Model and integral operators

The class tamaas::Model (and its counterpart Model) is both a central class in Tamaas and one of the simplest. It mostly serves as holder for material properties, fields and integral operators, and apart from a linear elastic behavior does not perform any computation on its own.

Model types

tamaas::Model has a concrete subclass tamaas::ModelTemplate which implements the model function for a given tamaas::model_type:


Model type used in normal frictionless contact: traction and displacement are 2D fields with only one component.


Model type used in frictional contact: traction and displacement are 2D fields with three components.


Model type used in elastoplastic contact: tractions are the same as with tamaas::surface_2d but the displacement is a 3D field.

The enumeration values suffixed with _1d are the one dimensional (line contact) counterparts of the above model types. The domain physical dimension and number of components are encoded in the class tamaas::model_type_traits.

Model creation and basic functionality

The instanciation of a Model is done with the ModelFactory class and its createModel function:

physical_size = [1., 1.]
discretization = [512, 512]
model = tm.ModelFactory.createModel(tm.model_type.basic_2d, physical_size, discretization)


For models of type volume_*d, the first component of the physical_size and discretization arrays corresponds to the depth dimension (\(z\) in most cases). For example:

tm.ModelFactory.createModel(tm.model_type.basic_2d, [0.3, 1, 1], [64, 81, 81])

creates a model of depth 0.3 and surface size 12, while the number of points is 64 in depth and 812 on the surface. This is done for data contiguity reasons, as we do discrete Fourier transforms in the horizontal plane.


If ran in an MPI context, the method createModel expects the global system sizes and discretization of the model.


Deep copies of model objects can be done with the copy.deepcopy() function:

import copy

model_copy = copy.deepcopy(model)

Note that it only copies fields, not operators or dumpers.

Model properties

The properties E and nu can be used to set the Young’s modulus and Poisson ratio respectively:

model.E = 1 = 0.3

Fields can be easlily accessed with the [] operator, similar to Python’s dictionaries:

surface_traction = model['traction']
# surface_traction is a numpy array

To know what fields are available, you can call the list function on a model (list(model)). You can add new fields to a model object with the [] operator:model['new_field'] = new_field, which is convenient for dumping fields that are computed outside of Tamaas.


The fields traction and displacement are always registered in models, and are accessible via model.traction and model.displacement.

A model can also be used to compute stresses from a strain field:

import numpy

strain = numpy.zeros(model.shape + [6])  # Mandel--Voigt notation
stress = numpy.zeros_like(strain)

model.applyElasticity(stress, strain)


print(model) gives a lot of information about the model: the model type, shape, registered fields, and more!

Integral operators

Integral operators are a central part of Tamaas: they are carefully designed for performance in periodic system. When a Model object is used with contact solvers or with a residual object (for plasticty), the objects using the model register integral operators with the model, so the user typically does not have to worry about creating integral operators.

Integral operators are accessed through the operators property of a model object. The [] operator gives access to the operators, and list(model.operators) gives the list of registered operators:

# Accessing operator
elasticity = model.operators['hooke']

# Applying operator
elasticity(strain, stress)

# Print all registered operators


At model creation, these operators are automatically registered:

  • hooke: Hooke’s elasticity law

  • von_mises: computes Von Mises stresses

  • deviatoric: computes the deviatoric part of a stress tensor

  • eigenvalues: computes the eigenvalues of a symetric tensor field

Westergaard operators are automatically registered when solveNeumann or solveDirichlet are called.

Model dumpers

The submodule tamaas.dumpers contains a number of classes to save model data into different formats:


Dumps a model to VTK format. Requires the UVW python package which you can install with pip:

pip install uvw

This dumper is made for visualization with VTK based software like Paraview.


Dumps a model to a compressed Numpy file.


Dumps a model to a compressed HDF5 file. Requires the h5py package. Saves separate files for each dump of a model.


Dumps a model to a compressed NetCDF file. Requires the netCDF4 package. Saves sequential dumps of a model into a single file, with the frame dimension containing the model dumps.

The dumpers are initialzed with a basename and the fields that you wish to write to file (optionally you can set all_fields to True to dump all fields in the model). By default, each write operation creates a new file in a separate directory (e.g. UVWDumper creates a paraview directory). To write to a specific file you can use the dump_to_file method. Here is a usage example:

from tamaas.dumpers import UVWDumper, H5Dumper

# Create dumper
uvw_dumper = UVWDumper('rough_contact_example', 'stress', 'plastic_strain')

# Dump model
uvw_dumper << model

# Or alternatively
model.addDumper(H5Dumper('rough_contact_archive', all_fields=True))

The last model.dump() call will trigger all dumpers. The resulting files will have the following hierachy:



Currently, only H5Dumper supports parallel output with MPI.