# -*- coding: utf-8
"""Module of class SimpleHeatExchanger.
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/heat_exchangers/simple.py
SPDX-License-Identifier: MIT
"""
import math
import warnings
import numpy as np
from tespy.components.component import Component
from tespy.components.component import component_registry
from tespy.tools import logger
from tespy.tools.data_containers import ComponentCharacteristics as dc_cc
from tespy.tools.data_containers import ComponentProperties as dc_cp
from tespy.tools.data_containers import GroupedComponentProperties as dc_gcp
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 s_mix_ph
from tespy.tools.fluid_properties.helpers import darcy_friction_factor as dff
from tespy.tools.helpers import convert_to_SI
[docs]
@component_registry
class SimpleHeatExchanger(Component):
r"""
A basic heat exchanger representing a heat source or heat sink.
The component SimpleHeatExchanger is the parent class for the components:
- :py:class:`tespy.components.heat_exchangers.solar_collector.SolarCollector`
- :py:class:`tespy.components.heat_exchangers.parabolic_trough.ParabolicTrough`
- :py:class:`tespy.components.piping.pipe.Pipe`
**Mandatory Equations**
- :py:meth:`tespy.components.component.Component.fluid_func`
- :py:meth:`tespy.components.component.Component.mass_flow_func`
**Optional Equations**
- :py:meth:`tespy.components.component.Component.pr_func`
- :py:meth:`tespy.components.component.Component.zeta_func`
- :py:meth:`tespy.components.heat_exchangers.simple.SimpleHeatExchanger.energy_balance_func`
- :py:meth:`tespy.components.heat_exchangers.simple.SimpleHeatExchanger.darcy_group_func`
- :py:meth:`tespy.components.heat_exchangers.simple.SimpleHeatExchanger.hw_group_func`
- :py:meth:`tespy.components.heat_exchangers.simple.SimpleHeatExchanger.kA_group_func`
- :py:meth:`tespy.components.heat_exchangers.simple.SimpleHeatExchanger.kA_char_group_func`
Inlets/Outlets
- in1
- out1
Image
.. image:: /api/_images/Pipe.svg
:alt: flowsheet of the simple heat exchanger
:align: center
:class: only-light
.. image:: /api/_images/Pipe_darkmode.svg
:alt: flowsheet of the simple heat exchanger
: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.
Q : float, dict, :code:`"var"`
Heat transfer, :math:`Q/\text{W}`.
pr : float, dict, :code:`"var"`
Outlet to inlet pressure ratio, :math:`pr/1`.
zeta : float, dict, :code:`"var"`
Geometry independent friction coefficient,
:math:`\frac{\zeta}{D^4}/\frac{1}{\text{m}^4}`.
D : float, dict, :code:`"var"`
Diameter of the pipes, :math:`D/\text{m}`.
L : float, dict, :code:`"var"`
Length of the pipes, :math:`L/\text{m}`.
ks : float, dict, :code:`"var"`
Pipe's roughness, :math:`ks/\text{m}`.
darcy_group : str, dict
Parametergroup for pressure drop calculation based on pipes dimensions
using darcy weissbach equation.
ks_HW : float, dict, :code:`"var"`
Pipe's roughness, :math:`ks/\text{1}`.
hw_group : str, dict
Parametergroup for pressure drop calculation based on pipes dimensions
using hazen williams equation.
kA : float, dict, :code:`"var"`
Area independent heat transfer coefficient,
:math:`kA/\frac{\text{W}}{\text{K}}`.
kA_char : tespy.tools.characteristics.CharLine, dict
Characteristic line for heat transfer coefficient.
Tamb : float, dict
Ambient temperature, provide parameter in network's temperature unit.
kA_group : str, dict
Parametergroup for heat transfer calculation from ambient temperature
and area independent heat transfer coefficient kA.
Example
-------
The SimpleHeatExchanger can be used as a sink or source of heat. This
component does not simulate the secondary side of the heat exchanger. It
is possible to calculate the pressure ratio with the Darcy-Weisbach
equation or in case of liquid water use the Hazen-Williams equation.
Also, given ambient temperature and the heat transfer coeffiecient, it is
possible to predict heat transfer.
>>> from tespy.components import Sink, Source, SimpleHeatExchanger
>>> from tespy.connections import Connection
>>> from tespy.networks import Network
>>> import shutil
>>> nw = Network()
>>> nw.set_attr(p_unit='bar', T_unit='C', h_unit='kJ / kg', iterinfo=False)
>>> so1 = Source('source 1')
>>> si1 = Sink('sink 1')
>>> heat_sink = SimpleHeatExchanger('heat sink')
>>> heat_sink.component()
'heat exchanger simple'
>>> heat_sink.set_attr(Tamb=10, pr=0.95, design=['pr'],
... offdesign=['zeta', 'kA_char'])
>>> inc = Connection(so1, 'out1', heat_sink, 'in1')
>>> outg = Connection(heat_sink, 'out1', si1, 'in1')
>>> nw.add_conns(inc, outg)
It is possible to determine the amount of heat transferred when the fluid
enters the heat sink at a temperature of 200 °C and is cooled down to
150 °C. Given an ambient temperature of 10 °C this also determines the heat
transfer coefficient to the ambient. Assuming a characteristic function
for the heat transfer coefficient we can predict the heat transferred at
variable flow rates.
>>> inc.set_attr(fluid={'N2': 1}, m=1, T=200, p=5)
>>> outg.set_attr(T=150, design=['T'])
>>> nw.solve('design')
>>> nw.save('tmp')
>>> round(heat_sink.Q.val, 0)
-52581.0
>>> round(heat_sink.kA.val, 0)
321.0
>>> inc.set_attr(m=1.25)
>>> nw.solve('offdesign', design_path='tmp')
>>> round(heat_sink.Q.val, 0)
-56599.0
>>> round(outg.T.val, 1)
156.9
>>> inc.set_attr(m=0.75)
>>> nw.solve('offdesign', design_path='tmp')
>>> round(heat_sink.Q.val, 1)
-47275.8
>>> round(outg.T.val, 1)
140.0
>>> shutil.rmtree('./tmp', ignore_errors=True)
"""
[docs]
@staticmethod
def component():
return 'heat exchanger simple'
[docs]
def get_parameters(self):
return {
'Q': dc_cp(
deriv=self.energy_balance_deriv,
latex=self.energy_balance_func_doc, num_eq=1,
func=self.energy_balance_func),
'pr': dc_cp(
min_val=1e-4, max_val=1, num_eq=1,
deriv=self.pr_deriv, latex=self.pr_func_doc,
func=self.pr_func, func_params={'pr': 'pr'}),
'zeta': dc_cp(
min_val=0, max_val=1e15, num_eq=1,
deriv=self.zeta_deriv, func=self.zeta_func,
latex=self.zeta_func_doc,
func_params={'zeta': 'zeta'}),
'D': dc_cp(min_val=1e-2, max_val=2, d=1e-4),
'L': dc_cp(min_val=1e-1, d=1e-3),
'ks': dc_cp(val=1e-4, min_val=1e-7, max_val=1e-3, d=1e-8),
'ks_HW': dc_cp(val=10, min_val=1e-1, max_val=1e3, d=1e-2),
'kA': dc_cp(min_val=0, d=1),
'kA_char': dc_cc(param='m'), 'Tamb': dc_cp(),
'dissipative': dc_simple(val=None),
'darcy_group': dc_gcp(
elements=['L', 'ks', 'D'], num_eq=1,
latex=self.darcy_func_doc,
func=self.darcy_func, deriv=self.darcy_deriv),
'hw_group': dc_gcp(
elements=['L', 'ks_HW', 'D'], num_eq=1,
latex=self.hazen_williams_func_doc,
func=self.hazen_williams_func, deriv=self.hazen_williams_deriv),
'kA_group': dc_gcp(
elements=['kA', 'Tamb'], num_eq=1,
latex=self.kA_group_func_doc,
func=self.kA_group_func, deriv=self.kA_group_deriv),
'kA_char_group': dc_gcp(
elements=['kA_char', 'Tamb'], num_eq=1,
latex=self.kA_char_group_func_doc,
func=self.kA_char_group_func, deriv=self.kA_char_group_deriv)
}
[docs]
@staticmethod
def inlets():
return ['in1']
[docs]
@staticmethod
def outlets():
return ['out1']
[docs]
def preprocess(self, num_nw_vars):
super().preprocess(num_nw_vars)
self.Tamb.val_SI = convert_to_SI('T', self.Tamb.val, self.inl[0].T.unit)
[docs]
def energy_balance_func(self):
r"""
Equation for pressure drop calculation.
Returns
-------
residual : float
Residual value of equation:
.. math::
0 =\dot{m}_{in}\cdot\left( h_{out}-h_{in}\right) -\dot{Q}
"""
return self.inl[0].m.val_SI * (
self.outl[0].h.val_SI - self.inl[0].h.val_SI
) - self.Q.val
[docs]
def energy_balance_func_doc(self, label):
r"""
Equation for pressure drop calculation.
Parameters
----------
label : str
Label for equation.
Returns
-------
latex : str
LaTeX code of equations applied.
"""
latex = (
r'0 = \dot{m}_\mathrm{in} \cdot \left(h_\mathrm{out} - '
r'h_\mathrm{in} \right) -\dot{Q}'
)
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]
o = self.outl[0]
if i.m.is_var:
self.jacobian[k, i.m.J_col] = o.h.val_SI - i.h.val_SI
if i.h.is_var:
self.jacobian[k, i.h.J_col] = -i.m.val_SI
if o.h.is_var:
self.jacobian[k, o.h.J_col] = i.m.val_SI
# custom variable Q
if self.Q.is_var:
self.jacobian[k, self.Q.J_col] = -1
[docs]
def darcy_func(self):
r"""
Equation for pressure drop calculation from darcy friction factor.
Returns
-------
residual : float
Residual value of equation.
.. math::
0 = p_{in} - p_{out} - \frac{8 \cdot |\dot{m}_{in}| \cdot
\dot{m}_{in} \cdot \frac{v_{in}+v_{out}}{2} \cdot L \cdot
\lambda\left(Re, ks, D\right)}{\pi^2 \cdot D^5}\\
Re = \frac{4 \cdot |\dot{m}_{in}|}{\pi \cdot D \cdot
\frac{\eta_{in}+\eta_{out}}{2}}\\
\eta: \text{dynamic viscosity}\\
v: \text{specific volume}\\
\lambda: \text{darcy friction factor}
"""
i = self.inl[0]
o = self.outl[0]
if abs(i.m.val_SI) < 1e-4:
return i.p.val_SI - o.p.val_SI
visc_i = i.calc_viscosity(T0=i.T.val_SI)
visc_o = o.calc_viscosity(T0=o.T.val_SI)
v_i = i.calc_vol(T0=i.T.val_SI)
v_o = o.calc_vol(T0=o.T.val_SI)
Re = 4 * abs(i.m.val_SI) / (math.pi * self.D.val * (visc_i + visc_o) / 2)
return (
(i.p.val_SI - o.p.val_SI)
- 8 * abs(i.m.val_SI) * i.m.val_SI * (v_i + v_o)
/ 2 * self.L.val * dff(Re, self.ks.val, self.D.val)
/ (math.pi ** 2 * self.D.val ** 5)
)
[docs]
def darcy_func_doc(self, label):
r"""
Equation for pressure drop calculation from darcy friction factor.
Parameters
----------
label : str
Label for equation.
Returns
-------
latex : str
LaTeX code of equations applied.
"""
latex = (
r'\begin{split}' + '\n'
r'0 = &p_\mathrm{in}-p_\mathrm{out}-'
r'\frac{8\cdot|\dot{m}_\mathrm{in}| \cdot\dot{m}_\mathrm{in}'
r'\cdot \frac{v_\mathrm{in}+v_\mathrm{out}}{2} \cdot L \cdot'
r'\lambda\left(Re, ks, D\right)}{\pi^2 \cdot D^5}\\' + '\n'
r'Re =&\frac{4 \cdot |\dot{m}_\mathrm{in}|}{\pi \cdot D \cdot'
r'\frac{\eta_\mathrm{in}+\eta_\mathrm{out}}{2}}\\' + '\n'
r'\end{split}'
)
return generate_latex_eq(self, latex, label)
[docs]
def darcy_deriv(self, increment_filter, k):
r"""
Calculate partial derivatives of hydro group (pressure drop).
Parameters
----------
increment_filter : ndarray
Matrix for filtering non-changing variables.
k : int
Position of derivatives in Jacobian matrix (k-th equation).
"""
func = self.darcy_func
i = self.inl[0]
o = self.outl[0]
if self.is_variable(i.m, increment_filter):
self.jacobian[k, i.m.J_col] = self.numeric_deriv(func, 'm', i)
if self.is_variable(i.p, increment_filter):
self.jacobian[k, i.p.J_col] = self.numeric_deriv(func, 'p', i)
if self.is_variable(i.h, increment_filter):
self.jacobian[k, i.h.J_col] = self.numeric_deriv(func, 'h', i)
if self.is_variable(o.p, increment_filter):
self.jacobian[k, o.p.J_col] = self.numeric_deriv(func, 'p', o)
if self.is_variable(o.h, increment_filter):
self.jacobian[k, o.h.J_col] = self.numeric_deriv(func, 'h', o)
# custom variables of hydro group
for variable_name in self.darcy_group.elements:
parameter = self.get_attr(variable_name)
if parameter.is_var:
self.jacobian[k, parameter.J_col] = (
self.numeric_deriv(func, variable_name, None)
)
[docs]
def hazen_williams_func(self):
r"""
Equation for pressure drop calculation from Hazen-Williams equation.
Returns
-------
residual : float
Residual value of equation.
.. math::
0 = \left(p_{in} - p_{out} \right) \cdot \left(-1\right)^i -
\frac{10.67 \cdot |\dot{m}_{in}| ^ {1.852}
\cdot L}{ks^{1.852} \cdot D^{4.871}} \cdot g \cdot
\left(\frac{v_{in} + v_{out}}{2}\right)^{0.852}
i = \begin{cases}
0 & \dot{m}_{in} \geq 0\\
1 & \dot{m}_{in} < 0
\end{cases}
Note
----
Gravity :math:`g` is set to :math:`9.81 \frac{m}{s^2}`
"""
i = self.inl[0]
o = self.outl[0]
if abs(i.m.val_SI) < 1e-4:
return i.p.val_SI - o.p.val_SI
v_i = i.calc_vol(T0=i.T.val_SI)
v_o = o.calc_vol(T0=o.T.val_SI)
return (
math.copysign(i.p.val_SI - o.p.val_SI, i.m.val_SI)
- (
10.67 * abs(i.m.val_SI) ** 1.852 * self.L.val /
(self.ks_HW.val ** 1.852 * self.D.val ** 4.871)
) * (9.81 * ((v_i + v_o) / 2) ** 0.852)
)
[docs]
def hazen_williams_func_doc(self, label):
r"""
Equation for pressure drop calculation from Hazen-Williams equation.
Parameters
----------
label : str
Label for equation.
Returns
-------
latex : str
LaTeX code of equations applied.
"""
latex = (
r'0 = \left(p_\mathrm{in} - p_\mathrm{out} \right) -'
r'\frac{10.67 \cdot |\dot{m}_\mathrm{in}| ^ {1.852}'
r'\cdot L}{ks^{1.852} \cdot D^{4.871}} \cdot g \cdot'
r'\left(\frac{v_\mathrm{in}+ v_\mathrm{out}}{2}\right)^{0.852}'
)
return generate_latex_eq(self, latex, label)
[docs]
def hazen_williams_deriv(self, increment_filter, k):
r"""
Calculate partial derivatives of hydro group (pressure drop).
Parameters
----------
increment_filter : ndarray
Matrix for filtering non-changing variables.
k : int
Position of derivatives in Jacobian matrix (k-th equation).
"""
func = self.hazen_williams_func
i = self.inl[0]
o = self.outl[0]
if self.is_variable(i.m, increment_filter):
self.jacobian[k, i.m.J_col] = self.numeric_deriv(func, 'm', i)
if self.is_variable(i.p, increment_filter):
self.jacobian[k, i.p.J_col] = self.numeric_deriv(func, 'p', i)
if self.is_variable(i.h, increment_filter):
self.jacobian[k, i.h.J_col] = self.numeric_deriv(func, 'h', i)
if self.is_variable(o.p, increment_filter):
self.jacobian[k, o.p.J_col] = self.numeric_deriv(func, 'p', o)
if self.is_variable(o.h, increment_filter):
self.jacobian[k, o.h.J_col] = self.numeric_deriv(func, 'h', o)
# custom variables of hydro group
for variable_name in self.hw_group.elements:
parameter = self.get_attr(variable_name)
if parameter.is_var:
self.jacobian[k, parameter.J_col] = (
self.numeric_deriv(func, variable_name, None)
)
[docs]
def kA_group_func(self):
r"""
Calculate heat transfer from heat transfer coefficient.
Returns
-------
residual : float
Residual value of equation.
.. math::
0 = \dot{m}_{in} \cdot \left( h_{out} - h_{in}\right) +
kA \cdot \Delta T_{log}
\Delta T_{log} = \begin{cases}
\frac{T_{in}-T_{out}}{\ln{\frac{T_{in}-T_{amb}}
{T_{out}-T_{amb}}}} & T_{in} > T_{out} \\
\frac{T_{out}-T_{in}}{\ln{\frac{T_{out}-T_{amb}}
{T_{in}-T_{amb}}}} & T_{in} < T_{out}\\
0 & T_{in} = T_{out}
\end{cases}
T_{amb}: \text{ambient temperature}
"""
i = self.inl[0]
o = self.outl[0]
ttd_1 = i.calc_T() - self.Tamb.val_SI
ttd_2 = o.calc_T() - self.Tamb.val_SI
# For numerical stability: If temperature differences have
# different sign use mean difference to avoid negative logarithm.
if (ttd_1 / ttd_2) < 0:
td_log = (ttd_2 + ttd_1) / 2
elif ttd_1 > ttd_2:
td_log = (ttd_1 - ttd_2) / math.log(ttd_1 / ttd_2)
elif ttd_1 < ttd_2:
td_log = (ttd_2 - ttd_1) / math.log(ttd_2 / ttd_1)
else:
# both values are equal
td_log = ttd_2
return i.m.val_SI * (o.h.val_SI - i.h.val_SI) + self.kA.val * td_log
[docs]
def kA_group_func_doc(self, label):
r"""
Calculate heat transfer from heat transfer coefficient.
Parameters
----------
label : str
Label for equation.
Returns
-------
latex : str
LaTeX code of equations applied.
"""
latex = (
r'\begin{split}' + '\n'
r'0=&\dot{m}_\mathrm{in}\cdot\left(h_\mathrm{out}-'
r'h_\mathrm{in}\right)+kA \cdot \Delta T_\mathrm{log}\\' + '\n'
r'\Delta T_\mathrm{log} = &\begin{cases}' + '\n'
r'\frac{T_\mathrm{in}-T_\mathrm{out}}{\ln{\frac{T_\mathrm{in}-'
r'T_\mathrm{amb}}{T_\mathrm{out}-T_\mathrm{amb}}}} &'
r' T_\mathrm{in} > T_\mathrm{out} \\' + '\n'
r'\frac{T_\mathrm{out}-T_\mathrm{in}}{\ln{\frac{'
r'T_\mathrm{out}-T_\mathrm{amb}}{T_\mathrm{in}-'
r'T_\mathrm{amb}}}} & T_\mathrm{in} < T_\mathrm{out}\\' + '\n'
r'0 & T_\mathrm{in} = T_\mathrm{out}' + '\n'
r'\end{cases}\\' + '\n'
r'T_\mathrm{amb} =& \text{ambient temperature}' + '\n'
r'\end{split}'
)
return generate_latex_eq(self, latex, label)
[docs]
def kA_group_deriv(self, increment_filter, k):
r"""
Calculate partial derivatives of kA group.
Parameters
----------
increment_filter : ndarray
Matrix for filtering non-changing variables.
k : int
Position of derivatives in Jacobian matrix (k-th equation).
"""
f = self.kA_group_func
i = self.inl[0]
o = self.outl[0]
if self.is_variable(i.m, increment_filter):
self.jacobian[k, i.m.J_col] = o.h.val_SI - i.h.val_SI
if self.is_variable(i.p, increment_filter):
self.jacobian[k, i.p.J_col] = self.numeric_deriv(f, 'p', i)
if self.is_variable(i.h, increment_filter):
self.jacobian[k, i.h.J_col] = self.numeric_deriv(f, 'h', i)
if self.is_variable(o.p, increment_filter):
self.jacobian[k, o.p.J_col] = self.numeric_deriv(f, 'p', o)
if self.is_variable(o.h, increment_filter):
self.jacobian[k, o.h.J_col] = self.numeric_deriv(f, 'h', o)
if self.kA.is_var:
self.jacobian[k, self.kA.J_col] = self.numeric_deriv(f, self.vars[self.kA])
[docs]
def kA_char_group_func(self):
r"""
Calculate heat transfer from heat transfer coefficient characteristic.
Returns
-------
residual : float
Residual value of equation.
.. math::
0 = \dot{m}_{in} \cdot \left( h_{out} - h_{in}\right) +
kA_{design} \cdot f_{kA} \cdot \Delta T_{log}
\Delta T_{log} = \begin{cases}
\frac{T_{in}-T_{out}}{\ln{\frac{T_{in}-T_{amb}}
{T_{out}-T_{amb}}}} & T_{in} > T_{out} \\
\frac{T_{out}-T_{in}}{\ln{\frac{T_{out}-T_{amb}}
{T_{in}-T_{amb}}}} & T_{in} < T_{out}\\
0 & T_{in} = T_{out}
\end{cases}
f_{kA} = \frac{2}{1 + \frac{1}{f\left( expr\right)}}
T_{amb}: \text{ambient temperature}
Note
----
For standard function of f\ :subscript:`kA` \ see module
:py:mod:`tespy.data`.
"""
p = self.kA_char.param
expr = self.get_char_expr(p, **self.kA_char.char_params)
i = self.inl[0]
o = self.outl[0]
# For numerical stability: If temperature differences have
# different sign use mean difference to avoid negative logarithm.
ttd_1 = i.calc_T() - self.Tamb.val_SI
ttd_2 = o.calc_T() - self.Tamb.val_SI
if (ttd_1 / ttd_2) < 0:
td_log = (ttd_2 + ttd_1) / 2
elif ttd_1 > ttd_2:
td_log = (ttd_1 - ttd_2) / math.log(ttd_1 / ttd_2)
elif ttd_1 < ttd_2:
td_log = (ttd_2 - ttd_1) / math.log(ttd_2 / ttd_1)
else:
# both values are equal
td_log = ttd_2
fkA = 2 / (1 + 1 / self.kA_char.char_func.evaluate(expr))
return i.m.val_SI * (o.h.val_SI - i.h.val_SI) + self.kA.design * fkA * td_log
[docs]
def kA_char_group_func_doc(self, label):
r"""
Calculate heat transfer from heat transfer coefficient characteristic.
Parameters
----------
label : str
Label for equation.
Returns
-------
latex : str
LaTeX code of equations applied.
"""
latex = (
r'\begin{split}' + '\n'
r'0=&\dot{m}_\mathrm{in}\cdot\left(h_\mathrm{out}-'
r'h_\mathrm{in}\right)+kA_\mathrm{design} \cdot f_\mathrm{kA}'
r' \cdot \Delta T_\mathrm{log}\\' + '\n'
r'\Delta T_\mathrm{log} = &\begin{cases}' + '\n'
r'\frac{T_\mathrm{in}-T_\mathrm{out}}{\ln{\frac{T_\mathrm{in}-'
r'T_\mathrm{amb}}{T_\mathrm{out}-T_\mathrm{amb}}}} &'
r' T_\mathrm{in} > T_\mathrm{out} \\' + '\n'
r'\frac{T_\mathrm{out}-T_\mathrm{in}}{\ln{\frac{'
r'T_\mathrm{out}-T_\mathrm{amb}}{T_\mathrm{in}-'
r'T_\mathrm{amb}}}} & T_\mathrm{in} < T_\mathrm{out}\\' + '\n'
r'0 & T_\mathrm{in} = T_\mathrm{out}' + '\n'
r'\end{cases}\\' + '\n'
r'f_{kA}=&\frac{2}{1 + \frac{1}{f\left(X\right)}}\\' + '\n'
r'T_\mathrm{amb} =& \text{ambient temperature}' + '\n'
r'\end{split}'
)
return generate_latex_eq(self, latex, label)
[docs]
def kA_char_group_deriv(self, increment_filter, k):
r"""
Calculate partial derivatives of kA characteristics.
Parameters
----------
increment_filter : ndarray
Matrix for filtering non-changing variables.
k : int
Position of derivatives in Jacobian matrix (k-th equation).
"""
f = self.kA_char_group_func
i = self.inl[0]
o = self.outl[0]
if self.is_variable(i.m, increment_filter):
self.jacobian[k, i.m.J_col] = self.numeric_deriv(f, 'm', i)
if self.is_variable(i.p, increment_filter):
self.jacobian[k, i.p.J_col] = self.numeric_deriv(f, 'p', i)
if self.is_variable(i.h, increment_filter):
self.jacobian[k, i.h.J_col] = self.numeric_deriv(f, 'h', i)
if self.is_variable(o.p, increment_filter):
self.jacobian[k, o.p.J_col] = self.numeric_deriv(f, 'p', o)
if self.is_variable(o.h, increment_filter):
self.jacobian[k, o.h.J_col] = self.numeric_deriv(f, 'h', o)
[docs]
def bus_func(self, bus):
r"""
Calculate the value of the bus function.
Parameters
----------
bus : tespy.connections.bus.Bus
TESPy bus object.
Returns
-------
val : float
Value of energy transfer :math:`\dot{E}`. This value is passed to
:py:meth:`tespy.components.component.Component.calc_bus_value`
for value manipulation according to the specified characteristic
line of the bus.
.. math::
\dot{E} = \dot{m}_{in} \cdot \left( h_{out} - h_{in} \right)
"""
return self.inl[0].m.val_SI * (
self.outl[0].h.val_SI - self.inl[0].h.val_SI)
[docs]
def bus_func_doc(self, bus):
r"""
Return LaTeX string of the bus function.
Parameters
----------
bus : tespy.connections.bus.Bus
TESPy bus object.
Returns
-------
latex : str
LaTeX string of bus function.
"""
return (
r'\dot{m}_\mathrm{in} \cdot \left(h_\mathrm{out} - '
r'h_\mathrm{in} \right)')
[docs]
def bus_deriv(self, bus):
r"""
Calculate partial derivatives of the bus function.
Parameters
----------
bus : tespy.connections.bus.Bus
TESPy bus object.
Returns
-------
deriv : ndarray
Matrix of partial derivatives.
"""
f = self.calc_bus_value
if self.inl[0].m.is_var:
if self.inl[0].m.J_col not in bus.jacobian:
bus.jacobian[self.inl[0].m.J_col] = 0
bus.jacobian[self.inl[0].m.J_col] -= self.numeric_deriv(f, 'm', self.inl[0], bus=bus)
if self.inl[0].h.is_var:
if self.inl[0].h.J_col not in bus.jacobian:
bus.jacobian[self.inl[0].h.J_col] = 0
bus.jacobian[self.inl[0].h.J_col] -= self.numeric_deriv(f, 'h', self.inl[0], bus=bus)
if self.outl[0].h.is_var:
if self.outl[0].h.J_col not in bus.jacobian:
bus.jacobian[self.outl[0].h.J_col] = 0
bus.jacobian[self.outl[0].h.J_col] -= self.numeric_deriv(f, 'h', self.outl[0], bus=bus)
[docs]
def initialise_source(self, c, key):
r"""
Return a starting value for pressure and enthalpy the outlets.
Parameters
----------
c : tespy.connections.connection.Connection
Connection to perform initialisation on.
key : str
Fluid property to retrieve.
Returns
-------
val : float
Starting value for pressure/enthalpy in SI units.
.. math::
val = \begin{cases}
\begin{cases}
1 \cdot 10^5 \; \frac{\text{J}}{\text{kg}} & \dot{Q} < 0\\
3 \cdot 10^5 \; \frac{\text{J}}{\text{kg}} & \dot{Q} = 0\\
5 \cdot 10^5 \; \frac{\text{J}}{\text{kg}} & \dot{Q} > 0
\end{cases} & \text{key = 'h'}\\
\; \; \; \; 10^5 \text{Pa} & \text{key = 'p'}
\end{cases}
"""
if key == 'p':
return 1e5
elif key == 'h':
if self.Q.val < 0 and self.Q.is_set:
return 1e5
elif self.Q.val > 0 and self.Q.is_set:
return 5e5
else:
return 3e5
[docs]
def initialise_target(self, c, key):
r"""
Return a starting value for pressure and enthalpy the inlets.
Parameters
----------
c : tespy.connections.connection.Connection
Connection to perform initialisation on.
key : str
Fluid property to retrieve.
Returns
-------
val : float
Starting value for pressure/enthalpy in SI units.
.. math::
val = \begin{cases}
1 \cdot 10^5 & \text{key = 'p'}\\
\begin{cases}
5 \cdot 10^5 & \dot{Q} < 0\\
3 \cdot 10^5 & \dot{Q} = 0\\
1 \cdot 10^5 & \dot{Q} > 0
\end{cases} & \text{key = 'h'}\\
\end{cases}
"""
if key == 'p':
return 1e5
elif key == 'h':
if self.Q.val < 0 and self.Q.is_set:
return 5e5
elif self.Q.val > 0 and self.Q.is_set:
return 1e5
else:
return 3e5
[docs]
def calc_parameters(self):
r"""Postprocessing parameter calculation."""
i = self.inl[0]
o = self.outl[0]
self.Q.val = i.m.val_SI * (o.h.val_SI - i.h.val_SI)
self.pr.val = o.p.val_SI / i.p.val_SI
self.zeta.val = self.calc_zeta(i, o)
if self.Tamb.is_set:
ttd_1 = i.T.val_SI - self.Tamb.val_SI
ttd_2 = o.T.val_SI - self.Tamb.val_SI
if (ttd_1 / ttd_2) < 0:
td_log = np.nan
if ttd_1 > ttd_2:
td_log = (ttd_1 - ttd_2) / math.log(ttd_1 / ttd_2)
elif ttd_1 < ttd_2:
td_log = (ttd_2 - ttd_1) / math.log(ttd_2 / ttd_1)
else:
# both values are equal
td_log = ttd_1
self.kA.val = abs(self.Q.val / td_log)
self.kA.is_result = True
else:
self.kA.is_result = False
[docs]
def entropy_balance(self):
r"""
Calculate entropy balance of a simple heat exchanger.
The allocation of the entropy streams due to heat exchanged and due to
irreversibility is performed by solving for T:
.. math::
h_\mathrm{out} - h_\mathrm{in} = \int_\mathrm{out}^\mathrm{in}
v \cdot dp - \int_\mathrm{out}^\mathrm{in} T \cdot ds
As solving :math:`\int_\mathrm{out}^\mathrm{in} v \cdot dp` for non
isobaric processes would require perfect process knowledge (the path)
on how specific volume and pressure change throught the component, the
heat transfer is splitted into three separate virtual processes:
- in->in*: decrease pressure to
:math:`p_\mathrm{in*}=p_\mathrm{in}\cdot\sqrt{\frac{p_\mathrm{out}}{p_\mathrm{in}}}`
without changing enthalpy.
- in*->out* transfer heat without changing pressure.
:math:`h_\mathrm{out*}-h_\mathrm{in*}=h_\mathrm{out}-h_\mathrm{in}`
- out*->out decrease pressure to outlet pressure :math:`p_\mathrm{out}`
without changing enthalpy.
Note
----
The entropy balance makes the follwing parameter available:
.. math::
\text{S\_Q}=\dot{m} \cdot \left(s_\mathrm{out*}-s_\mathrm{in*}
\right)\\
\text{S\_irr}=\dot{m} \cdot \left(s_\mathrm{out}-s_\mathrm{in}
\right) - \text{S\_Q}\\
\text{T\_mQ}=\frac{\dot{Q}}{\text{S\_Q}}
"""
i = self.inl[0]
o = self.outl[0]
p1_star = i.p.val_SI * (o.p.val_SI / i.p.val_SI) ** 0.5
s1_star = s_mix_ph(
p1_star, i.h.val_SI, i.fluid_data, i.mixing_rule, T0=i.T.val_SI
)
s2_star = s_mix_ph(
p1_star, o.h.val_SI, o.fluid_data, o.mixing_rule, T0=o.T.val_SI
)
self.S_Q = i.m.val_SI * (s2_star - s1_star)
self.S_irr = i.m.val_SI * (o.s.val_SI - i.s.val_SI) - self.S_Q
self.T_mQ = (o.h.val_SI - i.h.val_SI) / (s2_star - s1_star)
[docs]
def exergy_balance(self, T0):
r"""
Calculate exergy balance of a simple heat exchanger.
The exergy of heat is calculated by allocation of thermal and
mechanical share of exergy in the physical exergy. Depending on the
temperature levels at the inlet and outlet of the heat exchanger as
well as the direction of heat transfer (input or output) fuel and
product exergy are calculated as follows.
Parameters
----------
T0 : float
Ambient temperature T0 / K.
Note
----
If the fluid transfers heat to the ambient, you can specify
:code:`mysimpleheatexchanger.set_attr(dissipative=False)` if you do
NOT want the exergy production nan (only applicable in case
:math:`\dot{Q}<0`).
.. math ::
\dot{E}_\mathrm{P} =
\begin{cases}
\begin{cases}
\begin{cases}
\text{not defined (nan)} & \text{if dissipative}\\
\dot{E}_\mathrm{in}^\mathrm{T} - \dot{E}_\mathrm{out}^\mathrm{T} &
\text{else}\\
\end{cases}
& T_\mathrm{in}, T_\mathrm{out} \geq T_0\\
\dot{E}_\mathrm{out}^\mathrm{T}
& T_\mathrm{in} \geq T_0 > T_\mathrm{out}\\
\dot{E}_\mathrm{out}^\mathrm{T} - \dot{E}_\mathrm{in}^\mathrm{T}
& T_0 \geq T_\mathrm{in}, T_\mathrm{out}\\
\end{cases} & \dot{Q} < 0\\
\begin{cases}
\dot{E}_\mathrm{out}^\mathrm{PH} - \dot{E}_\mathrm{in}^\mathrm{PH}
& T_\mathrm{in}, T_\mathrm{out} \geq T_0\\
\dot{E}_\mathrm{in}^\mathrm{T} + \dot{E}_\mathrm{out}^\mathrm{T}
& T_\mathrm{out} > T_0 \geq T_\mathrm{in}\\
\dot{E}_\mathrm{in}^\mathrm{T} - \dot{E}_\mathrm{out}^\mathrm{T} +
\dot{E}_\mathrm{out}^\mathrm{M} - \dot{E}_\mathrm{in}^\mathrm{M} +
& T_0 \geq T_\mathrm{in}, T_\mathrm{out}\\
\end{cases} & \dot{Q} > 0\\
\end{cases}
\dot{E}_\mathrm{F} =
\begin{cases}
\begin{cases}
\dot{E}_\mathrm{in}^\mathrm{PH} - \dot{E}_\mathrm{out}^\mathrm{PH}
& T_\mathrm{in}, T_\mathrm{out} \geq T_0\\
\dot{E}_\mathrm{in}^\mathrm{T} + \dot{E}_\mathrm{in}^\mathrm{M} +
\dot{E}_\mathrm{out}^\mathrm{T} - \dot{E}_\mathrm{out}^\mathrm{M}
& T_\mathrm{in} \geq T_0 > T_\mathrm{out}\\
\dot{E}_\mathrm{out}^\mathrm{T} - \dot{E}_\mathrm{in}^\mathrm{T} +
\dot{E}_\mathrm{in}^\mathrm{M} - \dot{E}_\mathrm{out}^\mathrm{M} +
& T_0 \geq T_\mathrm{in}, T_\mathrm{out}\\
\end{cases} & \dot{Q} < 0\\
\begin{cases}
\dot{E}_\mathrm{out}^\mathrm{T} - \dot{E}_\mathrm{in}^\mathrm{T}
& T_\mathrm{in}, T_\mathrm{out} \geq T_0\\
\dot{E}_\mathrm{in}^\mathrm{T} + \dot{E}_\mathrm{in}^\mathrm{M} -
\dot{E}_\mathrm{out}^\mathrm{M}
& T_\mathrm{out} > T_0 \geq T_\mathrm{in}\\
\dot{E}_\mathrm{in}^\mathrm{T}-\dot{E}_\mathrm{out}^\mathrm{T}
& T_0 \geq T_\mathrm{in}, T_\mathrm{out}\\
\end{cases} & \dot{Q} > 0\\
\end{cases}
\dot{E}_\mathrm{bus} =
\begin{cases}
\begin{cases}
\dot{E}_\mathrm{P} & \text{other cases}\\
\dot{E}_\mathrm{in}^\mathrm{T}
& T_\mathrm{in} \geq T_0 > T_\mathrm{out}\\
\end{cases} & \dot{Q} < 0\\
\dot{E}_\mathrm{F} & \dot{Q} > 0\\
\end{cases}
"""
if self.dissipative.val is None:
self.dissipative.val = True
msg = (
"In a future version of TESPy, the dissipative property must "
"explicitly be set to True or False in the context of the "
f"exergy analysis for component {self.label}."
)
logger.warning(msg)
if self.Q.val < 0:
if self.inl[0].T.val_SI >= T0 and self.outl[0].T.val_SI >= T0:
if self.dissipative.val:
self.E_P = np.nan
else:
self.E_P = self.inl[0].Ex_therm - self.outl[0].Ex_therm
self.E_F = self.inl[0].Ex_physical - self.outl[0].Ex_physical
self.E_bus = {
"chemical": 0, "physical": 0, "massless": self.E_P
}
elif self.inl[0].T.val_SI >= T0 and self.outl[0].T.val_SI < T0:
self.E_P = self.outl[0].Ex_therm
self.E_F = self.inl[0].Ex_therm + self.outl[0].Ex_therm + (
self.inl[0].Ex_mech - self.outl[0].Ex_mech)
self.E_bus = {
"chemical": 0, "physical": 0,
"massless": self.inl[0].Ex_therm + self.outl[0].Ex_therm
}
elif self.inl[0].T.val_SI <= T0 and self.outl[0].T.val_SI <= T0:
self.E_P = self.outl[0].Ex_therm - self.inl[0].Ex_therm
self.E_F = self.outl[0].Ex_therm - self.outl[0].Ex_therm + (
self.inl[0].Ex_mech - self.outl[0].Ex_mech)
self.E_bus = {
"chemical": 0, "physical": 0, "massless": self.E_P
}
else:
msg = ('Exergy balance of simple heat exchangers, where '
'outlet temperature is higher than inlet temperature '
'with heat extracted is not implmented.')
logger.warning(msg)
self.E_P = np.nan
self.E_F = np.nan
self.E_bus = {
"chemical": np.nan, "physical": np.nan, "massless": np.nan
}
elif self.Q.val > 0:
if self.inl[0].T.val_SI >= T0 - 1e-6 and self.outl[0].T.val_SI >= T0 - 1e-6:
self.E_P = self.outl[0].Ex_physical - self.inl[0].Ex_physical
self.E_F = self.outl[0].Ex_therm - self.inl[0].Ex_therm
self.E_bus = {
"chemical": 0, "physical": 0, "massless": self.E_F
}
elif self.inl[0].T.val_SI <= T0 and self.outl[0].T.val_SI > T0:
self.E_P = self.outl[0].Ex_therm + self.inl[0].Ex_therm
self.E_F = self.inl[0].Ex_therm + (
self.inl[0].Ex_mech - self.outl[0].Ex_mech)
self.E_bus = {
"chemical": 0, "physical": 0,
"massless": self.inl[0].Ex_therm
}
elif self.inl[0].T.val_SI < T0 and self.outl[0].T.val_SI < T0:
if self.dissipative.val:
self.E_P = np.nan
else:
self.E_P = self.inl[0].Ex_therm - self.outl[0].Ex_therm + (
self.outl[0].Ex_mech - self.inl[0].Ex_mech
)
self.E_F = self.inl[0].Ex_therm - self.outl[0].Ex_therm
self.E_bus = {
"chemical": 0, "physical": 0, "massless": self.E_F
}
else:
msg = ('Exergy balance of simple heat exchangers, where '
'inlet temperature is higher than outlet temperature '
'with heat injected is not implmented.')
logger.warning(msg)
self.E_P = np.nan
self.E_F = np.nan
self.E_bus = {
"chemical": np.nan, "physical": np.nan, "massless": self.E_F
}
else:
# fully dissipative
self.E_P = np.nan
self.E_F = self.inl[0].Ex_physical - self.outl[0].Ex_physical
self.E_bus = {
"chemical": np.nan, "physical": np.nan, "massless": np.nan
}
if np.isnan(self.E_P):
self.E_D = self.E_F
else:
self.E_D = self.E_F - self.E_P
self.epsilon = self._calc_epsilon()
[docs]
def get_plotting_data(self):
"""Generate a dictionary containing FluProDia plotting information.
Returns
-------
data : dict
A nested dictionary containing the keywords required by the
:code:`calc_individual_isoline` method of the
:code:`FluidPropertyDiagram` class. First level keys are the
connection index ('in1' -> 'out1', therefore :code:`1` etc.).
"""
return {
1: {
'isoline_property': 'p',
'isoline_value': self.inl[0].p.val,
'isoline_value_end': self.outl[0].p.val,
'starting_point_property': 's',
'starting_point_value': self.inl[0].s.val,
'ending_point_property': 's',
'ending_point_value': self.outl[0].s.val
}
}
[docs]
class HeatExchangerSimple(SimpleHeatExchanger):
def __init__(self, label, **kwargs):
super().__init__(label, **kwargs)
msg = (
"The API for the component HeatExchangerSimple will change with "
"the next major release, please import SimpleHeatExchanger instead."
)
warnings.warn(msg, FutureWarning)