# -*- coding: utf-8 -*-
# BioSTEAM: The Biorefinery Simulation and Techno-Economic Analysis Modules
# Copyright (C) 2020-2023, Yoel Cortes-Pena <yoelcortes@gmail.com>
#
# This module is under the UIUC open-source license. See
# github.com/BioSTEAMDevelopmentGroup/biosteam/blob/master/LICENSE.txt
# for license details.
"""
.. contents:: :local:
.. autoclass:: biosteam.units.distillation.Distillation
.. autoclass:: biosteam.units.distillation.BinaryDistillation
.. autoclass:: biosteam.units.distillation.ShortcutColumn
.. autoclass:: biosteam.units.distillation.MESHDistillation
.. autoclass:: biosteam.units.distillation.AdiabaticMultiStageVLEColumn
References
----------
.. [1] J.D. Seader, E.J. Henley, D.K. Roper. (2011)
Separation Process Principles 3rd Edition. John Wiley & Sons, Inc.
.. [2] M. Duss, R. Taylor. (2018)
Predict Distillation Tray Efficiency. AICHE
.. [3] Green, D. W. Distillation. In Perry’s Chemical Engineers’
Handbook, 9 ed.; McGraw-Hill Education, 2018.
.. [4] Seider, W. D., Lewin, D. R., Seader, J. D., Widagdo, S., Gani, R.,
& Ng, M. K. (2017). Product and Process Design Principles. Wiley.
Cost Accounting and Capital Cost Estimation (Chapter 16)
"""
import numpy as np
import matplotlib.pyplot as plt
import thermosteam as tmo
import flexsolve as flx
from numba import njit
from thermosteam.exceptions import InfeasibleRegion
from thermosteam.equilibrium import DewPoint, BubblePoint
from math import ceil
from scipy.stats import gmean
from .design_tools.specification_factors import (
distillation_column_material_factors,
tray_material_factor_functions,
distillation_tray_type_factor,
material_densities_lb_per_in3)
from . import design_tools as design
from thermosteam import separations
from .. import Unit
from .splitting import MockSplitter
from thermosteam._graphics import vertical_column_graphics
from scipy.optimize import brentq
from warnings import warn
import biosteam as bst
from math import inf, sqrt, exp, pi
from .heat_exchange import HXutility
from ._flash import Flash
from .stage import MultiStageEquilibrium
from thermosteam import separations as sep
__all__ = (
'Distillation',
'BinaryDistillation',
'ShortcutColumn',
'MESHDistillation',
'RigorousDistillation',
'AdiabaticMultiStageVLEColumn',
'Stripper', 'Absorber',
)
# %% Distillation-specific auxliary units
class RefluxDrum(design.PressureVessel, Unit):
"""
Create a reflux drum for surge capacity and separation of entrained phases
after the condenser of a distillation coumn.
Parameters
----------
ins :
Inlet fluid.
outs :
* [0] Vapor product
* [1] Liquid product
vessel_material : str, optional
Vessel construction material. Defaults to 'Carbon steel'.
has_glycol_groups=False : bool
True if glycol groups are present in the mixture.
has_amine_groups=False : bool
True if amine groups are present in the mixture.
vessel_type=None : 'Horizontal' or 'Vertical', optional
Vessel separation type. If not specified, the vessel type will be chosen
according to heuristics.
holdup_time : float, optional
Time it takes to raise liquid to half full [min]. Defaults to 3 min.
surge_time : float, optional
Time it takes to reach from normal to maximum liquied level [min].
Defaults to 2 min.
has_mist_eliminator : bool
True if using a mist eliminator pad.
"""
_N_outs = 2
_design_parameters = Flash._design_parameters
_vertical_vessel_pressure_diameter_and_length = Flash._vertical_vessel_pressure_diameter_and_length
_horizontal_vessel_pressure_diameter_and_length = Flash._horizontal_vessel_pressure_diameter_and_length
_default_vessel_type = Flash._default_vessel_type
vapor = Flash.vapor
liquid = Flash.liquid
def _init(self,
vessel_material='Carbon steel',
has_glycol_groups=False,
has_amine_groups=False,
vessel_type=None,
holdup_time=3,
surge_time=2,
has_mist_eliminator=False
):
#: [str] Vessel construction material
self.vessel_material = vessel_material
#: [bool] True if glycol groups are present in the mixture
self.has_glycol_groups = has_glycol_groups
#: [bool] True if amine groups are present in the mixture
self.has_amine_groups = has_amine_groups
#: [str] 'Horizontal', 'Vertical', or 'Default'
self.vessel_type = vessel_type
#: [float] Time it takes to raise liquid to half full (min)
self.holdup_time = holdup_time
#: [float] Time it takes to reach from normal to maximum liquied level (min)
self.surge_time = surge_time
#: [bool] True if using a mist eliminator pad
self.has_mist_eliminator = has_mist_eliminator
def _run(self):
separations.phase_split(*self.ins, self.outs)
def _design(self):
vap, liq = self.outs
self.no_vessel_needed = vap.isempty() or liq.isempty()
if self.no_vessel_needed:
self.design_results.clear()
else:
vessel_type = self.vessel_type
if vessel_type == 'Vertical':
args = self._vertical_vessel_pressure_diameter_and_length()
elif vessel_type == 'Horizontal':
args = self._horizontal_vessel_pressure_diameter_and_length()
else: raise RuntimeError('unknown vessel type') # pragma: no cover
self.design_results.update(
self._vessel_design(*args)
)
def _cost(self):
D = self.design_results
if not self.no_vessel_needed:
self.baseline_purchase_costs.update(
self._vessel_purchase_cost(D['Weight'], D['Diameter'], D['Length'])
)
# %% Abstract distillation column unit operation
[docs]
class Distillation(Unit, isabstract=True):
r"""
Abstract distillation column class. The Murphree efficiency is based on the
modified O'Connell correlation [2]_. The diameter is based on tray separation
and flooding velocity [1]_ [3]_. Purchase costs are based on correlations
compiled by Warren et. al. [4]_.
Parameters
----------
ins :
Inlet fluids to be mixed into the feed stage.
outs :
* [0] Distillate
* [1] Bottoms product
LHK : tuple[str]
Light and heavy keys.
y_top : float
Molar fraction of light key to the light and heavy keys in the
distillate.
x_bot : float
Molar fraction of light key to the light and heavy keys in the bottoms
product.
Lr : float
Recovery of the light key in the distillate.
Hr : float
Recovery of the heavy key in the bottoms product.
k : float
Ratio of reflux to minimum reflux.
Rmin : float, optional
User enforced minimum reflux ratio. If the actual minimum reflux ratio
is more than `Rmin`, this enforced value is ignored. Defaults to 0.3.
product_specification_format=None : "Composition" or "Recovery"
If composition is used, `y_top` and `x_bot` must be specified.
If recovery is used, `Lr` and `Hr` must be specified.
P=101325 : float
Operating pressure [Pa].
vessel_material : str, optional
Vessel construction material. Defaults to 'Carbon steel'.
tray_material : str, optional
Tray construction material. Defaults to 'Carbon steel'.
tray_type='Sieve' : 'Sieve', 'Valve', or 'Bubble cap'
Tray type.
tray_spacing=450 : float
Typically between 152 to 915 mm.
stage_efficiency=None :
User enforced stage efficiency. If None, stage efficiency is
calculated by the O'Connell correlation [2]_.
velocity_fraction=0.8 : float
Fraction of actual velocity to maximum velocity allowable before
flooding.
foaming_factor=1.0 : float
Must be between 0 to 1.
open_tray_area=0.1 : float
Ratio of open area to active area of a tray.
downcomer_area_fraction=None : float
Enforced fraction of downcomer area to net (total) area of a tray.
If None, estimate ratio based on Oliver's estimation [1]_.
is_divided=False : bool
True if the stripper and rectifier are two separate columns.
"""
line = 'Distillation'
auxiliary_unit_names = (
'condenser', 'reflux_drum', 'top_split',
'pump', 'reboiler', 'bottoms_split',
'vacuum_system'
)
_auxin_index = {
'reflux_drum': 0,
'top_split': 0,
'reboiler': 1,
}
_auxout_index = {
'condenser': 0,
'bottoms_split': 1,
}
_graphics = vertical_column_graphics
_ins_size_is_fixed = False
_N_ins = 1
_N_outs = 2
_units = {'Minimum reflux': 'Ratio',
'Reflux': 'Ratio',
'Rectifier height': 'ft',
'Rectifier diameter': 'ft',
'Rectifier wall thickness': 'in',
'Rectifier weight': 'lb',
'Stripper height': 'ft',
'Stripper diameter': 'ft',
'Stripper wall thickness': 'in',
'Stripper weight': 'lb',
'Height': 'ft',
'Diameter': 'ft',
'Wall thickness': 'in',
'Weight': 'lb'}
_max_agile_design = (
'Actual stages',
'Rectifier stages',
'Stripper stages',
'Rectifier height',
'Rectifier diameter',
'Rectifier wall thickness',
'Rectifier weight',
'Stripper height',
'Stripper diameter',
'Stripper wall thickness',
'Stripper weight',
'Height',
'Diameter',
'Wall thickness',
'Weight',
)
_F_BM_default = {'Rectifier tower': 4.3,
'Stripper tower': 4.3,
'Rectifier trays': 4.3,
'Stripper trays': 4.3,
'Platform and ladders': 1.,
'Rectifier platform and ladders': 1.,
'Stripper platform and ladders': 1.,
'Tower': 4.3,
'Trays': 4.3,
'Vacuum system': 1.}
# [dict] Bounds for results
_bounds = {'Diameter': (3., 24.),
'Height': (27., 170.),
'Weight': (9000., 2.5e6)}
composition_sensitive = False
def _init(self,
LHK, k,
P=101325,
Rmin=0.01,
Lr=None,
Hr=None,
y_top=None,
x_bot=None,
product_specification_format=None,
vessel_material='Carbon steel',
tray_material='Carbon steel',
tray_type='Sieve',
tray_spacing=450,
stage_efficiency=None,
velocity_fraction=0.8,
foaming_factor=1.0,
open_tray_area=0.1,
downcomer_area_fraction=None,
is_divided=False,
vacuum_system_preference='Liquid-ring pump',
condenser_thermo=None,
reboiler_thermo=None,
partial_condenser=True,
weir_height=0.1,
):
self.check_LHK = True
# Operation specifications
self.k = k
self.P = P
self.Rmin = Rmin
self._partial_condenser = partial_condenser
self._set_distillation_product_specifications(product_specification_format,
x_bot, y_top, Lr, Hr)
# Construction specifications
self.vessel_material = vessel_material
self.tray_type = tray_type
self.tray_material = tray_material
self.tray_spacing = tray_spacing
self.weir_height = weir_height
self.stage_efficiency = stage_efficiency
self.velocity_fraction = velocity_fraction
self.foaming_factor = foaming_factor
self.open_tray_area = open_tray_area
self.downcomer_area_fraction = downcomer_area_fraction
self.is_divided = is_divided
self.vacuum_system_preference = vacuum_system_preference
self._load_components(partial_condenser, condenser_thermo, reboiler_thermo)
self.LHK = LHK
def _reset_thermo(self, thermo):
super()._reset_thermo(thermo)
self.LHK = self._LHK
def _load_components(self, partial_condenser, condenser_thermo, reboiler_thermo):
# Setup components
thermo = self.thermo
#: [MultiStream] Overall feed to the distillation column
self.mixed_feed = tmo.MultiStream(None, thermo=thermo)
#: [HXutility] Condenser.
if not condenser_thermo: condenser_thermo = thermo
if partial_condenser:
self.auxiliary(
'condenser', HXutility,
ins='vapor',
thermo=condenser_thermo
)
self.condenser.outlet.phases = ('g', 'l')
self.auxiliary(
'reflux_drum', RefluxDrum,
ins=self.condenser-0,
outs=(self-0, 'condensate')
)
self.condensate = self.reflux_drum-1
else:
self.auxiliary(
'condenser', HXutility,
ins='vapor',
thermo=condenser_thermo
)
self.auxiliary(
'top_split', MockSplitter,
ins = self.condenser-0,
outs=(self-0, 'condensate'),
thermo=condenser_thermo
)
self.condensate = self.top_split-1
self.condenser.inlet.phase = 'g'
if not reboiler_thermo: reboiler_thermo = thermo
self.auxiliary('pump', bst.Pump,
'liquid', thermo=reboiler_thermo,
)
self.auxiliary('reboiler', HXutility,
self.pump-0, thermo=reboiler_thermo
)
self.reboiler.outs[0].phases = ('g', 'l')
self.auxiliary('bottoms_split', bst.PhaseSplitter,
self.reboiler-0, ('boilup', self-1), thermo=reboiler_thermo,
)
@property
def distillate(self):
return self.outs[0]
@property
def bottoms_product(self):
return self.outs[1]
@property
def product_specification_format(self):
return self._product_specification_format
@product_specification_format.setter
def product_specification_format(self, spec):
if spec == 'Composition':
self._Lr = self._Hr = None
elif spec == 'Recovery':
self._y_top = self._x_bot = None
else:
raise AttributeError("product specification format must be either "
"'Composition' or 'Recovery'")
self._product_specification_format = spec
@property
def LHK(self):
"""tuple[str, str] Light and heavy keys."""
return self._LHK
@LHK.setter
def LHK(self, LHK):
# Set light non-key and heavy non-key indices
self._LHK = LHK = tuple(LHK)
intermediate_volatile_chemicals = []
chemicals = self.chemicals
LHK_chemicals = LK_chemical, HK_chemical = self.chemicals[LHK]
Tb_light = LK_chemical.Tb
Tb_heavy = HK_chemical.Tb
LNK = []
HNK = []
gases = []
solids = []
for chemical in chemicals:
ID = chemical.ID
Tb = chemical.Tb
if not Tb or chemical.locked_state in ('l', 's'):
solids.append(ID)
elif chemical.locked_state == 'g':
gases.append(ID)
elif Tb < Tb_light:
LNK.append(ID)
elif Tb > Tb_heavy:
HNK.append(ID)
elif chemical not in LHK_chemicals:
intermediate_volatile_chemicals.append(chemical.ID)
self._LNK = LNK = tuple(LNK)
self._HNK = HNK = tuple(HNK)
self._gases = gases = tuple(gases)
self._solids = solids = tuple(solids)
self._intermediate_volatile_chemicals = tuple(intermediate_volatile_chemicals)
get_index = self.chemicals.get_index
self._LHK_index = get_index(LHK)
self._LNK_index = get_index(LNK)
self._HNK_index = get_index(HNK)
self._gases_index = get_index(gases)
self._solids_index = get_index(solids)
@property
def Rmin(self):
"""User enforced minimum reflux ratio. If the actual minimum reflux ratio is less than `Rmin`. This enforced value is ignored."""
return self._Rmin
@Rmin.setter
def Rmin(self, Rmin):
self._Rmin = Rmin
@property
def y_top(self):
"""Light key composition of at the distillate."""
return self._y_top
@y_top.setter
def y_top(self, y_top):
assert self.product_specification_format == "Composition", (
"product specification format must be 'Composition' "
"to set distillate composition")
assert 0 < y_top < 1, "light key composition in the distillate must be a fraction"
self._y_top = y_top
self._y = np.array([y_top, 1-y_top])
@property
def x_bot(self):
"""Light key composition at the bottoms product."""
return self._x_bot
@x_bot.setter
def x_bot(self, x_bot):
assert self.product_specification_format == "Composition", (
"product specification format must be 'Composition' to set bottoms "
"product composition")
assert 0 < x_bot < 1, "light key composition in the bottoms product must be a fraction"
self._x_bot = x_bot
@property
def Lr(self):
"""Light key recovery in the distillate."""
return self._Lr
@Lr.setter
def Lr(self, Lr):
assert self.product_specification_format == "Recovery", (
"product specification format must be 'Recovery' "
"to set light key recovery")
assert 0 < Lr < 1, "light key recovery in the distillate must be a fraction"
self._Lr = Lr
@property
def Hr(self):
"""Heavy key recovery in the bottoms product."""
return self._Hr
@Hr.setter
def Hr(self, Hr):
if not self.product_specification_format == "Recovery":
raise ValueError(
"product specification format must be 'Recovery' "
"to set heavy key recovery"
)
if not 0 < Hr < 1:
raise ValueError(
"heavy key recovery in the bottoms product must be a fraction"
)
self._Hr = Hr
@property
def weir_height(self):
"""Weir height as a fraction tray spacing."""
return self._WH
@weir_height.setter
def weir_height(self, WS):
if not 0 < WS < 1:
raise ValueError(
"weir height must be a fraction"
)
self._WH = WS
@property
def tray_spacing(self):
return self._TS
@tray_spacing.setter
def tray_spacing(self, TS):
"""Tray spacing (225-600 mm)."""
self._TS = TS
@property
def stage_efficiency(self):
"""Enforced user defined stage efficiency."""
return self._E_eff
@stage_efficiency.setter
def stage_efficiency(self, E_eff):
self._E_eff = E_eff
@property
def velocity_fraction(self):
"""Fraction of actual velocity to maximum velocity allowable before flooding."""
return self._f
@velocity_fraction.setter
def velocity_fraction(self, f):
self._f = f
@property
def foaming_factor(self):
"""Foaming factor (0 to 1)."""
return self._F_F
@foaming_factor.setter
def foaming_factor(self, F_F):
if not 0 <= F_F <= 1:
raise ValueError(f"foaming_factor must be between 0 and 1, ({F_F} given).")
self._F_F = F_F
@property
def open_tray_area(self):
"""Ratio of open area, A_h, to active area, A_a."""
return self._A_ha
@open_tray_area.setter
def open_tray_area(self, A_ha):
self._A_ha = A_ha
@property
def downcomer_area_fraction(self):
"""Enforced fraction of downcomer area to net (total) area.
If None, the fraction is estimated based on heuristics."""
return self._A_dn
@downcomer_area_fraction.setter
def downcomer_area_fraction(self, A_dn):
self._A_dn = A_dn
@property
def tray_type(self):
"""Default 'Sieve'"""
return self._tray_type
@tray_type.setter
def tray_type(self, tray_type):
if tray_type in distillation_tray_type_factor:
self._tray_type = tray_type
F_D = self.F_D
F_D['Trays'] = F_D['Stripper trays'] = F_D['Rectifier trays'] = distillation_tray_type_factor[tray_type]
else:
raise ValueError("tray type must be one of the following: "
f"{', '.join(distillation_tray_type_factor)}")
@property
def tray_material(self):
"""Default 'Carbon steel'"""
return self._tray_material
@tray_material.setter
def tray_material(self, tray_material):
if tray_material in tray_material_factor_functions:
self._tray_material = tray_material
self._F_TM_function = tray_material_factor_functions[tray_material]
else:
raise ValueError("tray material must be one of the following: "
f"{', '.join(tray_material_factor_functions)}")
@property
def vessel_material(self):
"""Default 'Carbon steel'"""
return self._vessel_material
@vessel_material.setter
def vessel_material(self, vessel_material):
if vessel_material in distillation_column_material_factors:
self._vessel_material = vessel_material
F_M = self.F_M
F_M['Rectifier tower'] = F_M['Stripper tower'] = F_M['Tower'] = distillation_column_material_factors[vessel_material]
else:
raise ValueError("vessel material must be one of the following: "
f"{', '.join(distillation_column_material_factors)}")
@property
def is_divided(self):
"""[bool] True if the stripper and rectifier are two separate columns."""
return self._is_divided
@is_divided.setter
def is_divided(self, is_divided):
self._is_divided = is_divided
self.line = 'Divided Distillation Column' if is_divided else "Distillation Column"
def _set_distillation_product_specifications(self,
product_specification_format,
x_bot, y_top, Lr, Hr):
if not product_specification_format:
if (x_bot and y_top) and not (Lr or Hr):
product_specification_format = 'Composition'
elif (Lr and Hr) and not (x_bot or y_top):
product_specification_format = 'Recovery'
else:
raise ValueError("must specify either x_top and y_top, or Lr and Hr")
self._product_specification_format = product_specification_format
if product_specification_format == 'Composition':
self.y_top = y_top
self.x_bot = x_bot
elif product_specification_format == 'Recovery':
self.Lr = Lr
self.Hr = Hr
else:
raise ValueError("product specification format must be either 'Composition' or 'Recovery'")
def _get_y_top_and_x_bot(self):
if self.product_specification_format == 'Composition':
y_top = self.y_top
x_bot = self.x_bot
else:
distillate, bottoms_product = self.outs
LHK = self._LHK
y_top, _ = distillate.get_normalized_mol(LHK)
x_bot, _ = bottoms_product.get_normalized_mol(LHK)
return y_top, x_bot
def _check_mass_balance(self):
distillate, bottoms_product = self.outs
LHK = self._LHK
LK_distillate, HK_distillate = distillate.imol[LHK]
LK_bottoms, HK_bottoms = bottoms_product.imol[LHK]
if self.product_specification_format == 'Composition':
if LK_distillate < 0. or LK_bottoms < 0.:
raise InfeasibleRegion(
region='light key molar fraction',
msg=('the molar fraction of the light key in the feed must be '
'between the bottoms product and distillate compositions '
'(i.e. z_bottoms_LK < z_feed_LK < z_distillate_LK)')
)
if HK_distillate < 0. or HK_bottoms < 0.:
raise InfeasibleRegion(
region='heavy key molar fraction',
msg=('the molar fraction of the heavy key in the feed must be '
'between the distillate and bottoms product compositions '
'(i.e. z_distillate_HK < z_feed_HK < z_bottoms_HK)')
)
if self.check_LHK:
intermediate_chemicals = self._intermediate_volatile_chemicals
intermediate_flows = self.mixed_feed.imol[intermediate_chemicals]
minflow = min(LK_distillate, HK_bottoms)
for flow, chemical in zip(intermediate_flows, intermediate_chemicals):
if flow > minflow:
raise RuntimeError(
"significant intermediate volatile chemical,"
f"'{chemical}', between light and heavy "
f"keys, {', '.join(LHK)}; to ignore this check, "
"set `<Unit>.check_LHK = False`")
def _run_binary_distillation_mass_balance(self):
# Get all important flow rates (both light and heavy keys and non-keys)
feed = self.mixed_feed
feed.mix_from(self.ins)
feed.vle(H=feed.H, P=self.P)
mol = feed.mol
LHK_index = self._LHK_index
LNK_index = self._LNK_index
HNK_index = self._HNK_index
gases_index = self._gases_index
solids_index = self._solids_index
intermediate_chemicals = self._intermediate_volatile_chemicals
intemediates_index = self.chemicals.get_index(intermediate_chemicals)
LHK_mol = mol[LHK_index]
LNK_mol = mol[LNK_index]
HNK_mol = mol[HNK_index]
gases_mol = mol[gases_index]
try:
solids_mol = mol[solids_index]
except:
breakpoint()
# Mass balance for non-keys
distillate, bottoms_product = self.outs
distillate.mol[LNK_index] = LNK_mol
distillate.mol[gases_index] = gases_mol
bottoms_product.mol[HNK_index] = HNK_mol
bottoms_product.mol[solids_index] = solids_mol
# Mass balance for keys
spec = self.product_specification_format
if spec == 'Composition':
# Use lever rule
light, heavy = LHK_mol
F_mol_LHK = light + heavy
zf = light / F_mol_LHK
y_top, y_bot = self._y
x_bot = self._x_bot
distillate_fraction = (zf - x_bot)/(y_top - x_bot)
if distillate_fraction < 1e-6: distillate_fraction = 1e-6
if distillate_fraction > 1 - 1e-6: distillate_fraction = 1 - 1e-6
F_mol_LHK_distillate = F_mol_LHK * distillate_fraction
distillate_LHK_mol = F_mol_LHK_distillate * self._y
max_flows = (1 - 1e-9) * LHK_mol
mask = distillate_LHK_mol > (1 - 1e-9) * max_flows
distillate_LHK_mol[mask] = max_flows[mask]
elif spec == 'Recovery':
distillate_LHK_mol = LHK_mol * [self.Lr, (1 - self.Hr)]
else:
raise ValueError("invalid specification '{spec}'")
distillate.mol[LHK_index] = distillate_LHK_mol
bottoms_product.mol[LHK_index] = LHK_mol - distillate_LHK_mol
distillate.mol[intemediates_index] = \
bottoms_product.mol[intemediates_index] = mol[intemediates_index] / 2
self._check_mass_balance()
def _update_distillate_and_bottoms_temperature(self):
distillate, bottoms_product = self.outs
condenser_distillate = self.distillate
reboiler_bottoms_product = self.reboiler.outs[0]['l']
condenser_distillate.copy_like(distillate)
reboiler_bottoms_product.copy_like(bottoms_product)
self._boilup_bubble_point = bp = reboiler_bottoms_product.bubble_point_at_P()
bottoms_product.T = bp.T
if self._partial_condenser:
self._condenser_operation = p = condenser_distillate.dew_point_at_P()
else:
self._condenser_operation = p = condenser_distillate.bubble_point_at_P()
self.condenser.T = self.condensate.T = condenser_distillate.T = distillate.T = p.T
self.condenser.P = self.condensate.P = condenser_distillate.P = distillate.P = p.P
def _setup(self):
super()._setup()
distillate, bottoms_product = self.outs
self.reboiler.ins[0].P = self.condenser.ins[0].P = self.condenser.outs[0].P = self.mixed_feed.P = distillate.P = bottoms_product.P = self.P
distillate.phase = 'g' if self._partial_condenser else 'l'
bottoms_product.phase = 'l'
def get_feed_quality(self):
feed = self.mixed_feed
data = feed.get_data()
H_feed = feed.H
try: dp = feed.dew_point_at_P()
except: pass
else: feed.T = dp.T
feed.phase = 'g'
H_vap = feed.H
try: bp = feed.bubble_point_at_P()
except: pass
else: feed.T = bp.T
feed.phase = 'l'
H_liq = feed.H
q = (H_vap - H_feed) / (H_vap - H_liq)
feed.set_data(data)
return q
def _run_condenser_and_reboiler(self):
feed = self.mixed_feed
distillate, bottoms_product = self.outs
condenser = self.condenser
reboiler = self.reboiler
R = self.design_results['Reflux']
# Set condenser conditions
self.distillate.mol[:] = distillate.mol
self.F_Mol_distillate = F_mol_distillate = distillate.F_mol
self.F_Mol_condensate = F_mol_condensate = R * F_mol_distillate
p = self._condenser_operation
condensate = self.condensate
condensate.empty()
condensate.imol[p.IDs] = p.x * F_mol_condensate
condensate.T = p.T
condensate.P = p.P
condenser.outs[0].mix_from([condensate, distillate], conserve_phases=True)
vap = condenser.ins[0]
vap.mol = distillate.mol + condensate.mol
T_vap = vap.dew_point_at_P().T
if T_vap < p.T: T_vap = p.T + 0.1
vap.T = T_vap
vap.P = distillate.P
if not self._partial_condenser: self.top_split.ins[0].mix_from(self.top_split.outs)
# Set reboiler conditions
reboiler.outs[0]['l'].copy_flow(bottoms_product)
F_vap_feed = feed.imol['g'].sum()
self.F_Mol_boilup = F_mol_boilup = (R+1)*F_mol_distillate - F_vap_feed
bp = self._boilup_bubble_point
boilup_flow = bp.y * F_mol_boilup
boilup = reboiler.outs[0]['g']
boilup.T = bp.T
boilup.P = bp.P
boilup.imol[bp.IDs] = boilup_flow
liq = reboiler.ins[0]
liq.mix_from([bottoms_product, boilup], energy_balance=False)
liq.phase = 'l'
liq_T = liq.bubble_point_at_P().T
if liq_T > bp.T: liq_T = bp.T - 0.1
liq.T = liq_T
self.pump.ins[0].copy_like(liq)
self.pump.simulate()
self.bottoms_split.simulate()
if self._partial_condenser: self.reflux_drum.simulate()
def _simulate_components(self):
reboiler = self.reboiler
condenser = self.condenser
Q_condenser = condenser.outs[0].H - condenser.ins[0].H
H_out = self.H_out
H_in = self.H_in
Q_overall_boiler = H_out - H_in - Q_condenser
Q_boiler = reboiler.outs[0].H - reboiler.ins[0].H
if Q_boiler < Q_overall_boiler:
liquid = reboiler.ins[0]
H_out_boiler = reboiler.outs[0].H
try:
liquid.H = H_out_boiler - Q_overall_boiler
except:
liquid.phase = 'l'
boiler_kwargs = dict(duty=Q_boiler)
else:
boiler_kwargs = dict(duty=Q_overall_boiler)
condenser_kwargs = dict(duty=Q_condenser)
else:
boiler_kwargs = dict(duty=Q_boiler)
condenser_kwargs = dict(duty=Q_condenser)
reboiler.simulate(
run=False,
design_kwargs=boiler_kwargs,
)
condenser.simulate(
run=False,
design_kwargs=condenser_kwargs,
)
def _compute_N_stages(self):
"""Return a tuple with the actual number of stages for the rectifier and the stripper."""
feed = self.mixed_feed
vap, liq = self.outs
Design = self.design_results
R = Design['Reflux']
N_stages = Design['Theoretical stages']
feed_stage = Design['Theoretical feed stage']
E_eff = self.stage_efficiency
if E_eff:
E_rectifier = E_stripper = E_eff
else:
# Calculate Murphree Efficiency for rectifying section
condensate = self.condensate
mu = condensate.get_property('mu', 'mPa*s')
alpha_LHK_distillate, alpha_LHK_bottoms = self._get_relative_volatilities_LHK()
F_mol_distillate = self.F_Mol_distillate
L_Rmol = self.F_Mol_condensate
V_Rmol = (R+1) * F_mol_distillate
E_rectifier = design.compute_murphree_stage_efficiency(mu,
alpha_LHK_distillate,
L_Rmol, V_Rmol)
# Calculate Murphree Efficiency for stripping section
mu = liq.get_property('mu', 'mPa*s')
V_Smol = self.F_Mol_boilup
L_Smol = R*F_mol_distillate + feed.imol['g'].sum()
E_stripper = design.compute_murphree_stage_efficiency(mu,
alpha_LHK_bottoms,
L_Smol, V_Smol)
# Calculate actual number of stages
mid_stage = feed_stage - 0.5
N_rectifier = np.ceil(mid_stage/E_rectifier)
N_stripper = np.ceil((N_stages-mid_stage)/E_stripper)
return N_rectifier, N_stripper
def _complete_distillation_column_design(self):
distillate, bottoms_product = self.outs
Design = self.design_results
R = Design['Reflux']
Rstages, Sstages = self._compute_N_stages()
is_divided = self.is_divided
TS = self._TS
### Get diameter of rectifying section based on top plate ###
condensate = self.condensate
rho_L = condensate.rho
sigma = condensate.get_property('sigma', 'dyn/cm')
L = condensate.F_mass
V = L*(R+1)/R
vap = self.condenser.ins[0]
V_vol = vap.get_total_flow('m^3/s')
rho_V = vap.rho
F_LV = design.compute_flow_parameter(L, V, rho_V, rho_L)
C_sbf = design.compute_max_capacity_parameter(TS, F_LV)
F_F = self._F_F
A_ha = self._A_ha
U_f = design.compute_max_vapor_velocity(C_sbf, sigma, rho_L, rho_V, F_F, A_ha)
A_dn = self._A_dn
if A_dn is None:
A_dn = design.compute_downcomer_area_fraction(F_LV)
f = self._f
R_diameter = design.compute_tower_diameter(V_vol, U_f, f, A_dn) * 3.28
### Get diameter of stripping section based on feed plate ###
rho_L = bottoms_product.rho
boilup = self.reboiler.outs[0]['g']
V = boilup.F_mass
V_vol = boilup.get_total_flow('m^3/s')
rho_V = boilup.rho
L = bottoms_product.F_mass # To get liquid going down
F_LV = design.compute_flow_parameter(L, V, rho_V, rho_L)
C_sbf = design.compute_max_capacity_parameter(TS, F_LV)
sigma = condensate.get_property('sigma', 'dyn/cm')
U_f = design.compute_max_vapor_velocity(C_sbf, sigma, rho_L, rho_V, F_F, A_ha)
A_dn = self._A_dn
if A_dn is None:
A_dn = design.compute_downcomer_area_fraction(F_LV)
S_diameter = design.compute_tower_diameter(V_vol, U_f, f, A_dn) * 3.28
Po = self.P * 0.000145078 # to psi
rho_M = material_densities_lb_per_in3[self.vessel_material]
if Po < 14.68:
warn('vacuum pressure vessel ASME codes not implemented yet; '
'wall thickness may be inaccurate and stiffening rings may be '
'required', category=RuntimeWarning)
if is_divided:
Design['Rectifier stages'] = Rstages
Design['Stripper stages'] = Sstages
Design['Rectifier height'] = H_R = design.compute_tower_height(TS, Rstages-1) * 3.28
Design['Stripper height'] = H_S = design.compute_tower_height(TS, Sstages-1) * 3.28
Design['Rectifier diameter'] = R_diameter
Design['Stripper diameter'] = S_diameter
Design['Rectifier wall thickness'] = tv = design.compute_tower_wall_thickness(Po, R_diameter, H_R)
Design['Stripper wall thickness'] = tv = design.compute_tower_wall_thickness(Po, S_diameter, H_S)
Design['Rectifier weight'] = design.compute_tower_weight(R_diameter, H_R, tv, rho_M)
Design['Stripper weight'] = design.compute_tower_weight(S_diameter, H_S, tv, rho_M)
else:
Design['Actual stages'] = Rstages + Sstages
Design['Height'] = H = design.compute_tower_height(TS, Rstages+Sstages-2) * 3.28
Design['Diameter'] = Di = max((R_diameter, S_diameter))
Design['Wall thickness'] = tv = design.compute_tower_wall_thickness(Po, Di, H)
Design['Weight'] = design.compute_tower_weight(Di, H, tv, rho_M)
self._simulate_components()
def _cost_vacuum(self, dimensions):
P = self.P
if not P or P > 1e5:
self.vacuum_system = None
else:
volume = 0.
for length, diameter in dimensions:
R = diameter * 0.5
volume += 0.02832 * np.pi * length * R * R # m3
self.vacuum_system = bst.VacuumSystem(
self, self.vacuum_system_preference, vessel_volume=volume,
)
def _cost(self):
Design = self.design_results
Cost = self.baseline_purchase_costs
Cost.clear() # Prevent having previous results if `is_divided` changed
F_M = self.F_M
if self.is_divided:
# Number of trays assuming a partial condenser
N_RT = Design['Rectifier stages'] - 1.
Di_R = Design['Rectifier diameter']
Cost['Rectifier trays'] = design.compute_purchase_cost_of_trays(N_RT, Di_R)
F_M['Rectifier trays'] = self._F_TM_function(Di_R)
N_ST = Design['Stripper stages'] - 1.
Di_S = Design['Stripper diameter']
Cost['Stripper trays'] = design.compute_purchase_cost_of_trays(N_ST, Di_S)
F_M['Stripper trays'] = self._F_TM_function(Di_S)
# Cost vessel assuming T < 800 F
W_R = Design['Rectifier weight'] # in lb
H_R = Design['Rectifier height'] # in ft
Cost['Rectifier tower'] = design.compute_empty_tower_cost(W_R)
Cost['Stripper platform and ladders'] = design.compute_plaform_ladder_cost(Di_R, H_R)
W_S = Design['Stripper weight'] # in lb
H_S = Design['Stripper height'] # in ft
Cost['Stripper tower'] = design.compute_empty_tower_cost(W_S)
Cost['Rectifier platform and ladders'] = design.compute_plaform_ladder_cost(Di_S, H_S)
dimensions = [(H_R, Di_R), (H_S, Di_S)]
else:
# Cost trays assuming a partial condenser
N_T = Design['Actual stages'] - 1.
Di = Design['Diameter']
F_M['Trays'] = self._F_TM_function(Di)
Cost['Trays'] = design.compute_purchase_cost_of_trays(N_T, Di)
# Cost vessel assuming T < 800 F
W = Design['Weight'] # in lb
H = Design['Height'] # in ft
Cost['Tower'] = design.compute_empty_tower_cost(W)
Cost['Platform and ladders'] = design.compute_plaform_ladder_cost(Di, H)
dimensions = [(H, Di)]
self._cost_vacuum(dimensions)
def _update_equilibrium_variables(self):
top, bottom = self.outs
top = top.mol.to_array()
bottom = bottom.mol.to_array()
bottom_dummy = bottom.copy()
mask = bottom == 0
bottom_dummy[mask] = 1e-16
self.S = top / bottom_dummy
self.S[mask] = inf
# %% McCabe-Thiele distillation model utilities
def compute_stages_McCabeThiele(P, operating_line,
x_stages, y_stages, T_stages,
x_limit, solve_Ty):
"""
Use the McCabe-Thiele method to find the specifications at every stage of
the operating line before the maximum liquid molar fraction, `x_limit`.
Append the light key liquid molar fraction, light key vapor molar
fraction, and stage temperatures to `x_stages`, `y_stages` and `T_stages`
respectively.
Parameters
----------
P : float
Pressure [Pa].
operating_line : function
Should return the liquid molar fraction of the light
key given its vapor molar fraction.
x_stages : list
Liquid molar compositions at each stage. Last element
should be the starting point for the next stage.
y_stages : list
Vapor molar compositions at each stage. Last element
should be the starting point for the next stage.
x_limit : float
Maximum value of liquid composition before algorithm stops.
T_stages : list
Temperature at each stage.
solve_Ty : function
Should return T and y given x.
"""
i = 0
yi = y_stages[-1]
xi = x_stages[-1]
while xi < x_limit:
if i > 100:
raise RuntimeError('cannot meet specifications! stages > 100')
i += 1
# Go Up
x = np.array((xi, 1-xi))
T, y = solve_Ty(x, P)
yi = y[0]
y_stages.append(yi)
T_stages.append(T)
# Go Right
xi = operating_line(yi)
if xi > x_limit:
xi = x_limit
x_stages.append(xi)
# %% McCabe-Thiele distillation column unit operation
[docs]
class BinaryDistillation(Distillation, new_graphics=False):
r"""
Create a binary distillation column that assumes all light and heavy non keys
separate to the top and bottoms product respectively. McCabe-Thiele
analysis is used to find both the number of stages and the reflux ratio
given a ratio of actual reflux to minimum reflux [1]_. This assumption
is good for both binary distillation of highly polar compounds and
ternary distillation assuming complete separation of light non-keys
and heavy non-keys with large differences in boiling points. Preliminary
analysis showed that the theoretical number of stages using this method
on Methanol/Glycerol/Water systems is off by less than +-1 stage. Other
methods, such as the Fenske-Underwood-Gilliland method, are more suitable
for hydrocarbons. The Murphree efficiency is based on the modified
O'Connell correlation [2]_. The diameter is based on tray separation
and flooding velocity [1]_ [3]_. Purchase costs are based on correlations
compiled by Warren et. al. [4]_.
Parameters
----------
ins :
Inlet fluids to be mixed into the feed stage.
outs :
* [0] Distillate
* [1] Bottoms product
LHK : tuple[str]
Light and heavy keys.
y_top : float
Molar fraction of light key to the light and heavy keys in the
distillate.
x_bot : float
Molar fraction of light key to the light and heavy keys in the bottoms
product.
Lr : float
Recovery of the light key in the distillate.
Hr : float
Recovery of the heavy key in the bottoms product.
k : float
Ratio of reflux to minimum reflux.
Rmin : float, optional
User enforced minimum reflux ratio. If the actual minimum reflux ratio
is more than `Rmin`, this enforced value is ignored. Defaults to 0.3.
product_specification_format=None : "Composition" or "Recovery"
If composition is used, `y_top` and `x_bot` must be specified.
If recovery is used, `Lr` and `Hr` must be specified.
P=101325 : float
Operating pressure [Pa].
vessel_material : str, optional
Vessel construction material. Defaults to 'Carbon steel'.
tray_material : str, optional
Tray construction material. Defaults to 'Carbon steel'.
tray_type='Sieve' : 'Sieve', 'Valve', or 'Bubble cap'
Tray type.
tray_spacing=450 : float
Typically between 152 to 915 mm.
stage_efficiency=None :
User enforced stage efficiency. If None, stage efficiency is
calculated by the O'Connell correlation [2]_.
velocity_fraction=0.8 : float
Fraction of actual velocity to maximum velocity allowable before
flooding.
foaming_factor=1.0 : float
Must be between 0 to 1.
open_tray_area=0.1 : float
Fraction of open area to active area of a tray.
downcomer_area_fraction=None : float
Enforced fraction of downcomer area to net (total) area of a tray.
If None, estimate ratio based on Oliver's estimation [1]_.
is_divided=False : bool
True if the stripper and rectifier are two separate columns.
Examples
--------
Binary distillation assuming 100% separation on non-keys:
>>> from biosteam.units import BinaryDistillation
>>> from biosteam import Stream, settings
>>> settings.set_thermo(['Water', 'Methanol', 'Glycerol'], cache=True)
>>> feed = Stream('feed', flow=(80, 100, 25))
>>> bp = feed.bubble_point_at_P()
>>> feed.T = bp.T # Feed at bubble point T
>>> D1 = BinaryDistillation('D1', ins=feed,
... outs=('distillate', 'bottoms_product'),
... LHK=('Methanol', 'Water'),
... y_top=0.99, x_bot=0.01, k=2,
... is_divided=True)
>>> D1.simulate()
>>> # See all results
>>> D1.show(T='degC', P='atm', composition=True)
BinaryDistillation: D1
ins...
[0] feed
phase: 'l', T: 76.082 degC, P: 1 atm
composition (%): Water 39
Methanol 48.8
Glycerol 12.2
-------- 205 kmol/hr
outs...
[0] distillate
phase: 'g', T: 64.854 degC, P: 1 atm
composition (%): Water 1
Methanol 99
-------- 100 kmol/hr
[1] bottoms_product
phase: 'l', T: 100.02 degC, P: 1 atm
composition (%): Water 75.4
Methanol 0.761
Glycerol 23.9
-------- 105 kmol/hr
>>> D1.results()
Divided Distillation Column Units D1
Electricity Power kW 0.644
Cost USD/hr 0.0504
Cooling water Duty kJ/hr -4.88e+06
Flow kmol/hr 3.33e+03
Cost USD/hr 1.63
Low pressure steam Duty kJ/hr 1.02e+07
Flow kmol/hr 263
Cost USD/hr 62.6
Design Theoretical feed stage 9
Theoretical stages 13
Minimum reflux Ratio 0.687
Reflux Ratio 1.37
Rectifier stages 15
Stripper stages 13
Rectifier height ft 34.7
Stripper height ft 31.7
Rectifier diameter ft 3.93
Stripper diameter ft 3.19
Rectifier wall thickness in 0.312
Stripper wall thickness in 0.312
Rectifier weight lb 6e+03
Stripper weight lb 4.43e+03
Purchase cost Rectifier trays USD 1.5e+04
Stripper trays USD 1.25e+04
Rectifier tower USD 4.56e+04
Stripper platform and ladders USD 1.39e+04
Stripper tower USD 3.83e+04
Rectifier platform and ladders USD 1.14e+04
Condenser - Floating head USD 3.33e+04
Reflux drum - Horizontal pressur... USD 1.02e+04
Reflux drum - Platform and ladders USD 3.02e+03
Pump - Pump USD 4.37e+03
Pump - Motor USD 368
Reboiler - Floating head USD 2.71e+04
Total purchase cost USD 2.15e+05
Utility cost USD/hr 64.3
Binary distillation with full-condenser
>>> from biosteam.units import BinaryDistillation
>>> from biosteam import Stream, settings
>>> settings.set_thermo(['Water', 'Methanol', 'Glycerol'], cache=True)
>>> feed = Stream('feed', flow=(80, 100, 25))
>>> bp = feed.bubble_point_at_P()
>>> feed.T = bp.T # Feed at bubble point T
>>> D1 = BinaryDistillation('D1', ins=feed,
... outs=('distillate', 'bottoms_product'),
... LHK=('Methanol', 'Water'),
... y_top=0.99, x_bot=0.01, k=2,
... partial_condenser=False,
... is_divided=False)
>>> D1.simulate()
>>> # See all results
>>> D1.results() # doctest: +SKIP
Distillation Column Units D1
Electricity Power kW 2.48
Cost USD/hr 0.194
Cooling water Duty kJ/hr -8.41e+06
Flow kmol/hr 5.74e+03
Cost USD/hr 2.8
Low pressure steam Duty kJ/hr 1.02e+07
Flow kmol/hr 263
Cost USD/hr 62.6
Design Theoretical feed stage 9
Theoretical stages 13
Minimum reflux Ratio 0.687
Reflux Ratio 1.37
Actual stages 28
Height ft 52.4
Diameter ft 3.97
Wall thickness in 0.312
Weight lb 8.9e+03
Purchase cost Trays USD 2.28e+04
Tower USD 5.76e+04
Platform and ladders USD 1.95e+04
Condenser - Floating head USD 4.35e+04
Pump - Pump USD 4.32e+03
Pump - Motor USD 441
Reboiler - Floating head USD 2.71e+04
Total purchase cost USD 1.75e+05
Utility cost USD/hr 65.6
"""
_cache_tolerance = np.array([50., 1e-5, 1e-6, 1e-6, 1e-2, 1e-6], float)
_energy_variable = None
def _run(self):
self._run_binary_distillation_mass_balance()
self._update_distillate_and_bottoms_temperature()
if self.system and self.system.algorithm == 'Phenomena oriented':
self._update_equilibrium_variables()
def reset_cache(self, isdynamic=None):
self._McCabeThiele_args = np.zeros(6)
super().reset_cache()
def _run_McCabeThiele(self):
distillate, bottoms = self.outs
chemicals = self.chemicals
LHK = self._LHK
LHK_index = chemicals.get_index(LHK)
# Feed light key mol fraction
feed = self.mixed_feed
liq_mol = feed.imol['l']
vap_mol = feed.imol['g']
LHK_mol = liq_mol[LHK_index] + vap_mol[LHK_index]
F_mol_LHK = LHK_mol.sum()
zf = LHK_mol[0]/F_mol_LHK
q = self.get_feed_quality()
# Main arguments
P = self.P
k = self.k
y_top, x_bot = self._get_y_top_and_x_bot()
# Cache
args = np.array([P, k, y_top, x_bot, q, zf], float)
if hasattr(self, '_McCabeThiele_args') and (abs(self._McCabeThiele_args - args) < self._cache_tolerance).all(): return
self._McCabeThiele_args = args
# Get R_min and the q_line
if abs(q - 1) < 1e-4: q = 1 - 1e-4
q_line = lambda x: q*x/(q-1) - zf/(q-1)
self._q_line_args = dict(q=q, zf=zf)
solve_Ty = bottoms.get_bubble_point(LHK).solve_Ty
Rmin_intersection = lambda x: q_line(x) - solve_Ty(np.array((x, 1-x)), P)[1][0]
x_Rmin = brentq(Rmin_intersection, 0, 1)
y_Rmin = q_line(x_Rmin)
m = (y_Rmin-y_top)/(x_Rmin-y_top)
Rmin = m/(1-m)
if Rmin < self._Rmin:
Rmin = self._Rmin
R = k * Rmin
# Rectifying section: Inntersects q_line with slope given by R/(R+1)
m1 = R/(R+1)
b1 = y_top-m1*y_top
rs = lambda y: (y - b1)/m1 # -> x
# y_m is the solution to lambda y: y - q_line(rs(y))
self._y_m = y_m = (q*b1 + m1*zf)/(q - m1*(q-1))
self._x_m = x_m = rs(y_m)
# Stripping section: Intersects Rectifying section and q_line and beggins at bottoms liquid composition
m2 = (x_bot-y_m)/(x_bot-x_m)
b2 = y_m-m2*x_m
ss = lambda y: (y-b2)/m2 # -> x
# Data for staircase
self._x_stages = x_stages = [x_bot]
self._y_stages = y_stages = [x_bot]
self._T_stages = T_stages = []
error = [None]
try: compute_stages_McCabeThiele(P, ss, x_stages, y_stages, T_stages, x_m, solve_Ty)
except RuntimeError as e: error[0] = e
yi = y_stages[-1]
xi = rs(yi)
x_stages[-1] = xi if xi < 1 else 0.99999
try: compute_stages_McCabeThiele(P, rs, x_stages, y_stages, T_stages, y_top, solve_Ty)
except RuntimeError as e: error[0] = e
# Find feed stage
N_stages = len(x_stages)
feed_stage = ceil(N_stages/2)
for i in range(len(y_stages)-1):
if y_stages[i] < y_m < y_stages[i+1]:
feed_stage = i+1
# Results
Design = self.design_results
if error[0] is None:
Design['Theoretical feed stage'] = N_stages - feed_stage
Design['Theoretical stages'] = N_stages
else:
Design['Theoretical feed stage'] = '?'
Design['Theoretical stages'] = '100+'
Design['Minimum reflux'] = Rmin
Design['Reflux'] = R
y_stages = np.array(y_stages)
x_stages = np.array(x_stages)
mask = (x_stages >= 0) & (x_stages <= 1) & (y_stages >= 0) & (y_stages <= 1)
self._y_stages = y_stages[mask]
self._x_stages = x_stages[mask]
self._T_stages = np.array(T_stages)[mask[:len(T_stages)]]
raise error[0] from None
Design['Minimum reflux'] = Rmin
Design['Reflux'] = R
def _get_relative_volatilities_LHK(self):
x_stages = self._x_stages
y_stages = self._y_stages
K_light = y_stages[-1]/x_stages[-1]
K_heavy = (1-y_stages[-1])/(1-x_stages[-1])
alpha_LHK_distillate = K_light/K_heavy
K_light = y_stages[0]/x_stages[0]
K_heavy = (1-y_stages[0])/(1-x_stages[0] )
alpha_LHK_bottoms = K_light/K_heavy
return alpha_LHK_distillate, alpha_LHK_bottoms
def _design(self):
self._run_McCabeThiele()
self._run_condenser_and_reboiler()
self._complete_distillation_column_design()
def _plot_stages(self):
"""Plot stages, graphical aid line, and equilibrium curve. The plot does not include operating lines nor a legend."""
vap, liq = self.outs
if not hasattr(self, '_x_stages'):
raise RuntimeError('cannot plot stages without running McCabe Thiele binary distillation')
x_stages = self._x_stages
y_stages = self._y_stages
LHK = self.LHK
LK = self.LHK[0]
P = self.P
# Equilibrium data
x_eq = np.linspace(0, 1, 100)
y_eq = np.zeros(100)
T = np.zeros(100)
n = 0
bp = vap.get_bubble_point(IDs=LHK)
solve_Ty = bp.solve_Ty
for xi in x_eq:
T[n], y = solve_Ty(np.array([xi, 1-xi]), P)
y_eq[n] = y[0]
n += 1
# Set-up graph
plt.figure()
plt.xticks(np.arange(0, 1.1, 0.1), fontsize=12)
plt.yticks(fontsize=12)
plt.xlabel('x (' + LK + ')', fontsize=16)
plt.ylabel('y (' + LK + ')', fontsize=16)
plt.xlim([0, 1])
# Plot stages
x_stairs = []
for x in x_stages:
x_stairs.append(x)
x_stairs.append(x)
y_stairs = []
for y in y_stages:
y_stairs.append(y)
y_stairs.append(y)
try:
x_stairs.pop(-1)
x_stairs.insert(0, y_stairs[0])
except:
pass
plt.plot(x_stairs, y_stairs, '--')
# Graphical aid line
plt.plot([0, 1], [0, 1])
# Vapor equilibrium graph
plt.plot(x_eq, y_eq, lw=2)
def plot_stages(self):
"""Plot the McCabe Thiele Diagram."""
# Plot stages, graphical aid and equilibrium curve
self._plot_stages()
vap, liq = self.outs
Design = self.design_results
if not hasattr(self, '_x_stages'): self._design()
q_args = self._q_line_args
zf = q_args['zf']
q = q_args['q']
q_line = lambda x: q*x/(q-1) - zf/(q-1)
y_top, x_bot = self._get_y_top_and_x_bot()
stages = Design['Theoretical stages']
Rmin = Design['Minimum reflux']
R = Design['Reflux']
feed_stage = Design['Theoretical feed stage']
# q_line
intersect2 = lambda x: x - q_line(x)
x_m2 = brentq(intersect2, 0, 1)
# Graph q-line, Rectifying and Stripping section
plt.plot([self._x_m, x_m2], [self._y_m, x_m2])
plt.plot([self._x_m, y_top], [self._y_m, y_top])
plt.plot([x_bot, self._x_m], [x_bot, self._y_m])
plt.legend([f'Stages: {stages}, Feed: {feed_stage}', 'Graphical aid', 'eq-line', 'q-line', 'ROL', 'SOL'], fontsize=12)
plt.title(f'McCabe Thiele Diagram (Rmin = {Rmin:.2f}, R = {R:.2f})')
plt.show()
return plt
# def _update_net_flow_parameters(self):
# top, bottom = self.outs
# phi = sep.partition(
# self.ins[0], top, bottom, top.chemicals.IDs, self.K, 0.5,
# None, None, True,
# )
# if phi == 1:
# B = np.inf
# else:
# B = phi / (1 - phi)
# self.B = B
# if self.product_specification_format == 'Recovery':
# LK, HK = self._LHK_index
# Lr = self._Lr
# Hr = self._Hr
# self.K[LK] = Lr / ((1 - Lr) * B)
# self.K[HK] = (1 - Hr) / (Hr * B)
# def _update_composition_parameters(self):
# pass
def _create_material_balance_equations(self, composition_sensitive):
top, bottom = self.outs
S = self.S.copy()
fresh_inlets, process_inlets, equations = self._begin_equations(composition_sensitive)
top, bottom, *_ = self.outs
ones = np.ones(self.chemicals.size)
minus_ones = -ones
zeros = np.zeros(self.chemicals.size)
# Overall flows
eq_overall = {}
for i in self.outs: eq_overall[i] = ones
for i in process_inlets: eq_overall[i] = minus_ones
equations.append(
(eq_overall, sum([i.mol for i in fresh_inlets], zeros))
)
# Top to bottom flows
eq_outs = {}
infmask = ~np.isfinite(S)
S[infmask] = 1
eq_outs[top] = coef = -ones
coef[infmask] = 0
eq_outs[bottom] = S
equations.append(
(eq_outs, zeros)
)
return equations
def _get_energy_departure_coefficient(self, stream):
return None
def _create_energy_departure_equations(self):
return []
def _update_nonlinearities(self):
outs = self.outs
data = [i.get_data() for i in outs]
self._run_binary_distillation_mass_balance()
for i, j in zip(outs, data): i.set_data(j)
# %% Fenske-Underwook-Gilliland distillation model utilities
@njit(cache=True)
def geometric_mean(a, b):
return (a * b) ** 0.5
@njit(cache=True)
def compute_mean_volatilities_relative_to_heavy_key(K_distillate, K_bottoms, HK_index):
alpha_distillate = K_distillate / K_distillate[HK_index]
alpha_bottoms = K_bottoms / K_bottoms[HK_index]
alpha_mean = geometric_mean(alpha_distillate,
alpha_bottoms)
return alpha_mean
@njit(cache=True)
def compute_partition_coefficients(y, x):
x[x <= 1e-16] = 1e-16
return y / x
@njit(cache=True)
def compute_distillate_recoveries_Hengsteback_and_Gaddes(d_Lr, b_Hr,
alpha_mean,
LHK_index):
LK_index = LHK_index[0]
alpha_LK = alpha_mean[LK_index]
A_dummy = (1. - b_Hr) / b_Hr
A = np.log10(A_dummy)
B = np.log10(d_Lr / (1. - d_Lr) / A_dummy) / np.log10(alpha_LK)
alpha_mean[alpha_mean < 1e-9] = 1e-9
dummy = 10.**A * alpha_mean**B
dummy[dummy > 1e16] = 1e16
distillate_recoveries = dummy / (1. + dummy)
distillate_recoveries[LHK_index] = [d_Lr, 1. - b_Hr]
distillate_recoveries[distillate_recoveries < 1e-12] = 0.
return distillate_recoveries
@njit(cache=True)
def compute_minimum_theoretical_stages_Fenske(LHK_distillate, LHK_bottoms, alpha_LK):
LK, HK = LHK_distillate
LHK_ratio_distillate = LK / HK
LK, HK = LHK_bottoms
HLK_ratio_bottoms = HK / LK
N = np.log10(LHK_ratio_distillate * HLK_ratio_bottoms) / np.log10(alpha_LK)
return N
@njit(cache=True)
def objective_function_Underwood_constant(theta, q, z_f, alpha_mean):
return (alpha_mean * z_f / (alpha_mean - theta)).sum() - 1.0 + q
@njit(cache=True)
def compute_minimum_reflux_ratio_Underwood(alpha_mean, z_d, theta):
Rm = (alpha_mean * z_d / (alpha_mean - theta)).sum() - 1.0
return Rm
@njit(cache=True)
def compute_theoretical_stages_Gilliland(Nm, Rm, R):
X = (R - Rm) / (R + 1.)
Y = 1. - np.exp((1. + 54.4*X) / (11. + 117.2*X) * (X - 1.) / X**0.5)
N = (Y + Nm) / (1. - Y)
return np.ceil(N)
@njit(cache=True)
def compute_feed_stage_Kirkbride(N, B, D,
feed_HK_over_LK,
z_LK_bottoms,
z_HK_distillate):
m_over_p = (B/D * feed_HK_over_LK * (z_LK_bottoms / z_HK_distillate)**2.) ** 0.206
return np.floor(N / (m_over_p + 1.))
# %% Fenske-Underwook-Gilliland distillation column unit operation
[docs]
class ShortcutColumn(Distillation, new_graphics=False):
r"""
Create a multicomponent distillation column that relies on the
Fenske-Underwood-Gilliland method to solve for the theoretical design
of the distillation column and the separation of non-keys [1]_.The Murphree
efficiency (i.e. column efficiency) is based on the modified O'Connell
correlation [2]_. The diameter is based on tray separation and flooding
velocity [1]_ [3]_. Purchase costs are based on correlations compiled by
Warren et. al. [4]_.
Parameters
----------
ins :
Inlet fluids to be mixed into the feed stage.
outs :
* [0] Distillate
* [1] Bottoms product
LHK : tuple[str]
Light and heavy keys.
y_top : float
Molar fraction of light key to the light and heavy keys in the
distillate.
x_bot : float
Molar fraction of light key to the light and heavy keys in the bottoms
product.
Lr : float
Recovery of the light key in the distillate.
Hr : float
Recovery of the heavy key in the bottoms product.
k : float
Ratio of reflux to minimum reflux.
Rmin : float, optional
User enforced minimum reflux ratio. If the actual minimum reflux ratio is less than `Rmin`, this enforced value is ignored. Defaults to 0.6.
specification="Composition" : "Composition" or "Recovery"
If composition is used, `y_top` and `x_bot` must be specified.
If recovery is used, `Lr` and `Hr` must be specified.
P=101325 : float
Operating pressure [Pa].
vessel_material : str, optional
Vessel construction material. Defaults to 'Carbon steel'.
tray_material : str, optional
Tray construction material. Defaults to 'Carbon steel'.
tray_type='Sieve' : 'Sieve', 'Valve', or 'Bubble cap'
Tray type.
tray_spacing=450 : float
Typically between 152 to 915 mm.
stage_efficiency=None :
User enforced stage efficiency. If None, stage efficiency is
calculated by the O'Connell correlation [2]_.
velocity_fraction=0.8 : float
Fraction of actual velocity to maximum velocity allowable before
flooding.
foaming_factor=1.0 : float
Must be between 0 to 1.
open_tray_area=0.1 : float
Fraction of open area to active area of a tray.
downcomer_area_fraction=None : float
Enforced fraction of downcomer area to net (total) area of a tray.
If None, estimate ratio based on Oliver's estimation [1]_.
is_divided=False : bool
True if the stripper and rectifier are two separate columns.
Examples
--------
>>> from biosteam.units import ShortcutColumn
>>> from biosteam import Stream, settings
>>> settings.set_thermo(['Water', 'Methanol', 'Glycerol'], cache=True)
>>> feed = Stream('feed', flow=(80, 100, 25))
>>> bp = feed.bubble_point_at_P()
>>> feed.T = bp.T # Feed at bubble point T
>>> D1 = ShortcutColumn('D1', ins=feed,
... outs=('distillate', 'bottoms_product'),
... LHK=('Methanol', 'Water'),
... y_top=0.99, x_bot=0.01, k=2,
... is_divided=True)
>>> D1.simulate()
>>> # See all results
>>> D1.show(T='degC', P='atm', composition=True)
ShortcutColumn: D1
ins...
[0] feed
phase: 'l', T: 76.082 degC, P: 1 atm
composition (%): Water 39
Methanol 48.8
Glycerol 12.2
-------- 205 kmol/hr
outs...
[0] distillate
phase: 'g', T: 64.854 degC, P: 1 atm
composition (%): Water 1
Methanol 99
-------- 100 kmol/hr
[1] bottoms_product
phase: 'l', T: 100.02 degC, P: 1 atm
composition (%): Water 75.4
Methanol 0.761
Glycerol 23.9
-------- 105 kmol/hr
>>> D1.results()
Divided Distillation Column Units D1
Electricity Power kW 0.761
Cost USD/hr 0.0595
Cooling water Duty kJ/hr -7.54e+06
Flow kmol/hr 5.15e+03
Cost USD/hr 2.51
Low pressure steam Duty kJ/hr 1.34e+07
Flow kmol/hr 346
Cost USD/hr 82.4
Design Theoretical feed stage 8
Theoretical stages 16
Minimum reflux Ratio 1.06
Reflux Ratio 2.12
Rectifier stages 13
Stripper stages 26
Rectifier height ft 31.7
Stripper height ft 50.9
Rectifier diameter ft 4.52
Stripper diameter ft 3.64
Rectifier wall thickness in 0.312
Stripper wall thickness in 0.312
Rectifier weight lb 6.45e+03
Stripper weight lb 7.93e+03
Purchase cost Rectifier trays USD 1.52e+04
Stripper trays USD 2.01e+04
Rectifier tower USD 4.76e+04
Stripper platform and ladders USD 1.42e+04
Stripper tower USD 5.38e+04
Rectifier platform and ladders USD 1.81e+04
Condenser - Floating head USD 4.07e+04
Reflux drum - Horizontal pressur... USD 1.03e+04
Reflux drum - Platform and ladders USD 3.02e+03
Pump - Pump USD 4.37e+03
Pump - Motor USD 379
Reboiler - Floating head USD 2.98e+04
Total purchase cost USD 2.57e+05
Utility cost USD/hr 84.9
"""
line = 'Distillation'
_ins_size_is_fixed = False
_N_ins = 1
_N_outs = 2
_energy_variable = None
minimum_guess_distillate_recovery = 1e-11
bounded_solver_kwargs = dict(
checkiter=False,
checkbounds=False,
)
iter_solver_kwargs = dict(
xtol=5e-6,
checkiter=False,
checkconvergence=False,
convergenceiter=3,
)
def reset_cache(self, isdynamic=None):
self._vle_chemicals = None
super().reset_cache()
def _run(self):
for i in self.outs: i.empty()
if all([i.isempty() for i in self.ins]): return
# Initial mass balance
self._run_binary_distillation_mass_balance()
# Initialize objects to calculate bubble and dew points
vle_chemicals = self.mixed_feed.vle_chemicals
try:
reset_cache = self._vle_chemicals != vle_chemicals or np.isnan(self._distillate_recoveries).any()
except:
reset_cache = True
if reset_cache:
self._dew_point = DewPoint(vle_chemicals, self.thermo)
self._bubble_point = BubblePoint(vle_chemicals, self.thermo)
self._IDs_vle = self._dew_point.IDs
self._vle_chemicals = vle_chemicals
# Setup light and heavy keys
LHK = [i.ID for i in self.chemicals[self.LHK]]
IDs = self._IDs_vle
self._LHK_vle_index = np.array([IDs.index(i) for i in LHK], dtype=int)
# Add temporary specification
composition_spec = self.product_specification_format == 'Composition'
if composition_spec:
feed = self.mixed_feed
distillate, bottoms = self.outs
LK_index, HK_index = LHK_index = self._LHK_index
LK_feed, HK_feed = feed.mol[LHK_index]
self._Lr = distillate.mol[LK_index] / LK_feed
self._Hr = bottoms.mol[HK_index] / HK_feed
# Set starting point for solving column
if reset_cache:
self._add_trace_heavy_and_light_non_keys_in_products()
self._distillate_recoveries = self._estimate_distillate_recoveries()
else:
distillate_recoveries = self._distillate_recoveries
lb = self.minimum_guess_distillate_recovery
ub = 1 - lb
distillate_recoveries[distillate_recoveries < lb] = lb
distillate_recoveries[distillate_recoveries > ub] = ub
# Solve for new recoveries
try:
self._solve_distillate_recoveries()
except:
if not reset_cache:
self.reset_cache()
self._run()
self._update_distillate_and_bottoms_temperature()
# Remove temporary data
if composition_spec: self._Lr = self._Hr = None
if self.system and self.system.algorithm == 'Phenomena oriented':
self._update_equilibrium_variables()
def plot_stages(self):
raise TypeError('cannot plot stages for shortcut column')
def _design(self):
self._run_FenskeUnderwoodGilliland()
self._run_condenser_and_reboiler()
self._complete_distillation_column_design()
def _run_FenskeUnderwoodGilliland(self):
LHK_index = self._LHK_index
alpha_mean = self._estimate_mean_volatilities_relative_to_heavy_key()
LK_index = self._LHK_vle_index[0]
alpha_LK = alpha_mean[LK_index]
feed, = self.ins
distillate, bottoms = self.outs
Nm = compute_minimum_theoretical_stages_Fenske(distillate.mol[LHK_index],
bottoms.mol[LHK_index],
alpha_LK)
theta = self._solve_Underwood_constant(alpha_mean, alpha_LK)
IDs = self._IDs_vle
z_d = distillate.get_normalized_mol(IDs)
Rm = compute_minimum_reflux_ratio_Underwood(alpha_mean, z_d, theta)
if Rm < self.Rmin: Rm = self.Rmin
R = self.k * Rm
N = compute_theoretical_stages_Gilliland(Nm, Rm, R)
feed_HK, feed_LK = feed.mol[LHK_index]
feed_HK_over_LK = feed_HK / feed_LK
Bs = bottoms.imol[IDs]
Ds = distillate.imol[IDs]
B = Bs.sum()
D = Ds.sum()
LK_index, HK_index = LHK_index
z_LK_bottoms = bottoms.mol[LK_index] / B
z_HK_distillate = distillate.mol[HK_index] / D
feed_stage = compute_feed_stage_Kirkbride(N, B, D,
feed_HK_over_LK,
z_LK_bottoms,
z_HK_distillate)
design = self.design_results
design['Theoretical feed stage'] = N - feed_stage
design['Theoretical stages'] = N
design['Minimum reflux'] = Rm
design['Reflux'] = R
def _get_relative_volatilities_LHK(self):
distillate, bottoms = self.outs
LHK = self.LHK
condensate = self.condensate
K_light, K_heavy = distillate.get_molar_composition(LHK) / condensate.get_molar_composition(LHK)
alpha_LHK_distillate = K_light/K_heavy
boilup = self.reboiler.outs[0]['g']
K_light, K_heavy = boilup.get_molar_composition(LHK) / bottoms.get_molar_composition(LHK)
alpha_LHK_distillate = K_light/K_heavy
alpha_LHK_bottoms = K_light/K_heavy
return alpha_LHK_distillate, alpha_LHK_bottoms
def _solve_Underwood_constant(self, alpha_mean, alpha_LK):
q = self.get_feed_quality()
z_f = self.ins[0].get_normalized_mol(self._IDs_vle)
args = (q, z_f, alpha_mean)
ub = np.inf
lb = -np.inf
bracket = flx.find_bracket(objective_function_Underwood_constant,
1.0, alpha_LK, lb, ub, args)
theta = flx.IQ_interpolation(objective_function_Underwood_constant,
*bracket, args=args, **self.bounded_solver_kwargs)
return theta
def _add_trace_heavy_and_light_non_keys_in_products(self):
distillate, bottoms = self.outs
LNK_index = self._LNK_index
HNK_index = self._HNK_index
feed_mol = self.mixed_feed.mol
LNK_mol = feed_mol[LNK_index]
HNK_mol = feed_mol[HNK_index]
bottoms.mol[LNK_index] = LNK_trace = 0.0001 * LNK_mol
distillate.mol[LNK_index] = LNK_mol - LNK_trace
distillate.mol[HNK_index] = HNK_trace = 0.0001 * HNK_mol
bottoms.mol[HNK_index] = HNK_mol - HNK_trace
def _estimate_mean_volatilities_relative_to_heavy_key(self):
# Mean volatilities taken at distillate and bottoms product
distillate, bottoms = self.outs
dew_point = self._dew_point
bubble_point = self._bubble_point
IDs = self._IDs_vle
z_distillate = distillate.get_normalized_mol(IDs)
z_bottoms = bottoms.get_normalized_mol(IDs)
dp = (dew_point if self._partial_condenser else bubble_point)(z_distillate, P=self.P)
bp = bubble_point(z_bottoms, P=self.P)
K_distillate = compute_partition_coefficients(dp.y, dp.x)
K_bottoms = compute_partition_coefficients(bp.y, bp.x)
HK_index = self._LHK_vle_index[1]
alpha_mean = compute_mean_volatilities_relative_to_heavy_key(
K_distillate, K_bottoms, HK_index
)
return alpha_mean
def _estimate_distillate_recoveries(self):
# Use Hengsteback and Geddes equations
alpha_mean = self._estimate_mean_volatilities_relative_to_heavy_key()
return compute_distillate_recoveries_Hengsteback_and_Gaddes(self.Lr, self.Hr,
alpha_mean,
self._LHK_vle_index)
def _update_distillate_recoveries(self, distillate_recoveries):
feed = self.mixed_feed
distillate, bottoms = self.outs
IDs = self._IDs_vle
feed_mol = feed.imol[IDs]
distillate.imol[IDs] = distillate_mol = distillate_recoveries * feed_mol
bottoms.imol[IDs] = feed_mol - distillate_mol
def _solve_distillate_recoveries(self):
distillate_recoveries = self._distillate_recoveries
flx.wegstein(self._recompute_distillate_recoveries,
distillate_recoveries,**self.iter_solver_kwargs)
def _recompute_distillate_recoveries(self, distillate_recoveries):
if np.logical_or(distillate_recoveries > 1., distillate_recoveries < 0.).any():
raise InfeasibleRegion('distillate composition')
self._update_distillate_recoveries(distillate_recoveries)
distillate_recoveries = self._estimate_distillate_recoveries()
if hasattr(self, '_distillate_recoveries_hook'):
self._distillate_recoveries_hook(self._IDs_vle, distillate_recoveries)
self._distillate_recoveries = distillate_recoveries
return distillate_recoveries
_get_energy_departure_coefficient = BinaryDistillation._get_energy_departure_coefficient
_create_energy_departure_equations = BinaryDistillation._create_energy_departure_equations
_create_material_balance_equations = BinaryDistillation._create_material_balance_equations
# _update_net_flow_parameters = BinaryDistillation._update_net_flow_parameters
# def _update_composition_parameters(self):
# mol = sum([i.mol for i in self.ins]).to_array()
# LHK_index = self._LHK_index
# LHK_mol = mol[LHK_index]
# light, heavy = LHK_mol
# F_mol_LHK = light + heavy
# zf = light / F_mol_LHK
# y_top, y_bot = self._y
# x_bot = self._x_bot
# distillate_fraction = (zf - x_bot)/(y_top - x_bot)
# if distillate_fraction < 1e-16: distillate_fraction = 1e-16
# if distillate_fraction > 1 - 1e-16: distillate_fraction = 1 - 1e-16
# F_mol_LHK_distillate = F_mol_LHK * distillate_fraction
# distillate_LHK_mol = F_mol_LHK_distillate * self._y
# max_flows = (1 - 1e-16) * LHK_mol
# mask = distillate_LHK_mol > (1 - 1e-16) * max_flows
# distillate_LHK_mol[mask] = max_flows[mask]
# self._Lr = distillate_LHK_mol[0] / LHK_mol[0]
# self._Hr = distillate_LHK_mol[1] / LHK_mol[1]
# self._distillate_recoveries = split = self._estimate_distillate_recoveries()
# top = mol * split
# bottom = mol - top
# y = top / top.sum()
# x = bottom / bottom.sum()
# x[x == 0] = 1e-16
# bottom[bottom == 0] = 1e-16
# self.K = y / x
def _update_nonlinearities(self):
mol = sum([i.mol for i in self.outs]).to_array()
if self.product_specification_format == 'Composition':
LHK_index = self._LHK_index
LHK_mol = mol[LHK_index]
light, heavy = LHK_mol
F_mol_LHK = light + heavy
zf = light / F_mol_LHK
y_top, y_bot = self._y
x_bot = self._x_bot
distillate_fraction = (zf - x_bot)/(y_top - x_bot)
if distillate_fraction < 1e-16: distillate_fraction = 1e-16
if distillate_fraction > 1 - 1e-16: distillate_fraction = 1 - 1e-16
F_mol_LHK_distillate = F_mol_LHK * distillate_fraction
distillate_LHK_mol = F_mol_LHK_distillate * self._y
max_flows = (1 - 1e-16) * LHK_mol
mask = distillate_LHK_mol > (1 - 1e-16) * max_flows
distillate_LHK_mol[mask] = max_flows[mask]
self._Lr = distillate_LHK_mol[0] / LHK_mol[0]
self._Hr = distillate_LHK_mol[1] / LHK_mol[1]
self._distillate_recoveries = split = self._estimate_distillate_recoveries()
top = mol * split
bottom = mol - top
bottom_dummy = bottom.copy()
mask = bottom_dummy == 0
bottom_dummy[mask] = 1e-16
self.S = top / bottom_dummy
self.S[mask] = inf
# s_top, s_bottom = self.outs
# s_dummy = s_top.copy()
# s_dummy.mol = top
# s_top.T = (s_dummy.dew_point_at_P() if self._partial_condenser else s_dummy.bubble_point_at_P()).T
# s_dummy.mol = bottom
# s_bottom.T = s_dummy.bubble_point_at_P().T
# %% Rigorous absorption/stripping column
[docs]
class AdiabaticMultiStageVLEColumn(MultiStageEquilibrium):
r"""
Create an adsorption or stripping column without a reboiler/condenser.
The diameter is based on tray separation and flooding velocity.
Purchase costs are based on correlations compiled by Warren et. al.
Parameters
----------
ins :
* [0] Liquid
* [1] Vapor
outs :
* [0] Vapor
* [1] Liquid
P : float
Operating pressure [Pa].
vessel_material : str, optional
Vessel construction material. Defaults to 'Carbon steel'.
tray_material : str, optional
Tray construction material. Defaults to 'Carbon steel'.
tray_type='Sieve' : 'Sieve', 'Valve', or 'Bubble cap'
Tray type.
tray_spacing=450 : float
Typically between 152 to 915 mm.
stage_efficiency=None :
User enforced stage efficiency. If None, stage efficiency is
calculated by the O'Connell correlation [2]_.
velocity_fraction=0.8 : float
Fraction of actual velocity to maximum velocity allowable before
flooding.
foaming_factor=1.0 : float
Must be between 0 to 1.
open_tray_area=0.1 : float
Fraction of open area to active area of a tray.
downcomer_area_fraction=None : float
Enforced fraction of downcomer area to net (total) area of a tray.
If None, estimate ratio based on Oliver's estimation [1]_.
Examples
--------
>>> import biosteam as bst
>>> bst.settings.set_thermo(['AceticAcid', 'EthylAcetate', 'Water', 'MTBE'], cache=True)
>>> feed = bst.Stream('feed', Water=75, AceticAcid=5, MTBE=20, T=320)
>>> steam = bst.Stream('steam', Water=100, phase='g', T=390)
>>> absorber = bst.Absorber(None,
... N_stages=2, ins=[feed, steam],
... solute="AceticAcid", outs=['vapor', 'liquid']
... )
>>> absorber.simulate()
>>> absorber.show()
AdiabaticMultiStageVLEColumn
ins...
[0] feed
phase: 'l', T: 320 K, P: 101325 Pa
flow (kmol/hr): AceticAcid 5
Water 75
MTBE 20
[1] steam
phase: 'g', T: 390 K, P: 101325 Pa
flow (kmol/hr): Water 100
outs...
[0] vapor
phase: 'g', T: 366.33 K, P: 101325 Pa
flow (kmol/hr): AceticAcid 3.71
Water 73.8
MTBE 20
[1] liquid
phase: 'l', T: 372.87 K, P: 101325 Pa
flow (kmol/hr): AceticAcid 1.29
Water 101
MTBE 0.00031
>>> absorber.results()
Absorber Units
Design Theoretical stages 2
Actual stages 4
Height ft 19.9
Diameter ft 3
Wall thickness in 0.312
Weight lb 2.71e+03
Purchase cost Trays USD 5.59e+03
Tower USD 2.91e+04
Platform and ladders USD 7.52e+03
Total purchase cost USD 4.23e+04
Utility cost USD/hr 0
"""
_graphics = vertical_column_graphics
_ins_size_is_fixed = False
_N_ins = 2
_N_outs = 2
_units = {'Height': 'ft',
'Diameter': 'ft',
'Wall thickness': 'in',
'Weight': 'lb'}
_max_agile_design = (
'Actual stages',
'Height',
'Diameter',
'Wall thickness',
'Weight',
)
_F_BM_default = {
'Platform and ladders': 1,
'Tower': 4.3,
'Trays': 4.3,
}
# [dict] Bounds for results
_bounds = {'Diameter': (3., 24.),
'Height': (27., 170.),
'Weight': (9000., 2.5e6)}
_side_draw_names = ('vapor_side_draws', 'liquid_side_draws')
def _init(self,
N_stages,
solute, # Needed to compute the Murphree stage efficiency
feed_stages=None,
vapor_side_draws=None,
liquid_side_draws=None,
P=101325,
partition_data=None,
vessel_material='Carbon steel',
tray_material='Carbon steel',
tray_type='Sieve',
tray_spacing=450,
stage_efficiency=None,
velocity_fraction=0.8,
foaming_factor=1.0,
open_tray_area=0.1,
downcomer_area_fraction=None,
weir_height=0.1,
use_cache=None,
collapsed_init=False,
method=None,
):
super()._init(N_stages=N_stages, feed_stages=feed_stages,
top_side_draws=vapor_side_draws,
bottom_side_draws=liquid_side_draws,
partition_data=partition_data,
phases=("g", "l"), collapsed_init=collapsed_init,
P=P, use_cache=use_cache, method=method)
# Construction specifications
self.solute = solute
self.vessel_material = vessel_material
self.tray_type = tray_type
self.tray_material = tray_material
self.tray_spacing = tray_spacing
self.stage_efficiency = stage_efficiency
self.velocity_fraction = velocity_fraction
self.foaming_factor = foaming_factor
self.open_tray_area = open_tray_area
self.downcomer_area_fraction = downcomer_area_fraction
self.weir_height = weir_height
self._last_args = (
self.N_stages, self.feed_stages, self.vapor_side_draws,
self.liquid_side_draws, self.use_cache, *self._ins,
self.partition_data, self.P, self.collapsed_init,
)
def _setup(self):
super()._setup()
args = (self.N_stages, self.feed_stages, self.vapor_side_draws,
self.liquid_side_draws, self.use_cache, *self._ins,
self.partition_data, self.P, self.collapsed_init)
if args != self._last_args:
MultiStageEquilibrium._init(
self, N_stages=self.N_stages,
feed_stages=self.feed_stages,
phases=('g', 'l'), P=self.P,
top_side_draws=self.vapor_side_draws,
bottom_side_draws=self.liquid_side_draws,
partition_data=self.partition_data,
use_cache=self.use_cache,
collapsed_init=self.collapsed_init,
)
self._last_args = args
def reset_cache(self, isdynamic=None):
self._last_args = None
super().reset_cache()
@property
def vapor(self):
return self.outs[0]
@property
def liquid(self):
return self.outs[1]
weir_height = Distillation.weir_height
tray_spacing = Distillation.tray_spacing
stage_efficiency = Distillation.stage_efficiency
velocity_fraction = Distillation.velocity_fraction
foaming_factor = Distillation.foaming_factor
open_tray_area = Distillation.open_tray_area
downcomer_area_fraction = Distillation.downcomer_area_fraction
tray_type = Distillation.tray_type
tray_material = Distillation.tray_material
vessel_material = Distillation.vessel_material
def _actual_stages(self):
"""Return a tuple with the actual number of stages for the rectifier and the stripper."""
eff = self.stage_efficiency
if eff is None:
# Calculate Murphree Efficiency
vapor, liquid = self.outs
mu = liquid.get_property('mu', 'mPa*s')
alpha = self._get_relative_volatilities()
L_Rmol = liquid.F_mol
V_Rmol = vapor.F_mol
eff = design.compute_murphree_stage_efficiency(
mu, alpha, L_Rmol, V_Rmol
)
# Calculate actual number of stages
return np.ceil(self.N_stages / eff)
def _get_relative_volatilities(self):
stages = self.stages
IDs = stages[0].partition.IDs
solute = self.solute
index = IDs.index(solute)
K = gmean([i.partition.K[index] for i in stages])
if self.liquid.imol[solute] > self.vapor.imol[solute]:
self.line = "Stripper"
alpha = 1 / K
else:
self.line = "Absorber"
alpha = K
return alpha
def _design(self):
vapor_out, liquid_out = self.outs
Design = self.design_results
TS = self._TS
A_ha = self._A_ha
F_F = self._F_F
f = self._f
### Get diameter of column based on outlets (assuming they are comparable to each stages) ###
rho_L = liquid_out.rho
V = vapor_out.F_mass
V_vol = vapor_out.get_total_flow('m^3/s')
rho_V = vapor_out.rho
L = liquid_out.F_mass # To get liquid going down
F_LV = design.compute_flow_parameter(L, V, rho_V, rho_L)
C_sbf = design.compute_max_capacity_parameter(TS, F_LV)
sigma = liquid_out.get_property('sigma', 'dyn/cm')
U_f = design.compute_max_vapor_velocity(C_sbf, sigma, rho_L, rho_V, F_F, A_ha)
A_dn = self._A_dn
if A_dn is None:
A_dn = design.compute_downcomer_area_fraction(F_LV)
diameter = design.compute_tower_diameter(V_vol, U_f, f, A_dn) * 3.28
Po = self.P * 0.000145078 # to psi
rho_M = material_densities_lb_per_in3[self.vessel_material]
if Po < 14.68:
warn('vacuum pressure vessel ASME codes not implemented yet; '
'wall thickness may be inaccurate and stiffening rings may be '
'required', category=RuntimeWarning)
Design['Theoretical stages'] = self.N_stages
Design['Actual stages'] = actual_stages = self._actual_stages()
Design['Height'] = H = design.compute_tower_height(TS, actual_stages) * 3.28
Design['Diameter'] = Di = diameter
Design['Wall thickness'] = tv = design.compute_tower_wall_thickness(Po, Di, H)
Design['Weight'] = design.compute_tower_weight(Di, H, tv, rho_M)
def _cost(self):
Design = self.design_results
Cost = self.baseline_purchase_costs
F_M = self.F_M
# Cost trays
N_T = Design['Actual stages']
Di = Design['Diameter']
F_M['Trays'] = self._F_TM_function(Di)
Cost['Trays'] = design.compute_purchase_cost_of_trays(N_T, Di)
# Cost vessel assuming T < 800 F
W = Design['Weight'] # in lb
H = Design['Height'] # in ft
Cost['Tower'] = design.compute_empty_tower_cost(W)
Cost['Platform and ladders'] = design.compute_plaform_ladder_cost(Di, H)
Stripper = Absorber = AdiabaticMultiStageVLEColumn
# %% Rigorous distillation column based on MESH (Mass, Equilibrium, Summation, and Enthalpy) equations
[docs]
class MESHDistillation(MultiStageEquilibrium, new_graphics=False):
r"""
Create a distillation column that rigorously converges MESH
(Mass, Equilibrium, Summation, and Enthalpy) equations.
Parameters
----------
ins :
Inlet fluids to be mixed into the feed stage.
outs :
* [0] Distillate
* [1] Bottoms product
* [...] Vapor side draws
* [...] Liquid side draws
LHK : tuple[str]
IDs of light and heavy keys. The stage efficiency is estimated based on the
relative volatility of the light and heavy keys.
boilup : float
Vapor to liquid flow rate at the reboiler.
reflux : float
Liquid to vapor flow rate at the condenser.
N_stages : int
Number of stages.
feed_stages : tuple[int]
Stage at which each inlet enters, respectively
vapor_side_draws : tuple[tuple[int]]
Stage number and split fraction pairs.
liquid_side_draws : tuple[tuple[int]]
Stage number and split fraction pairs.
P=101325 : float
Operating pressure [Pa].
vessel_material : str, optional
Vessel construction material. Defaults to 'Carbon steel'.
tray_material : str, optional
Tray construction material. Defaults to 'Carbon steel'.
tray_type='Sieve' : 'Sieve', 'Valve', or 'Bubble cap'
Tray type.
tray_spacing=450 : float
Typically between 152 to 915 mm.
stage_efficiency=None :
User enforced stage efficiency. If None, stage efficiency is
calculated by the O'Connell correlation [2]_.
velocity_fraction=0.8 : float
Fraction of actual velocity to maximum velocity allowable before
flooding.
foaming_factor=1.0 : float
Must be between 0 to 1.
open_tray_area=0.1 : float
Fraction of open area to active area of a tray.
downcomer_area_fraction=None : float
Enforced fraction of downcomer area to net (total) area of a tray.
If None, estimate ratio based on Oliver's estimation [1]_.
is_divided=False : bool
True if the stripper and rectifier are two separate columns.
Examples
--------
Simulate distillation column with 5 stages, a 0.673 reflux ratio,
2.57 boilup ratio, and feed at stage 2:
>>> import biosteam as bst
>>> bst.settings.set_thermo(['Water', 'Ethanol'], cache=True)
>>> feed = bst.Stream('feed', Ethanol=80, Water=100, T=80.215 + 273.15)
>>> D1 = bst.MESHDistillation(None, N_stages=5, ins=[feed], feed_stages=[2],
... outs=['vapor', 'liquid'],
... reflux=0.673, boilup=2.57,
... LHK=('Ethanol', 'Water'),
... )
>>> D1.simulate()
>>> vapor, liquid = D1.outs
>>> vapor.imol['Ethanol'] / feed.imol['Ethanol']
0.96
>>> vapor.imol['Ethanol'] / vapor.F_mol
0.69
>>> D1.results()
Distillation Units
Electricity Power kW 0.574
Cost USD/hr 0.0449
Cooling water Duty kJ/hr -2.98e+06
Flow kmol/hr 2.03e+03
Cost USD/hr 0.992
Low pressure steam Duty kJ/hr 7.8e+06
Flow kmol/hr 202
Cost USD/hr 48
Design Theoretical stages 5
Actual stages 7
Height ft 24.3
Diameter ft 3.32
Wall thickness in 0.312
Weight lb 3.63e+03
Purchase cost Trays USD 8.11e+03
Tower USD 3.43e+04
Platform and ladders USD 9.43e+03
Condenser - Floating head USD 2.36e+04
Reflux drum - Vertical pressure ... USD 1.29e+04
Reflux drum - Platform and ladders USD 3.89e+03
Pump - Pump USD 4.35e+03
Pump - Motor USD 358
Reboiler - Floating head USD 2.34e+04
Total purchase cost USD 1.2e+05
Utility cost USD/hr 49
Simulate distillation column with a full condenser, 5 stages, a 0.673 reflux ratio,
2.57 boilup ratio, and feed at stage 2:
>>> import biosteam as bst
>>> bst.settings.set_thermo(['Water', 'Ethanol'], cache=True)
>>> feed = bst.Stream('feed', Ethanol=80, Water=100, T=80.215 + 273.15)
>>> D1 = bst.MESHDistillation(None, N_stages=5, ins=[feed], feed_stages=[2],
... outs=['vapor', 'liquid', 'distillate'],
... reflux=0.673, boilup=2.57,
... LHK=('Ethanol', 'Water'),
... full_condenser=True,
... )
>>> D1.simulate()
>>> vapor, liquid, distillate = D1.outs
>>> distillate.imol['Ethanol'] / feed.imol['Ethanol']
0.81
>>> distillate.imol['Ethanol'] / distillate.F_mol
0.70
>>> D1.results()
Distillation Units
Electricity Power kW 0.918
Cost USD/hr 0.0718
Cooling water Duty kJ/hr -9.13e+06
Flow kmol/hr 6.24e+03
Cost USD/hr 3.04
Low pressure steam Duty kJ/hr 9.62e+06
Flow kmol/hr 249
Cost USD/hr 59.2
Design Theoretical stages 5
Actual stages 6
Height ft 22.9
Diameter ft 3.82
Wall thickness in 0.312
Weight lb 4e+03
Purchase cost Trays USD 7.58e+03
Tower USD 3.62e+04
Platform and ladders USD 9.8e+03
Condenser - Floating head USD 3.5e+04
Pump - Pump USD 4.33e+03
Pump - Motor USD 390
Reboiler - Floating head USD 2.41e+04
Total purchase cost USD 1.17e+05
Utility cost USD/hr 62.3
Notes
-----
The convergence algorithm decouples the equilibrium relationships,
mass balances, and energy balances using a custom version of the Wang-Henke
bubble point method. This algorithm is authored by Yoel Cortes-Pena, but is
not yet peer reviewed. The main difference is that the tridiagonal matrix of
mass balances across stages is used to solve for flow rates instead of mass
fractions.
The initialization algorithm first converges a "collapsed" column without
adiabatic stages which have no feeds or side draws. This collapsed column
is initialized by solving for liquid and vapor flow rates assuming no phase
change across adiabatic stages and unity partition coefficients at
reboilers/condensers (in which case the stripping factor is equal to the
boil-up ratio). Then, top and bottom stage temperatures are assumed to be
the bubble point and dew point of the fed mixture and the temperature
across stages are linearly interpolated. The partition coefficients in
all stages are assumed to be equal to the feed bubble point.
The Murphree efficiency (i.e. stage efficiency) is based on the
modified O'Connell correlation [2]_. The diameter is based on tray
separation and flooding velocity [1]_ [3]_. Purchase costs are based on
correlations compiled by Warren et. al. [4]_.
"""
auxiliary_unit_names = (
'condenser', 'reflux_drum', 'top_split',
'pump', 'reboiler', 'bottoms_split',
'vacuum_system'
)
line = 'Distillation'
_ins_size_is_fixed = False
_outs_size_is_fixed = False
_N_ins = 1
_N_outs = 2
_bounds = AdiabaticMultiStageVLEColumn._bounds
_side_draw_names = AdiabaticMultiStageVLEColumn._side_draw_names
_F_BM_default = AdiabaticMultiStageVLEColumn._F_BM_default
_max_agile_design = AdiabaticMultiStageVLEColumn._max_agile_design
_units = AdiabaticMultiStageVLEColumn._units
weir_height = Distillation.weir_height
tray_spacing = Distillation.tray_spacing
stage_efficiency = Distillation.stage_efficiency
velocity_fraction = Distillation.velocity_fraction
foaming_factor = Distillation.foaming_factor
open_tray_area = Distillation.open_tray_area
downcomer_area_fraction = Distillation.downcomer_area_fraction
tray_type = Distillation.tray_type
tray_material = Distillation.tray_material
vessel_material = Distillation.vessel_material
def _init(self,
LHK, N_stages, feed_stages,
reflux=None, boilup=None,
P=101325,
vapor_side_draws=None, liquid_side_draws=None,
stage_reactions=None,
vessel_material='Carbon steel',
tray_material='Carbon steel',
tray_type='Sieve',
tray_spacing=450,
stage_efficiency=None,
velocity_fraction=0.8,
foaming_factor=1.0,
open_tray_area=0.1,
weir_height=0.1,
downcomer_area_fraction=None,
vacuum_system_preference='Liquid-ring pump',
partition_data=None,
full_condenser=None,
collapsed_init=None,
use_cache=None,
algorithm=None,
method=None,
inside_out=None,
maxiter=None,
stage_specifications=None,
):
if full_condenser:
if liquid_side_draws is None:
liquid_side_draws = {}
if 0 not in liquid_side_draws:
if reflux is None:
liquid_side_draws[0] = 1.
else:
liquid_side_draws[0] = reflux / (1 + reflux)
reflux = inf # Boil-up is 0
self.LHK = LHK
if stage_specifications is None: stage_specifications = {}
if reflux is not None:
stage_specifications[0] = ('Reflux', reflux)
if boilup is not None:
stage_specifications[-1] = ('Boilup', boilup)
super()._init(N_stages=N_stages, feed_stages=feed_stages,
top_side_draws=vapor_side_draws,
bottom_side_draws=liquid_side_draws,
partition_data=partition_data,
phases=("g", "l"), P=P, use_cache=use_cache,
stage_specifications=stage_specifications,
stage_reactions=stage_reactions,
collapsed_init=collapsed_init,
inside_out=inside_out,
algorithm=algorithm,
method=method,
maxiter=maxiter)
# Construction specifications
self.weir_height = weir_height
self.vessel_material = vessel_material
self.tray_type = tray_type
self.tray_material = tray_material
self.tray_spacing = tray_spacing
self.stage_efficiency = stage_efficiency
self.velocity_fraction = velocity_fraction
self.foaming_factor = foaming_factor
self.open_tray_area = open_tray_area
self.downcomer_area_fraction = downcomer_area_fraction
self.vacuum_system_preference = vacuum_system_preference
self._load_components()
self._last_args = (
self.N_stages, self.feed_stages, self.vapor_side_draws,
self.liquid_side_draws, self.use_cache, *self._ins,
self.partition_data, self.P, self.stage_specifications,
)
@property
def reflux(self):
if 0 in self.stage_specifications:
name, value = self.stage_specifications[0]
if name == 'Reflux': return value
@reflux.setter
def reflux(self, reflux):
self.stage_specifications[0] = ('Reflux', reflux)
@property
def boilup(self):
if -1 in self.stage_specifications:
name, value = self.stage_specifications[-1]
if name == 'Boilup': return value
else:
last_stage = self.N_stages - 1
name, value = self.stage_specifications[last_stage]
if name == 'Boilup': return value
@boilup.setter
def boilup(self, boilup):
self.stage_specifications[-1] = ('Boilup', boilup)
def _setup(self):
super()._setup()
args = (self.N_stages, self.feed_stages, self.vapor_side_draws,
self.liquid_side_draws, self.use_cache, *self._ins,
self.partition_data, self.P, self.stage_specifications)
if args != self._last_args:
MultiStageEquilibrium._init(
self, N_stages=self.N_stages,
feed_stages=self.feed_stages,
phases=('g', 'l'), P=self.P,
top_side_draws=self.vapor_side_draws,
bottom_side_draws=self.liquid_side_draws,
partition_data=self.partition_data,
stage_specifications=self.stage_specifications,
stage_reactions=self.stage_reactions,
use_cache=self.use_cache,
)
self._last_args = args
def _load_components(self):
# Setup components
thermo = self.thermo
reflux = self.reflux
#: [HXutility] Condenser.
if reflux is None: # No condenser
self.condenser = self.reflux_drum = self.top_split = None
self.condensate = self.stages[0].outs[1]
elif reflux == inf: # Full condenser
self.reflux_drum = None
self.auxiliary(
'condenser', HXutility,
ins='vapor',
thermo=thermo,
)
self.auxiliary(
'top_split', MockSplitter,
ins = self.condenser-0,
outs=(self-2, 'condensate'),
thermo=thermo,
)
self.condensate = self.top_split-1
self.condenser.inlet.phase = 'g'
elif reflux == 0:
self.condenser = self.reflux_drum = self.top_split = None
self.condensate = self.stages[0].outs[1]
else: # Partial condenser
self.top_split = None
self.auxiliary(
'condenser', HXutility,
ins='vapor',
thermo=thermo,
)
self.condenser.outlet.phases = ('g', 'l')
self.auxiliary(
'reflux_drum', RefluxDrum,
ins=self.condenser-0,
outs=(self-0, 'condensate')
)
self.condensate = self.reflux_drum-1
self.condenser.inlet.phase = 'g'
self.auxiliary('pump', bst.Pump,
'liquid', thermo=thermo,
)
self.auxiliary('reboiler', HXutility,
self.pump-0, thermo=thermo,
)
self.reboiler.outs[0].phases = ('g', 'l')
self.auxiliary('bottoms_split', bst.PhaseSplitter,
self.reboiler-0, ('boilup', self-1), thermo=thermo,
)
def plot_stages(self):
raise TypeError('cannot plot stages for shortcut column')
def _actual_stages(self):
"""Return a tuple with the actual number of stages for the rectifier and the stripper."""
eff = self.stage_efficiency
if eff is None:
# Calculate Murphree Efficiency
eff = 1
stages = self.stages
IDs = stages[0].partition.IDs
LK, HK = self.LHK
LI = IDs.index(LK)
HI = IDs.index(HK)
N_stages = 0
for i in stages:
try:
vapor, liquid = i.partition.outs
mu = liquid.get_property('mu', 'mPa*s')
alpha = i.partition.K[LI] / i.partition.K[HI]
L_Rmol = liquid.F_mol
V_Rmol = vapor.F_mol
eff *= design.compute_murphree_stage_efficiency(
mu, alpha, L_Rmol, V_Rmol
)
N_stages += 1
except:
N_stages += i.partition.B in (0, inf)
eff = eff ** (1 / N_stages)
return N_stages, np.ceil(N_stages / eff)
else:
return self.N_stages, np.ceil(self.N_stages / eff)
def update_liquid_holdup(self):
diameter = self.estimate_diameter()
hw = weir_height = self._TS * self.weir_height * 0.0393701 # mm to inches
area = diameter * diameter * pi / 4
b = 2/3
partitions = self.partitions
for i in self.stage_reactions:
partition = partitions[i]
vapor, liquid = partition.outs
if vapor.isempty():
Ks = 0
elif liquid.isempty():
partition.reaction.liquid_volume = 0
continue
else:
rho_V = vapor.rho
rho_L = liquid.rho
active_area = area * (1 - 2 * partition.downcomer_area_fraction)
Ua = vapor.get_total_flow('ft3/s') / active_area
Ks = Ua * sqrt(rho_V / (rho_L - rho_V)) # Capacity parameter
Phi_e = exp(-4.257 * Ks**0.91) # Effective relative froth density
Lw = 0.73 * diameter * 12 # Weir length [in] assuming Ad/A = 0.1
# TODO: Compute weir length or other Ad/A
qL = liquid.get_total_flow('gal/min')
CL = 0.362 + 0.317 * exp(-3.5 * weir_height)
hL = Phi_e * (hw + CL * (qL / (Lw * Phi_e)) ** b) # equivalent height of clear liquid holdup [in]
partition.reaction.liquid_volume = hL * area * 0.00236155 # m3
def estimate_diameter(self): # ft
diameters = []
TS = self._TS
A_ha = self._A_ha
F_F = self._F_F
f = self._f
for i in self.stages:
vapor, liquid = i.partition.outs
if liquid.isempty() or vapor.isempty(): continue
rho_L = liquid.rho
V = vapor.F_mass
V_vol = vapor.get_total_flow('m^3/s')
rho_V = vapor.rho
L = liquid.F_mass # To get liquid going down
sigma = liquid.get_property('sigma', 'dyn/cm')
F_LV = design.compute_flow_parameter(L, V, rho_V, rho_L)
C_sbf = design.compute_max_capacity_parameter(TS, F_LV)
U_f = design.compute_max_vapor_velocity(C_sbf, sigma, rho_L, rho_V, F_F, A_ha)
A_dn = self._A_dn
if A_dn is None: i.partition.downcomer_area_fraction = A_dn = design.compute_downcomer_area_fraction(F_LV)
diameters.append(
design.compute_tower_diameter(V_vol, U_f, f, A_dn)
)
return max(diameters) * 3.28 # ft
def _design(self):
self._simulate_condenser_and_reboiler()
Design = self.design_results
### Get maximum required diameter of column across stages ###
Po = self.P * 0.000145078 # to psi
rho_M = material_densities_lb_per_in3[self.vessel_material]
if Po < 14.68:
warn('vacuum pressure vessel ASME codes not implemented yet; '
'wall thickness may be inaccurate and stiffening rings may be '
'required', category=RuntimeWarning)
N_theoretical, N_actual = self._actual_stages()
TS = self._TS
Design['Theoretical stages'] = N_theoretical
Design['Actual stages'] = actual_stages = N_actual - (bool(self.condenser) + bool(self.reboiler))
Design['Height'] = H = design.compute_tower_height(TS, actual_stages) * 3.28
Design['Diameter'] = Di = self.estimate_diameter()
Design['Wall thickness'] = tv = design.compute_tower_wall_thickness(Po, Di, H)
Design['Weight'] = design.compute_tower_weight(Di, H, tv, rho_M)
def _simulate_condenser_and_reboiler(self):
top = self.stages[0]
bottom = self.stages[-1]
reboiler = self.reboiler
condenser = self.condenser
reflux_drum = self.reflux_drum
top_split = self.top_split
# Set condenser conditions
if condenser:
condenser.simulate_as_auxiliary_exchanger(top.ins, top.outs, vle=False)
# Set reboiler conditions
reboiler.simulate_as_auxiliary_exchanger(bottom.ins, bottom.outs, vle=False)
liq = reboiler.ins[0]
self.pump.ins[0].copy_like(liq)
self.pump.simulate()
self.bottoms_split.simulate()
if reflux_drum:
reflux_drum.simulate()
elif top_split:
splitter = self.stages[0].splitters[-1]
top_split.ins[0].copy_like(splitter.ins[0])
for i, j in zip(top_split.ins + top_split.outs, splitter.ins + splitter.outs):
i.copy_like(j)
def _cost(self):
Design = self.design_results
Cost = self.baseline_purchase_costs
F_M = self.F_M
# Cost trays assuming a partial condenser
N_T = Design['Actual stages'] - 1.
Di = Design['Diameter']
F_M['Trays'] = self._F_TM_function(Di)
Cost['Trays'] = design.compute_purchase_cost_of_trays(N_T, Di)
# Cost vessel assuming T < 800 F
W = Design['Weight'] # in lb
H = Design['Height'] # in ft
Cost['Tower'] = design.compute_empty_tower_cost(W)
Cost['Platform and ladders'] = design.compute_plaform_ladder_cost(Di, H)
RigorousDistillation = MESHDistillation
