Overview of Elasticity of Materials/Introduction to Tensors

Introduction to Tensors edit

We've been working with stress and in particular looking as stress at a point and the impact of rotating the reference frame. Using the tools in the previous sections it is possible to identify the principal stresses and the orientation of the reference frame relative to the principal axis, which allows determination of the stress state in any orientation. This allows determination of the orientation and value of the maximum shear and normal forces, which are critical for engineering design. As you've see, computing this information requires either extensive use of equations or geometry/trigonometry. In this section tensors are going to be introduced, which will allow for a more elegant means of addressing coordination transformations.

Lets begin by thinking about vectors, such as

 

This vector is represented using the   coordinates, but it just as well could have been expressed relative to a different set, which we will call  . The direction cosines, the cosine between all the axis of the two coordinate systems, allows us to rewrite the vector

 

where   is the cosine between   and   and can be rewritten   allowing forː

            [eq 1]
            [eq 2]
            [eq 3]

recognizing that for the cosine of an angle  . Equations 1-3 can be written in a compact form, known as Einstein notation:

            [eq 4]

In Einstein notation, if a subscript is seen two or more times on a side of an equation, a summation is performed. In the example above, the   shows up twice on the right side of the equation, but the   only once. This means that this equation becomes:

 

In this equation   is a dummy variable; substituting the value 1, 2, or 3 in for   returns the equations above.

Here   is a rank 2 tensor that relates the two vectors   and  . Tensors are geometric objects that describe the linear relationship between scalars, vectors, and other tensors. Are the vector's   and   tensors? Although vectors can be tensors, in this case they are not because   and   do not act to map linear spaces onto each other. The rank of a tensor is the number of indexes needed to describe it, therefore   is a rank two tensor because it requires   and  ,  , to describe it.

Tensors are used frequently, to represent the intrinsic physical properties of materials. A good example is the electrical conductivity,  , a rank two tensor that expresses the current density in a material   induced by the application of an electric field,  .

 

Both   and   are vectors since they have both a magnitude and direction. Interestingly, the off-axis terms in   implies cross interactions between the vectors, e.g., the current response in the   direction is influenced by the electric field in the   and   directions, which is indeed true.

There are many other tensors that represent materials properties including the thermal conductivity, diffusivity, permittivity, dielectric susceptibility, permeability, and magnetic susceptibility to name a few. We will see that stress, and strain also are tensors. Stress relates the surface normal to an arbitrary imaginary surface,  , to the stress vector at that point,  , as was discussed in the previous section.

Tensor Transformations edit

The vectors that represent material properties also must be able to transform. This is useful to allow coordinate transformation, which essentially are rotations. It also allows the tensors that represent material responses to transform according to crystallographic symmetry; these can involve rotations, mirror operations, and inversions. Because these transformations involve linear one-to-one mapping, the transformation themselves are enabled by transformation tensors.

In equation 4 we rotated vector   to   by applying transformation tensor  

 

What if we want to reverse this? We can simply reverse the equation

            [eq 5]

Note that there are implications here regarding the inversion of  . Since

 

we have that   which means that transposing   yields the inverse of  , written  .

Consider now that there is a second vector that we'll call   is related to   by the rank two materials property tensor  

             [eq 6]

In a transformed coordinate system we'll express this as

            [eq 7]

So we can now write

 

This tells us that the transformation of   to   causes the transformations from   to  ,   to  , and   to  , where the vector transformations are given by equations 4 & 5, and the tensor transformation is given by

            [eq 8]

and

            [eq 9]

Note that these solutions are really double sums over   and  , due to Einstein Notation.

Because the order of the summation is not important, we can writeː

            [eq 10]

This is a Tensor that relates   and  . Since it is a double sum, each term in   has nine elements and the total tensor mapping the relationship between   and   must have a total of   terms as  .

Tensor Symmetry edit

The nature of a tensor is determined by it's application. There are subsets of tensors that we can classify according to their symmetry properties.

Symmetric tensors have a structure such asː   where  


Antisymmetric Tensors have a structure such asː   where  


Note that the main diagonal of an antisymmetric tensor must be zero and the overall symmetry or antisymmetry depends on the reference frame selected. Any second rank tensor can be expressed as a sum of a symmetric and antisymmetric tensor asː

            [eq 11]

We will find this useful in the next section dealing with strain. Meanwhile, any symmetric tensor can be transformed by rotations to be aligned along its principal axis, such thatː

 

The properties of tensors are highly tied to the crystal symmetry of the material they represent. For example, let's say that we have two vector properties   and   in a crystal which are related by a tensor  . If we rotate the reference farm according to a symmetry element of the crystal then

 .
 
Figure 1: Rotating a simple cubic crystal. Due to symmetry, the crystal will periodically rotate such that it is practically at the same orientation it started at.

Let's examine this by looking at a simple cubic crystal such as the one in Figure 1. When rotated, this crystal will periodically rotate back on itself, and the properties of the relevant tensors should do the same. By applying this theory to each possible crystal formations, we can develop simplified tensors for each, which represent this symmetry.

Crystal Tensors
Crystal

Formation

Tensor Number of

Independent

Components

Cubic
 
1
Tetragonal

Hexagonal

Trigonal

 
2
Orthorhombic
 
3
Monoclinic
 
4
Triclinic
 
6

Tensor Contractions and Invariant Relations in Stress edit

Much of this discussion has been about property relations, but here our interest is in the stress tensor; a symmetric tensor that can therefore be arranged to be aligned in the principal axis. Let's now rederive the 3D stress relationships using tensors. The stresses normal to an oblique plane are writtenː

            [eq 12]

Here the   is the direction of the normal to the plane and is the original stress state. If the oblique plane is a principal direction, with a normal stress of  , then we can write our equation asː

            [eq 13]

By combining equations 12 & 13, we getː

            [eq 14]

Kronecker Delta edit

Additionally, there is a handy expression called a Kronecker Delta   that has the propertiesː

 

When applied to a tensor, the Kronecker Delta is said to "contract" the tensor's rank by two. This turns a 4th rank tensor into a 2nd rank, a 3rd rank tensor into a 1st rank, etc... For the purpose of this text, we won't be using this expression often, but in applying this to equation 14   we can replace the scalar   with the contraction of the second rank tensor such thatː

 

The rule for contraction here is to replace   with  , and remove the Kronecker Delta term.

Returning to equation 14, we replace the   with our Kronecker Delta expansion to getː

            [eq 15]

This equation can be entirely summed over  , and because   is normal to the plane, this makes   equal to   and our equation evolves toː

            [eq 16]

This gives us a set of three equations where  . By substituting the direction cosines into the left term and using  ,  ,   and   when  , we can solve for the non-trivial (non-zero) solution by taking the determinant ofː

 

Which yields the same result as returned before.

The Three Invariants edit

We also identify the invariant relations. It should be noted that these also can come from the stress tensor. First, let's apply a contraction to  ː  

This is our first invariant. The second invariant comes from the minors of  , which can be used to expand the determinant.

 

The third invariant is the determinant of   where  .