# -*- coding: utf-8
"""Module of class Splitter.
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/splitter.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
[docs]
class Splitter(NodeBase):
r"""
Split up a mass flow in parts of identical enthalpy and fluid composition.
**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.splitter.Splitter.fluid_func`
- :py:meth:`tespy.components.nodes.splitter.Splitter.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
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
-------
A splitter is used to split up a single mass flow into a specified number
of different parts at identical pressure, enthalpy and fluid composition.
>>> from tespy.components import Sink, Source, Splitter
>>> 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')
>>> si3 = Sink('sink3')
>>> s = Splitter('splitter', num_out=3)
>>> s.component()
'splitter'
>>> inc = Connection(so, 'out1', s, 'in1')
>>> outg1 = Connection(s, 'out1', si1, 'in1')
>>> outg2 = Connection(s, 'out2', si2, 'in1')
>>> outg3 = Connection(s, 'out3', si3, 'in1')
>>> nw.add_conns(inc, outg1, outg2, outg3)
An Air (simplified) mass flow is split up into three mass flows. The total
incoming mass flow is 5 kg/s, 3 kg/s and 1 kg/s respectively are leaving
the splitter into the first two outlets. The residual mass flow will
drain in the last outlet. Temperature and fluid composition will not
change.
>>> inc.set_attr(fluid={'O2': 0.23, 'N2': 0.77}, p=1, T=20, m=5)
>>> outg1.set_attr(m=3)
>>> outg2.set_attr(m=1)
>>> nw.solve('design')
>>> round(outg3.m.val_SI, 1)
1.0
>>> round(inc.T.val, 1)
20.0
>>> round(outg3.T.val, 1)
20.0
"""
[docs]
@staticmethod
def component():
return 'splitter'
[docs]
@staticmethod
def get_parameters():
return {'num_out': dc_simple()}
[docs]
def get_mandatory_constraints(self):
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},
'energy_balance_constraints': {
'func': self.energy_balance_func,
'deriv': self.energy_balance_deriv,
'constant_deriv': True, '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]
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 preprocess(self, num_nw_vars):
super().preprocess(num_nw_vars)
self._propagation_start = False
[docs]
def energy_balance_func(self):
r"""
Calculate energy balance.
Returns
-------
residual : list
Residual value of energy balance.
.. math::
0 = h_{in} - h_{out,j} \;
\forall j \in \mathrm{outlets}\\
"""
residual = []
for o in self.outl:
residual += [self.inl[0].h.val_SI - o.h.val_SI]
return residual
[docs]
def energy_balance_func_doc(self, label):
r"""
Calculate energy balance.
Parameters
----------
label : str
Label for equation.
"""
latex = r'0=h_{in}-h_{\mathrm{out,}j}\;\forall j \in\text{outlets}'
return generate_latex_eq(self, latex, label)
[docs]
def energy_balance_deriv(self, k):
r"""
Calculate partial derivatives for energy balance equation.
Returns
-------
deriv : list
Matrix of partial derivatives.
"""
for eq, o in enumerate(self.outl):
if self.inl[0].h.is_var:
self.jacobian[k + eq, self.inl[0].h.J_col] = 1
if o.h.is_var:
self.jacobian[k + eq, o.h.J_col] = -1