Divergence of second-order Tensor

In summary, the problem is asking to calculate the divergence of a second-order tensor \sigma_{ij}=\sigma_{0}x_{i}x_{j}. The attempt at a solution involves using the formula \bigtriangledown \cdot \sigma_{ij}=\sigma_{ij'i} and calculating the partial derivatives, but there may be an error in the approach.
  • #1
paccali
6
0

Homework Statement


Calculate the Divergence of a second-order tensor:

[tex]\sigma _{ij}(x_{i})=\sigma_{0}x_{i}x_{j}[/tex]

Homework Equations



[tex]\bigtriangledown \cdot \sigma_{ij}=\sigma_{ij'i}[/tex]

The Attempt at a Solution



[tex]\sigma_{ij'i}=\frac{\partial }{\partial x_{i}}\cdot\sigma_{0}x_{i}x_{j}[/tex]
[tex]=\sigma_{0}(x_{j})[/tex]

I'm not sure if this is correct. When I put it into a matrix form and calculate the divergence, I seem to get:

[tex]\sigma_{0}\begin{bmatrix}
x_{1}^{2} & x_{1}x_{2} & x_{1}x_{3}\\
x_{1}x_{2} & x_{2}^{2} & x_{2}x_{3}\\
x_{1}x_{3} & x_{2}x_{3} & x_{3}^{2}
\end{bmatrix}[/tex]

[tex]\sigma_{ij'i}=\sigma_{0}\begin{bmatrix}
2x_{1} & x_{2} & x_{3}\\
x_{1} & 2x_{2} & x_{3}\\
x_{1} & x_{2} & 2x_{3}
\end{bmatrix}[/tex]

Which doesn't equal the partial that wasn't put into matrix form. Any help?
 
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  • #2
hi paccali! :wink:

σij'i is a vector, not a tensor …

you haven't summed over i :smile:
 
  • #3
Here is the other part of the problem, and please help me out with this:
[tex]\sigma(r)=\sigma_{0}\mathbf{r}\otimes\mathbf{r}[/tex] where [tex]\mathbr{r}=x_{i}i_{i}[/tex]

So, would this be a correct approach?:

[tex]\bigtriangledown \cdot\sigma_{ij}=\frac{\partial }{\partial x_{k}}\sigma_{0}x_{i}x_{j}i_{i}\otimes i_{j}\cdot i_{k}[/tex]
[tex]=(\sigma_{0}x_{i}x_{j})_{'k}i_{i}\delta _{jk}=\sigma_{0}(x_{i}x_{j})_{'j}i_{i}=\sigma_{0}x_{i}i_{i}[/tex]
 
Last edited:
  • #4
sorry, not my field … you'd better start a new thread on this one
 
  • #5
tiny-tim said:
sorry, not my field … you'd better start a new thread on this one

Yeah, sorry, the problem is in tensor notation, which implies summation symbols, but it's a shorthand.
 

Related to Divergence of second-order Tensor

What is a second-order tensor?

A second-order tensor is a mathematical object that is used to represent linear transformations between vectors in a multi-dimensional space. It consists of a matrix of numbers that can be manipulated using specific rules and operations.

What does divergence of a second-order tensor mean?

The divergence of a second-order tensor is a measure of how much the tensor field is spreading out or converging at a given point. It is a scalar value that represents the rate of change of the flux of the tensor field.

How is divergence of a second-order tensor calculated?

The divergence of a second-order tensor is calculated by taking the dot product of the gradient of the tensor field with the normal vector to the surface at a given point. This can also be represented using the divergence operator (∇⋅).

What is the physical interpretation of divergence of a second-order tensor?

The physical interpretation of divergence of a second-order tensor depends on the application. In fluid mechanics, it represents the rate of expansion or contraction of a fluid flow. In solid mechanics, it represents the change in volume of a material under stress. In electromagnetics, it represents the rate of flow of electric or magnetic fields.

What are the real-world applications of divergence of a second-order tensor?

The concept of divergence of a second-order tensor has various applications in fields such as fluid mechanics, solid mechanics, electromagnetics, and image processing. It is used to study the behavior of fluids, materials under stress, and electromagnetic fields. It is also used in computer vision and image processing techniques to analyze and manipulate images.

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