# -*- coding: utf-8
"""Module of class Separator.
This file is part of project TESPy (github.com/oemof/tespy). It's copyrighted
by the contributors recorded in the version control history of the file,
available from its original location tespy/components/nodes/separator.py
SPDX-License-Identifier: MIT
"""
import numpy as np
from tespy.components.nodes.base import NodeBase
from tespy.tools.data_containers import SimpleDataContainer as dc_simple
from tespy.tools.document_models import generate_latex_eq
from tespy.tools.fluid_properties import dT_mix_dph
from tespy.tools.fluid_properties import dT_mix_pdh
# from tespy.tools.fluid_properties import dT_mix_ph_dfluid
[docs]
class Separator(NodeBase):
r"""
A separator separates fluid components from a mass flow.
**Mandatory Equations**
- :py:meth:`tespy.components.nodes.base.NodeBase.mass_flow_func`
- :py:meth:`tespy.components.nodes.base.NodeBase.pressure_equality_func`
- :py:meth:`tespy.components.nodes.separator.Separator.fluid_func`
- :py:meth:`tespy.components.nodes.separator.Separator.energy_balance_func`
Inlets/Outlets
- in1
- specify number of outlets with :code:`num_out` (default value: 2)
Image
.. image:: /api/_images/Splitter.svg
:alt: flowsheet of the splitter
:align: center
:class: only-light
.. image:: /api/_images/Splitter_darkmode.svg
:alt: flowsheet of the splitter
:align: center
:class: only-dark
Note
----
Fluid separation requires power and cooling, equations have not been
implemented, yet!
Parameters
----------
label : str
The label of the component.
design : list
List containing design parameters (stated as String).
offdesign : list
List containing offdesign parameters (stated as String).
design_path : str
Path to the components design case.
local_offdesign : boolean
Treat this component in offdesign mode in a design calculation.
local_design : boolean
Treat this component in design mode in an offdesign calculation.
char_warnings : boolean
Ignore warnings on default characteristics usage for this component.
printout : boolean
Include this component in the network's results printout.
num_out : float, dict
Number of outlets for this component, default value: 2.
Example
-------
The separator is used to split up a single mass flow into a specified
number of different parts at identical pressure and temperature but
different fluid composition. Fluids can be separated from each other.
>>> from tespy.components import Sink, Source, Separator
>>> from tespy.connections import Connection
>>> from tespy.networks import Network
>>> import shutil
>>> import numpy as np
>>> nw = Network(p_unit='bar', T_unit='C',
... iterinfo=False)
>>> so = Source('source')
>>> si1 = Sink('sink1')
>>> si2 = Sink('sink2')
>>> s = Separator('separator', num_out=2)
>>> s.component()
'separator'
>>> inc = Connection(so, 'out1', s, 'in1')
>>> outg1 = Connection(s, 'out1', si1, 'in1')
>>> outg2 = Connection(s, 'out2', si2, 'in1')
>>> nw.add_conns(inc, outg1, outg2)
An Air (simplified) mass flow of 5 kg/s is split up into two mass flows.
One mass flow of 1 kg/s containing 10 % oxygen and 90 % nitrogen leaves the
separator. It is possible to calculate the fluid composition of the second
mass flow. Specify starting values for the second mass flow fluid
composition for calculation stability.
>>> inc.set_attr(fluid={'O2': 0.23, 'N2': 0.77}, p=1, T=20, m=5)
>>> outg1.set_attr(fluid={'O2': 0.1, 'N2': 0.9}, m=1)
>>> outg2.set_attr(fluid0={'O2': 0.5, 'N2': 0.5})
>>> nw.solve('design')
>>> outg2.fluid.val['O2']
0.2625
In the same way, it is possible to specify one of the fluid components in
the second mass flow instead of the first mass flow. The solver will find
the mass flows matching the desired composition. 65 % of the mass flow
will leave the separator at the second outlet the case of 30 % oxygen
mass fraction for this outlet.
>>> outg1.set_attr(m=None)
>>> outg2.set_attr(fluid={'O2': 0.3})
>>> nw.solve('design')
>>> outg2.fluid.val['O2']
0.3
>>> round(outg2.m.val_SI / inc.m.val_SI, 2)
0.65
"""
[docs]
@staticmethod
def component():
return 'separator'
[docs]
@staticmethod
def get_parameters():
return {'num_out': dc_simple()}
[docs]
def get_mandatory_constraints(self):
self.variable_fluids = set(
[fluid for c in self.inl + self.outl for fluid in c.fluid.is_var]
)
num_fluid_eq = len(self.variable_fluids)
if num_fluid_eq == 0:
num_fluid_eq = 1
self.variable_fluids = [list(self.inl[0].fluid.is_set)[0]]
return {
'mass_flow_constraints': {
'func': self.mass_flow_func, 'deriv': self.mass_flow_deriv,
'constant_deriv': True, 'latex': self.mass_flow_func_doc,
'num_eq': 1},
'fluid_constraints': {
'func': self.fluid_func, 'deriv': self.fluid_deriv,
'constant_deriv': False, 'latex': self.fluid_func_doc,
'num_eq': num_fluid_eq},
'energy_balance_constraints': {
'func': self.energy_balance_func,
'deriv': self.energy_balance_deriv,
'constant_deriv': False, 'latex': self.energy_balance_func_doc,
'num_eq': self.num_o},
'pressure_constraints': {
'func': self.pressure_equality_func,
'deriv': self.pressure_equality_deriv,
'constant_deriv': True,
'latex': self.pressure_equality_func_doc,
'num_eq': self.num_i + self.num_o - 1}
}
[docs]
@staticmethod
def inlets():
return ['in1']
[docs]
def outlets(self):
if self.num_out.is_set:
return ['out' + str(i + 1) for i in range(self.num_out.val)]
else:
self.set_attr(num_out=2)
return self.outlets()
[docs]
@staticmethod
def is_branch_source():
return True
[docs]
def start_branch(self):
branches = {}
for outconn in self.outl:
branch = {
"connections": [outconn],
"components": [self, outconn.target],
"subbranches": {}
}
outconn.target.propagate_to_target(branch)
branches[outconn.label] = branch
return branches
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def propagate_to_target(self, branch):
return
[docs]
def propagate_wrapper_to_target(self, branch):
branch["components"] += [self]
for outconn in self.outl:
branch["connections"] += [outconn]
outconn.target.propagate_wrapper_to_target(branch)
[docs]
def fluid_func(self):
r"""
Calculate the vector of residual values for fluid balance equations.
Returns
-------
residual : list
Vector of residual values for component's fluid balance.
.. math::
0 = \dot{m}_{in} \cdot x_{fl,in} - \dot {m}_{out,j}
\cdot x_{fl,out,j}\\
\forall fl \in \text{network fluids,}
\; \forall j \in \text{outlets}
"""
i = self.inl[0]
residual = []
for fluid in self.variable_fluids:
res = i.fluid.val[fluid] * i.m.val_SI
for o in self.outl:
res -= o.fluid.val[fluid] * o.m.val_SI
residual += [res]
return residual
[docs]
def fluid_func_doc(self, label):
r"""
Calculate the vector of residual values for fluid balance equations.
Parameters
----------
label : str
Label for equation.
Returns
-------
latex : str
LaTeX code of equations applied.
"""
latex = (
r'0 = \dot{m}_\mathrm{in} \cdot x_{fl\mathrm{,in}} - '
r'\dot {m}_{\mathrm{out,}j} \cdot x_{fl\mathrm{,out,}j}'
r'\; \forall fl \in \text{network fluids,} \; \forall j \in'
r'\text{outlets}'
)
return generate_latex_eq(self, latex, label)
[docs]
def fluid_deriv(self, increment_filter, k):
r"""
Calculate partial derivatives of fluid balance.
Parameters
----------
increment_filter : ndarray
Matrix for filtering non-changing variables.
k : int
Position of derivatives in Jacobian matrix (k-th equation).
"""
i = self.inl[0]
for fluid in self.variable_fluids:
for o in self.outl:
if self.is_variable(o.m):
self.jacobian[k, o.m.J_col] = -o.fluid.val[fluid]
if fluid in o.fluid.is_var:
self.jacobian[k, o.fluid.J_col[fluid]] = -o.m.val_SI
if self.is_variable(i.m):
self.jacobian[k, i.m.J_col] = i.fluid.val[fluid]
if fluid in i.fluid.is_var:
self.jacobian[k, i.fluid.J_col[fluid]] = i.m.val_SI
k += 1
[docs]
def energy_balance_func(self):
r"""
Calculate energy balance.
Returns
-------
residual : list
Residual value of energy balance.
.. math::
0 = T_{in} - T_{out,j}\\
\forall j \in \text{outlets}
"""
residual = []
T_in = self.inl[0].calc_T()
for o in self.outl:
residual += [T_in - o.calc_T()]
return residual
[docs]
def energy_balance_func_doc(self, label):
r"""
Calculate energy balance.
Parameters
----------
label : str
Label for equation.
Returns
-------
latex : str
LaTeX code of equations applied.
"""
latex = (
r'0= T_\mathrm{in} - T_{\mathrm{out,}j}'
r'\; \forall j \in \text{outlets}'
)
return generate_latex_eq(self, latex, label)
[docs]
def energy_balance_deriv(self, increment_filter, k):
r"""
Calculate partial derivatives of energy balance.
Parameters
----------
increment_filter : ndarray
Matrix for filtering non-changing variables.
k : int
Position of derivatives in Jacobian matrix (k-th equation).
"""
i = self.inl[0]
dT_dp_in = dT_mix_dph(i.p.val_SI, i.h.val_SI, i.fluid_data, i.mixing_rule)
dT_dh_in = dT_mix_pdh(i.p.val_SI, i.h.val_SI, i.fluid_data, i.mixing_rule)
# dT_dfluid_in = {}
# for fluid in i.fluid.is_var:
# dT_dfluid_in[fluid] = dT_mix_ph_dfluid(i)
for o in self.outl:
if self.is_variable(i.p):
self.jacobian[k, i.p.J_col] = dT_dp_in
if self.is_variable(i.h):
self.jacobian[k, i.h.J_col] = dT_dh_in
# for fluid in i.fluid.is_var:
# self.jacobian[k, i.fluid.J_col[fluid]] = dT_dfluid_in[fluid]
args = (o.p.val_SI, o.h.val_SI, o.fluid_data, o.mixing_rule)
self.jacobian[k, o.p.J_col] = -dT_mix_dph(*args)
self.jacobian[k, o.h.J_col] = -dT_mix_pdh(*args)
# for fluid in o.fluid.is_var:
# self.jacobian[k, o.fluid.J_col[fluid]] = -dT_mix_ph_dfluid(o)
k += 1