Divergence Theorem - Curve Integrals

In summary, the question is asking to verify the divergence theorem when a given vector field is equal to the gradient of a function u, and to find the net flow through a closed path C if a different function u satisfies Laplace's equation in the given square. The first part is solved by showing that each side of the expression matches and the second part involves finding the net flow through the path C, using the fundamental theorem of vector calculus. The question may be confusing for someone not comfortable with vector calculus notation.
  • #1
FrogPad
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This question is throwing me for a loop.

Q: If [itex] u = x^2 [/itex] in the square [itex] S = \{ -1<x,y<1\} [/itex], verify the divergence theorem when [itex] \vec w = \Nabla u [/itex]:

[tex] \int\int_S div\,grad\,u\,dx\,dy = \int_C \hat n \cdot grad\,u\,ds [/tex]

If a different [itex] u [/itex] satisfies Laplace's equation in [itex] S [/itex], what is the net flow through C?

----
So the first thing I should do is show that each side of the expression match:

[tex]\vec w = \Nabla u = (2x,0)[/tex]

(1) [tex] \int\int_S div\,grad\,u\,dx\,dy = \int_{-1}^{1} \int_{-1}^{1} \Nabla \cdot \vec w \, dx \, dy = 2 \int_{-1}^{1} \int_{-1}^{1} \,dx\,dy = 8 [/tex]

(2) [tex]\int_C \hat n \cdot \nabla u \,ds = \sum\limits_{i = 1}^4 \int_C \hat n_i \cdot \vec w(\vec r_i) ds[/tex]

[tex] \vec w = (2x,0) [/tex]
[tex] ds = \sqrt{\left( \frac{dx}{dt} \right)^2+\left( \frac{dy}{dt} \right)^2} dt = \frac{d}{dt}(2(\vec r_{xi}(t)))dt[/tex]

A parametric line is of the form:
[tex] \vec r(t) = \vec r_0 - t\vec r_0 + t\vec r_1 [/tex]

Since we have [itex] \vec w \cdot \hat n_i [/itex] only the x-component of the path is used. And to trace the square we have the parametric paths:

[tex] r_1(t) = (2t-1,---)[/tex]
[tex] r_2(t) = (1,---) [/tex]
[tex] r_3(t) = (-2t+1,---) [/tex]
[tex] r_4(t) = (-1,---) [/tex]

The normal vectors for each path would be:
[tex] \hat n_1 = (0,1) [/tex]
[tex] \hat n_2 = (1,0) [/tex]
[tex] \hat n_3 = (0,1) [/tex]
[tex] \hat n_4 = (-1,0) [/tex]

Evaluating:
[tex] \int_0^1 (1,0)\cdot (2(1),0)2(1)dt + \int_0^1 (-1,0) \cdot (2(-1),0) 2(-1)dt = 4 - 4 [/tex]

Now I'm doing something wrong. But to be honest, I feel so lost on this problem it's not funny.

Some of my concerns are as follows:
* I'm not doing this question correctly AT ALL.
* [itex] \vec w [/itex] is conservative. So the fundamental theorem of vector calculus should hold. So going from the start point to the end point which is the same point will yield 0? Or is this when you are only traveling in a vector field.

* This part of the question:
If a different [itex] u [/itex] satisfies Laplace's equation in [itex] S [/itex], what is the net flow through C?

What is C? Is C the path traced around the square?* Ahhh! :(
If anyone could shed some light on this problem for me, that'd be awesome. Thanks.
 
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  • #2
Wait a second. [itex] ds [/itex] is supposed to be giving me an arc length. How can I get a negative length returned from it. Ok, so I'm guessing the second part of the curve integral is wrong, so it DOES return 8 like it should.

Also... I grabbed my calc book out and looked at the fundamental theorem again. It is not for dealing with [itex] \int_C f(x,y) \, ds [/itex] integrals. It is for vector fields. Since the curve integral (in the form f(x,y)ds is really returning a sum of all the heights f(x,y) above the x-y plane (assuming a positve function). So again 0 even on a closed path doesn't make any sense.

Ok, I think I cleared that part up anyway... I hope so :)
Vector calc confuses the hell out of me sometimes, weird notation I guess (just not very comfortable with it yet).

I just need to tackle the part about laplaces equation now. (I hope). So, any help on that would be awesome.

By the way... I still feel rather confused with this question. Which I'm sure you can tell.
 
  • #3
got it figured out.

no worries anymore.
 

Related to Divergence Theorem - Curve Integrals

1. What is the Divergence Theorem?

The Divergence Theorem is a mathematical theorem that relates the surface integral of a vector field to the volume integral of the divergence of that vector field. It essentially states that the flux of a vector field through a closed surface is equal to the volume integral of the sources of that field within the surface.

2. How is the Divergence Theorem related to curve integrals?

The Divergence Theorem is closely related to curve integrals because it allows us to calculate the flux of a vector field through a closed surface by using a line integral along the boundary of that surface. This is known as the Stokes' Theorem, which is a generalization of the Divergence Theorem.

3. What is the significance of the Divergence Theorem in science and engineering?

The Divergence Theorem is an important tool in the fields of science and engineering because it allows us to relate the behavior of a vector field on a surface to its sources within that surface. This is useful in many applications such as fluid mechanics, electromagnetism, and thermodynamics.

4. What are the assumptions of the Divergence Theorem?

The Divergence Theorem assumes that the vector field is continuously differentiable and that the surface is a closed, smooth, and orientable surface. It also assumes that the surface is bounded by a simple, closed curve and that the vector field is defined on the entire surface.

5. How is the Divergence Theorem used in practical applications?

The Divergence Theorem is used in practical applications to calculate the total flow of a vector field through a closed surface, which can be useful in fluid flow problems and in calculating electric and magnetic flux. It is also used in the derivation of other important theorems, such as Gauss's Law and the Continuity Equation.

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