Parameter values

The parameter values PyTES provides, read from the code at each build. A parameter set is composed from layers of several kinds, so that one, e.g. the PCM, can be swapped without touching the rest (see pytes.parameter_layers). Every value is in SI units, under the name the models read. Each layer gives its source and, for the materials and fluids, the temperature at which its values were taken: the models hold one value per phase, constant in temperature.

A set or a layer is obtained with:

import pytes

parameter_values = pytes.parameter_layers.compose_set("Finned tube default")
pcm = pytes.parameter_layers.get("pcm", "PCM 60")

Parameter sets

The named sets, composed with pytes.parameter_layers.compose_set(). The default parameter values of each family are one of them.

Finned tube default

Kind	Layer
Operation	Finned tube discharge
Coupling	Finned tube default
Heat transfer fluid	Water
Phase-change material	PCM 60
Metal	Aluminium
Finned-tube flow path	Finned tube default
Finned-tube storage element	Finned tube default

Nallusamy2007

Kind	Layer
Operation	Nallusamy2007
Coupling	Packed bed default
Heat transfer fluid	Water
Phase-change material	Paraffin (Nallusamy 2007)
Packed-bed flow path	Nallusamy2007
Packed-bed storage element	Nallusamy2007

Raul2018

Kind	Layer
Operation	Raul2018
Coupling	Packed bed default
Heat transfer fluid	Hytherm 600
Phase-change material	A164 (Raul 2018)
Packed-bed flow path	Raul2018
Packed-bed storage element	Raul2018

Layers

The registered layers of each kind, obtained with pytes.parameter_layers.get().

Operation

How the device is run: the energy reference, the initial state and the controls (DESIGN D14).

Finned tube discharge

A discharge of the default finned-tube battery: from uniform and liquid at 70 °C, with water at 10 °C. Meant for “PCM 60”, which melts at 60 °C.

These values are illustrative and not based on any source.

pytes.parameter_layers.get("operation", "Finned tube discharge")

Parameter	Value
Reference temperature [K]	283.15 (10 °C)
Initial temperature [K]	343.15 (70 °C)
Inlet temperature [K]	283.15 (10 °C)
Mass flow rate [kg.s-1]	0.02

Nallusamy2007

The charge of Nallusamy, Sampath and Velraj (2007): from 32 °C, with water at 70 °C and 2 l/min.

Source:

Nallusamy, Sampath and Velraj (2007).

pytes.parameter_layers.get("operation", "Nallusamy2007")

Parameter	Value
Reference temperature [K]	305.15 (32 °C)
Initial temperature [K]	305.15 (32 °C)
Inlet temperature [K]	343.15 (70 °C)
Mass flow rate [kg.s-1]	0.0333333

Raul2018

The charge of Raul et al. (2018): from 400 K, with Hytherm 600 at 180 °C and 8.2 l/min.

Source:

Raul et al. (2018).

pytes.parameter_layers.get("operation", "Raul2018")

Parameter	Value
Reference temperature [K]	400 (126.85 °C)
Initial temperature [K]	400 (126.85 °C)
Inlet temperature [K]	453.15 (180 °C)
Mass flow rate [kg.s-1]	0.0985

Coupling

Parameters of the surface flux law between the fluid and the storage (DESIGN D6, D8).

Finned tube default

The coefficient of the default finned-tube battery.

The value is an estimate, not based on any source.

pytes.parameter_layers.get("coupling", "Finned tube default")

Parameter	Value
Heat transfer coefficient [W.m-2.K-1]	1000

Packed bed default

The coefficient of the packed beds (“Nallusamy2007” and “Raul2018” sets).

The value is an estimate, not based on any source.

pytes.parameter_layers.get("coupling", "Packed bed default")

Parameter	Value
Heat transfer coefficient [W.m-2.K-1]	100

Heat transfer fluid

The heat transfer fluid, as read by pytes.fluids.ConstantPropertyLiquid.

Water

Liquid water. It does not change phase.

Source:

CRC Handbook of Chemistry and Physics, 95th edition (2014).

Taken at:

293.15 K.

pytes.parameter_layers.get("heat_transfer_fluid", "Water")

Parameter	Value
Heat transfer fluid density [kg.m-3]	998.21
Heat transfer fluid specific heat capacity [J.kg-1.K-1]	4184.1
Heat transfer fluid conductivity [W.m-1.K-1]	0.6
Heat transfer fluid viscosity [Pa.s]	0.001

Hytherm 600

Hytherm 600, a heat transfer oil.

Source:

Raul et al. (2018).

Taken at:

not specified.

pytes.parameter_layers.get("heat_transfer_fluid", "Hytherm 600")

Parameter	Value
Heat transfer fluid density [kg.m-3]	720.9
Heat transfer fluid specific heat capacity [J.kg-1.K-1]	3097.4
Heat transfer fluid conductivity [W.m-1.K-1]	0.116
Heat transfer fluid viscosity [Pa.s]	0.0195

Phase-change material

The phase-change material, as read by pytes.materials.PureMaterial. “PCM smoothing width [K]” is numerical, but stays in this layer for now (issue #3).

Paraffin (Nallusamy 2007)

The paraffin of Nallusamy, Sampath and Velraj (2007).

Source:

Nallusamy, Sampath and Velraj (2007).

Taken at:

not specified.

pytes.parameter_layers.get("pcm", "Paraffin (Nallusamy 2007)")

Parameter	Value
PCM solid phase conductivity [W.m-1.K-1]	0.4
PCM liquid phase conductivity [W.m-1.K-1]	0.15
PCM solid phase density [kg.m-3]	861
PCM liquid phase density [kg.m-3]	778
PCM solid phase specific heat capacity [J.kg-1.K-1]	1850
PCM liquid phase specific heat capacity [J.kg-1.K-1]	2384
PCM latent heat [J.kg-1]	213000
PCM melting temperature [K]	333.15 (60 °C)
PCM melting range [K]	0
PCM smoothing width [K]	0.01

A164 (Raul 2018)

A164, the PCM of Raul et al. (2018).

Source:

Raul et al. (2018).

Taken at:

not specified.

pytes.parameter_layers.get("pcm", "A164 (Raul 2018)")

Parameter	Value
PCM solid phase conductivity [W.m-1.K-1]	0.45
PCM liquid phase conductivity [W.m-1.K-1]	0.45
PCM solid phase density [kg.m-3]	1500
PCM liquid phase density [kg.m-3]	1500
PCM solid phase specific heat capacity [J.kg-1.K-1]	2013.3
PCM liquid phase specific heat capacity [J.kg-1.K-1]	2013.3
PCM latent heat [J.kg-1]	249700
PCM melting temperature [K]	441.85 (168.7 °C)
PCM melting range [K]	0
PCM smoothing width [K]	0.01

PCM 10N

A representative PCM for cold storage applications. The values are representative of a commercial PCM, but not of any one product.

Taken at:

not specified.

pytes.parameter_layers.get("pcm", "PCM 10N")

Parameter	Value
PCM solid phase conductivity [W.m-1.K-1]	0.6
PCM liquid phase conductivity [W.m-1.K-1]	0.4
PCM solid phase density [kg.m-3]	1000
PCM liquid phase density [kg.m-3]	1200
PCM solid phase specific heat capacity [J.kg-1.K-1]	2000
PCM liquid phase specific heat capacity [J.kg-1.K-1]	3500
PCM latent heat [J.kg-1]	330000
PCM melting temperature [K]	263.15 (-10 °C)
PCM melting range [K]	1
PCM smoothing width [K]	0.01

PCM 30

A representative PCM for room temperature applications. The values are representative of a commercial PCM, but not of any one product.

Taken at:

not specified.

pytes.parameter_layers.get("pcm", "PCM 30")

Parameter	Value
PCM solid phase conductivity [W.m-1.K-1]	0.3
PCM liquid phase conductivity [W.m-1.K-1]	0.15
PCM solid phase density [kg.m-3]	1000
PCM liquid phase density [kg.m-3]	850
PCM solid phase specific heat capacity [J.kg-1.K-1]	2200
PCM liquid phase specific heat capacity [J.kg-1.K-1]	2800
PCM latent heat [J.kg-1]	180000
PCM melting temperature [K]	303.15 (30 °C)
PCM melting range [K]	3
PCM smoothing width [K]	0.01

PCM 60

A representative PCM for hot water applications. The values are representative of a commercial PCM, but not of any one product.

Taken at:

not specified.

pytes.parameter_layers.get("pcm", "PCM 60")

Parameter	Value
PCM solid phase conductivity [W.m-1.K-1]	0.6
PCM liquid phase conductivity [W.m-1.K-1]	0.5
PCM solid phase density [kg.m-3]	1400
PCM liquid phase density [kg.m-3]	1300
PCM solid phase specific heat capacity [J.kg-1.K-1]	2500
PCM liquid phase specific heat capacity [J.kg-1.K-1]	3000
PCM latent heat [J.kg-1]	250000
PCM melting temperature [K]	333.15 (60 °C)
PCM melting range [K]	2
PCM smoothing width [K]	0.01

Metal

The metal of the fins, as read by pytes.materials.SensibleMaterial. One metal per device for now (issue #3).

Aluminium

Pure aluminium.

Source:

CRC Handbook of Chemistry and Physics, 95th edition (2014).

Taken at:

298 K for density and heat capacity, 300 K for thermal conductivity.

pytes.parameter_layers.get("metal", "Aluminium")

Parameter	Value
Metal conductivity [W.m-1.K-1]	237
Metal density [kg.m-3]	2700
Metal specific heat capacity [J.kg-1.K-1]	897

Steel

Stainless steel, grade 310.

Source:

CRC Handbook of Chemistry and Physics, 95th edition (2014).

Taken at:

298 K.

pytes.parameter_layers.get("metal", "Steel")

Parameter	Value
Metal conductivity [W.m-1.K-1]	12.67
Metal density [kg.m-3]	7829
Metal specific heat capacity [J.kg-1.K-1]	483

Copper

Copper.

Source:

CRC Handbook of Chemistry and Physics, 95th edition (2014).

Taken at:

298 K for density and heat capacity, 300 K for thermal conductivity.

pytes.parameter_layers.get("metal", "Copper")

Parameter	Value
Metal conductivity [W.m-1.K-1]	401
Metal density [kg.m-3]	8960
Metal specific heat capacity [J.kg-1.K-1]	385

Finned-tube flow path

The tubes of the finned-tube family, and so the size of the device (see pytes.models.finned_tube.FinnedTubeParameters).

Finned tube default

The tube of the default finned-tube battery.

These values are illustrative and not based on any source.

pytes.parameter_layers.get("finned_tube_flow_path", "Finned tube default")

Parameter	Value
Number of tubes	1
Tube radius [m]	0.003
Tube length [m]	10

Finned-tube storage element

The fins of the finned-tube family, per unit length of tube (see pytes.models.finned_tube.FinnedTubeParameters).

Finned tube default

The fins of the default finned-tube battery.

These values are illustrative and not based on any source.

pytes.parameter_layers.get("finned_tube_storage_element", "Finned tube default")

Parameter	Value
Fin thickness [m]	0.0002
Fin pitch [m]	0.003
Storage depth [m]	0.02

Packed-bed flow path

The bed of the packed-bed family, and so the size of the device (see pytes.models.packed_bed.PackedBedParameters).

Nallusamy2007

The tank of Nallusamy, Sampath and Velraj (2007): 360 mm in diameter, 460 mm high.

Source:

Nallusamy, Sampath and Velraj (2007).

pytes.parameter_layers.get("packed_bed_flow_path", "Nallusamy2007")

Parameter	Value
Bed length [m]	0.46
Bed cross-sectional area [m2]	0.101788

Raul2018

The bed of Raul et al. (2018): 170 mm in diameter, 360 mm long.

Source:

Raul et al. (2018).

pytes.parameter_layers.get("packed_bed_flow_path", "Raul2018")

Parameter	Value
Bed length [m]	0.36
Bed cross-sectional area [m2]	0.022698

Packed-bed storage element

The capsules of the packed-bed family and how they pack (see pytes.models.packed_bed.PackedBedParameters).

Nallusamy2007

The capsules of Nallusamy, Sampath and Velraj (2007), 55 mm in diameter, and how they pack.

Source:

Nallusamy, Sampath and Velraj (2007).

pytes.parameter_layers.get("packed_bed_storage_element", "Nallusamy2007")

Parameter	Value
Capsule radius [m]	0.0275
Bed porosity	0.5

Raul2018

The capsules of Raul et al. (2018), 31 mm in diameter, and how they pack.

Source:

Raul et al. (2018).

pytes.parameter_layers.get("packed_bed_storage_element", "Raul2018")

Parameter	Value
Capsule radius [m]	0.0155
Bed porosity	0.6

Default capsule

A generic spherical capsule, randomly packed in a bed large compared with the capsules.

These values are illustrative and not based on any source.

pytes.parameter_layers.get("packed_bed_storage_element", "Default capsule")

Parameter	Value
Capsule radius [m]	0.02
Bed porosity	0.5