation = data.get("evaporation")
evaporation_avg = data.get("evaporation_avg")
infiltration_losses = data.get("infiltration_losses")
infiltration_losses_avg = data.get("infiltration_losses_avg")
P = 1.01325
T = 273.15 + 25
brine_pc_wt = 0.057 #%wt
brine = cl.flow({"P": P, "T": T, "pc_wt": brine_pc_wt, "flow": 192e6})
brine.CalcOsmoticProperties()
brine.CalcMassRate()
brine_water = brine.data.get("mass_water")
brine_NaCl = brine.data.get("mass_NaCl")
rho_brine = brine.data.get("density")
m_t_brine = brine.data.get("mass_total")
targ_diff_pc_wt = 0.15 #%wt
targ_pond_pc_wt = targ_diff_pc_wt + brine_pc_wt #%wt
print(targ_pond_pc_wt) #0.207
gamma_D = 0.3
gamma_F = 1 - gamma_D
print(gamma_F) #0.7
s)
membrane.CalcElementDimensions()
[dAd, dA] = membrane.GetDimensions(["dAd", "dAm"]) #m^2
Qi = 100 #L/h
Jw = 35 #L/h/m^2
Js = 5 #L/h/m^2
Qf = f.IDF(Qi, Jw, dA)
print(Qi, Qf)
P = 50
T = 273.15
pc_wt = 0.1
Vi = Qi / dAd / 1e3 / 3600 #m/s
flow = cl.flow({"P": P, "T": T, "pc_wt": pc_wt, "flow": Qi})
flow.CalcOsmoticProperties()
flow.CalcMassRate()
Ci = flow.data.get("molar_concentration")
Cf = f.IDC(Qi, Ci, Qf, Js, dA)
print(Ci, Cf)
# def IterateFlow(flow, Jw, Js, side, vel):
# rho = flow.data.get("density")
# rho_w = f.DensityWater(T)
# m_w_i = flow.data.get("mass_water")
# m_NaCl_i = flow.data.get("mass_NaCl")
# if side == "draw":
# m_w_f = m_w_i + Jw*dA*rho_w
# m_NaCl_f = m_NaCl_i - Js*dA
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
Amax = 151 * 1e6 #m^2
T = 298.15
P = 1.01325
fs = open('environmental_data.json', 'r')
data = json.loads(fs.read())
rainfall = data.get("rainfall")
evaporation = data.get("evaporation")
infiltration_losses = data.get("infiltration_losses")
RO = {"recovery_rate": 0.4}
RO_water = cl.flow({
"pc_wt": 0.0001,
"P": P,
"T": T,
"flow": 128 #MLD
})
seawater = cl.flow({
"pc_wt": 0.035,
"P": P,
"T": T,
"flow": RO_water.data["flow"] / RO["recovery_rate"] #MLD
})
seawater.CalcOsmoticProperties()
seawater.CalcMassRate()
RO_water.CalcOsmoticProperties()
RO_water.CalcMassRate()
brine_discharge = cl.flow({
"P": P,
"T": T,
import json
import math
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.colors import BoundaryNorm
from matplotlib.ticker import MaxNLocator
import MembraneFlow as mf
import numpy as np
T = 298.15
P = 1.01325
RO = {"recovery_rate": 0.4}
RO_water = cl.flow({
"pc_wt": 0.0001,
"P": P,
"T": T,
"flow": 128e6 #L/d
})
seawater = cl.flow({
"pc_wt": 0.035,
"P": P,
"T": T,
"flow": RO_water.data["flow"] / RO["recovery_rate"] #MLD
})
seawater.CalcOsmoticProperties()
seawater.CalcMassRate()
RO_water.CalcOsmoticProperties()
RO_water.CalcMassRate()
RO_brine = cl.flow({
"P": P,
"T": T,