Building a Thermal Model#

A thermal mathematical model (TMM) in pycanha consists of two main parts: nodes and couplings. Optionally, you can define parameters and formulas to link model quantities to parameters.

Creating a model#

Every analysis starts by instantiating a ThermalMathematicalModel:

from pycanha.tmm import ThermalMathematicalModel

tmm = ThermalMathematicalModel("MyModel")

Adding nodes#

Nodes represent lumped thermal masses with a temperature. Each node has a unique integer identifier (node_num) and several attributes like thermal capacity and heat loads. Nodes are either diffusive (temperature computed by the solver) or boundary.

from pycanha.tmm import Node, NodeType

# Diffusive node (temperature computed by solver)
node1 = Node(1)
node1.C  = 1000.0      # capacity [J/K]
node1.qi = 50.0         # internal dissipation [W]

# Boundary node (temperature fixed)
node2 = Node(2)
node2.type = NodeType.BOUNDARY
node2.T = 300.0         # fixed temperature [K]

tmm.add_node(node1)
tmm.add_node(node2)

Note

Internally, nodes are auto-sorted so that all diffusive nodes come before all boundary nodes. Use get_idx_from_node_num() to map between user node numbers and internal indices. This internal order is not guaranteed to remain as described here, so don’t rely on it in your code.

Node attributes#

Each node exposes the following scalar attributes:

Attribute	Description	Default
`T`	Temperature [K]	0.0
`C`	Thermal capacity [J/K]	0.0
`qi`	Internal dissipation [W]	0.0
`qs`	Solar absorbed heat [W]	0.0
`qa`	Albedo absorbed heat [W]	0.0
`qe`	Earth IR absorbed heat [W]	0.0
`qr`	Other heat loads [W]	0.0
`eps`	Emissivity	0.0
`aph`	Absorptivity	0.0
`fx`, `fy`, `fz`	User-defined auxiliary floats (e.g. position)	0.0

Adding couplings#

Couplings define the heat exchange between nodes.

# Conductive coupling: GL(1,2) = 0.5 W/K
tmm.conductive_couplings.add_coupling(1, 2, 0.5)

# Radiative coupling: GR(1,2) = 1e-7 m^2
tmm.radiative_couplings.add_coupling(1, 2, 1.0e-7)

Conductive couplings produce a heat flow proportional to the temperature difference: \(Q = GL \cdot (T_1 - T_2)\).

Radiative couplings produce a heat flow proportional to the difference of fourth powers: \(Q = \sigma \cdot GR \cdot (T_1^4 - T_2^4)\).

Accessing the thermal network#

The model exposes its internal containers through properties:

tmm.nodes                     # Nodes container
tmm.conductive_couplings      # ConductiveCouplings container
tmm.radiative_couplings       # RadiativeCouplings container
tmm.network                   # ThermalNetwork (nodes + couplings)
tmm.parameters                # Parameters storage
tmm.formulas                  # Formulas collection
tmm.thermal_data              # ThermalData result tables