Input definition
The hamopy algorithm is called like so:
from hamopy.algorithm import calcul
results = calcul(mesh, clim, init, time)
This means that all inputs of the simulation are contained within 4 objects that serve as arguments for the calcul method:
meshcontains all information regarding the material definition and spatial discretisation of the domainclimstores boundary conditionsinitdefines the initialisation of the domaintimespecifies the time of simulation, time step size, etc.
Below is the syntax for the definition of these objects.
mesh: material definition and discretisation
The mesh argument is created by instantiating a new object of the hamopy.classes.Mesh class.
from hamopy.classes import Mesh
from hamopy.materials.standard import wood_fibre
mesh = Mesh(materials = [wood_fibre],
sizes = [0.08],
nbr_elements = [16] )
The example above imports the wood fibre board from the hamopy.materials.standard material library. Then, it creates a wall of thickness 0.08 m, discretised with 16 finite elements.
Here is an example of a multi-layered wall:
from hamopy.classes import Mesh
from hamopy.materials.standard import concrete, wood_fibre
mesh = Mesh(materials = [concrete, wood_fibre],
sizes = [0.10, 0.08],
nbr_elements = [24, 16] )
From left to right, this example creates a wall with a 10 cm concrete layer divided into 24 finite elements, and an 8 cm wood fibre layer with 16 finite elements.
The instantiation of the Mesh class always takes 3 arguments: materials, sizes and nbr_elements. These arguments are always lists, even when only one layer is involved as in the first example.
Materials must be imported before the mesh is created. They are objects of the Material class: the materials page of this site shows how to define one.
clim: boundary conditions
The clim argument sent to the simulation is a list of two objects of the Boundary class.
from hamopy.classes import Boundary
clim_01 = Boundary('Dirichlet',**{"T" : 293.15,
"HR" : 0.7 })
clim_02 = Boundary('Fourier',**{"T" : 278.15,
"HR" : 0.9,
"h_t" : 5 })
clim = [clim_01, clim_02]
Two boundaries are created separately and stored in the clim list. The first one is a constant type one (Dirichlet) condition of 293.15 K and 0.7 relative humidity. The second one is a type three (Fourier) conditions with a surface transfer coefficient of 5 [W/(m2K)].
The instantiation of a boundary requires two arguments: a string to specify the boundary type, and a dictionary to specify numerical data.
The example above is very simple, but things can get a little more complicated: boundary conditions can be variable in time and more parameters can be specified (air pressure, surface transfer coefficients...) The boundary conditions page shows how to do all that.
init: initialisation
The init object is simply a dictionary containing the initial value of the temperature under the 'T' key, and of the relative humidity under the 'HR' key:
init = {'T' : 293.15,
'HR' : 0.95}
Alternatively, the relative humidity can be replaced by a value of vapor pressure with the 'PV' key or of capillary pressure with the 'PC' key.
It is possible to define non-uniform initial conditions, by adding an 'x' key to the dictionary:
init = {'x' : [0, 0.05, 0.10],
'T' : [273, 287, 291],
'HR' : [0.7, 0.4, 0.6] }
In this example, the initial conditions will be a linear interpolation of the values given at the coordinates 0, 0.05, and 0.10 m.
time: temporal discretisation
The object storing information on the discretisation in time is an occurence of the Time class. Its instantiation resembles that of the Boundary object:
from hamopy.classes import Time
time = Time('constant',**{"delta_t" : 600,
"t_max" : 7200 } )
The definition of the time requires two input arguments: a string indicating whether the time step size should be constant or variable, and a dictionary containing numerical data. In the example above, it is declared that the time step size delta_t is 600 seconds, and that the simulation time t_max is 7200 seconds.
It is possible to ask for the time step size to automatically adapt to eventual convergence difficulties. This is done by setting the method string to 'variable', and optionnaly adding some keys to the dictionary:
'iter_max': maximum number of iterations in a time step (default is 12)'delta_min': minimum time step size (default is 1e-3)'delta_max': maximum time step size (default is 900)
Once all 4 objects are defined, you can start the simulation.