What are
the differences between the vector and the tensor? What are the relation
between the mechanical rotations vectors and tensors? This topic will also
cover these all.
Any
quantity that has both magnitude and direction is called a vector. Velocity,
acceleration, and force are a few examples of mechanical vectors.
So, from the definition above it should be clear that every vector
must have two components: the magnitude component and the direction component.
In three dimensional space,
a vector is represented by its X, Y, Z components. The magnitude part of the
vector is
expressed by the matrix of numbers, and the direction part
of the vector is expressed by the matrix of unit vectors.
In the
adjacent picture, the vector a, which has three scalar
components ax,
ay, and az
and three
unit vectors i,
j, k along X, Y and Z, can
be represented as:
a= ax i + ay j
+ az k……………………(1.1)
In the
matrix representation of the vector, the starting point of the vector is
implicitly considered to be at the origin of the representing co-ordinate
system and this is how the vector is different than a point.
The above
vector can
also be represented in matrix form as:
The
following MathCAD example
is showing the inner product of two vectors:
And the result is 20, which is a scalar quantity. So, it can be
concluded that the inner product of the two vectors produce a scalar quantity.
So, by multiplying by a scalar quantity, all the three components of
the vector have scaled up proportionately or, in other words, the vector
changed its magnitude without changing its direction.
By, now
you know that if you want to change only the magnitude of a vector without
changing its direction, you will go for the multiplication of the vector with a
scalar quantity.
In case
you want to create a new vector with a different magnitude as well as direction
(than the initial vector) then you have to multiply the initial vector with
another type of mathematical entity called a tensor.
The
tensor is a more generalized form of scalar and vector. Or, the scalar, vector are
the special cases of tensor.
○ If a tensor has only
magnitude and no direction (i.e., rank 0 tensor), then it is called scalar.
○ If a tensor has
magnitude and one direction (i.e., rank 1 tensor), then it is called vector.
○ If a tensor has
magnitude and two directions (i.e., rank 2 tensor), then it is
called dyad.
○ And so on...
Please
note that there are differences between the term “direction" and
the term “dimension." All the types of tensor (scalar, vector,
and dyad) can
be defined in a three dimensional space or co-ordinate
system.
For
describing a rank-1 tensor, one subscript should be sufficient. Refer the Fig.1 and
the matrix representation of the vector a above for
better clarity. You can think of a force vector for practical example.
For
describing a rank-2 tensor or dyad, I will use the example of mechanical stress
tensor below:
Please observe that
each of the stress components of the stress tensor matrix has two subscripts,
the first subscript is for the direction of area normal (the surface normal of
the x2–x3 surface is 1 and
so on) and the second subscript is for direction of the stress component.
So, the stress tensor (a dyad or rank-2 tensor) has two directions
namely direction of area normal and the direction of stress component.
Say, you
have a vector and you want to change the direction of it then you have to go
for the vector rotation.
For
rotating the vector, multiply the vector with the rotation matrix and you will
get the rotated vector.
In the
above example the vector a is rotated by angle θ
about X axis and
the vector b is produced.
In the
above example the vector a is rotated by angle θ
about Y axis and
the vector b is produced.
In the
above example the vector a is rotated by angle θ
about Z axis and
the vector b is produced.
Please
note that the rotation matrix is also a 3X3 matrix but it is not necessarily a
tensor. Tensor is a physical object and in a tensor matrix there are certain
relations between the different elements of it.
Tensor is
the generalized form of vectors and scalars. All matrixes cannot be a
tensor unitary; to be a tensor the matrix elements must follow certain
relations among each other. A vector can be rotated by
multiplying it by a rotation matrix.