Tensor Representation and Utility Classes

The basis for Tensor Mechanics is the tensor representation classes. The two base classes are RankTwoTensor and RankFourTensor, which as expected hold 3x3 values and 3x3x3x3 values, respectively. A suite of operators and get/set methods are available.

Specifying Values from an Input File

Full tensor notation

Both RankTwoTensor and RankFourTensor allow a user to specify how to the tensor from an input file.

  • RankTwoTensor takes a vector of six or nine inputs. If six inputs are used, the appropriate symmetries are maintained ().

  • RankFourTensor takes a vector of inputs of the appropriate length to fill in the tensor, with the appropriate symmetries maintained Several fill methods are available to specify additional symmetries as described in ComputeElasticityTensor.

Symmetric Mandel notation tensors

  • SymmetricRankTwoTensor uses the 6-vector representation of a symmetric rank two tensor.

  • SymmetricRankFourTensor uses the 6x6 matrix representation with Mandel notation coefficients. The Mandel notation was chosen as it yields meaningful eigenvectors.

Getting and Setting Specific Component Values

Both RankTwoTensor and RankFourTensor allow a user to get and set values from the tensor using the bracket () notation.


RankTwoTensor a;
a(i,j) = val;

sets the i,j component of the tensor to val. We use zero based indexing for the dimensions (0, 1, and 2).


RankFourTensor b;
b(i,j,k,l) = val;

sets the i,j,k,l component of the tensor to val. We use zero based indexing for the dimensions (0, 1, and 2).

Use the same notation to read tensor components.


RankTwoTensor a;
RankFourTensor b;
Real c;
c = a(0,0);
c = b(0,0,0,0);

Tensor Operations

See the list of available operators and matrix operations for the RankTwoTensor, RankThreeTensor, and RankFourTensor in the description of the MOOSE Utility Classes.