Question on divergence/gradient theorem

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In summary, the conversation discusses the divergence theorem and the gradient theorem, with a specific equation presented. The legitimacy and physical intuition of the equation are questioned, and the conversation concludes with a proof using Gauß's theorem. A summary of the proof is provided, indicating that the equation is valid.
  • #1
member 428835
hey pf!

i had a subtlety about the divergence theroem/gradient theorem. specifically, the following was presented: $$ \iint_s p \vec{dS} = \iiint_v \nabla (p) dv$$

i am familiar with the divergence theorem, but that is for a vector "dotted" with a surface element (flux) related to the divergence (expansion) through the volume. i believe the above is the gradient theorem. can anyone verify the legitimacy of this (and perhaps offer some physical intuition if it holds). i should say [itex]p[/itex] is not a constant.

thanks!
 
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  • #3
joshmccraney said:
hey pf!

i had a subtlety about the divergence theroem/gradient theorem. specifically, the following was presented: $$ \iint_s p \vec{dS} = \iiint_v \nabla (p) dv$$

i am familiar with the divergence theorem, but that is for a vector "dotted" with a surface element (flux) related to the divergence (expansion) through the volume. i believe the above is the gradient theorem. can anyone verify the legitimacy of this (and perhaps offer some physical intuition if it holds). i should say [itex]p[/itex] is not a constant.

thanks!
We may write:
[tex]\vec{dS}=dS(n_{x}\vec{i}+n_{y}\vec{j}+n_{z}\vec{k})
[tex]\int\int_{S}p\vec{dS}=\int\int_{S}pn_{x}dS\vec{i}+\int\int_{S}pn_{y}dS\vec{j}+\int\int_{S}pn_{z}dS\vec{k} (*)[/tex]
Since the Cartesian unit vector can be extracted from the integrand!
--
But, we have:
[tex]pn_{x}dS=(p\vec{i}\cdot\vec{dS})[/tex]
And the first term in RHS in (*) is then simply, by the divergence theorem:
[tex]\int\int_{S}pn_{x}dS\vec{i}=+int\int\int_{V}\frac{\partial{p}}{\partial{x}}\vec{i}dV[/tex]

Do the similar thing to the other two terms on RHS in (*), and you get your identity.
 
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  • #4
thank you arildno! this makes a lot of sense now! youre brilliant!
 
  • #5
on another note, arildno, did you just figure this out by thinking about what's going on or did you see it in a book before? either way, thanks again
 
  • #6
I noticed it a long time ago. I don't remember if it was in a book or on my own inspiration.
 
  • #7
I'd apply Gauß's theorem to the vector field
[tex]\vec{V}(\vec{x})=\vec{a} p(\vec{x})[/tex]
for a constant vector [itex]\vec{a}[/itex]. Then you have
[tex]\vec{\nabla} \cdot \vec{V}=\vec{a} \cdot \vec{\nabla} p.[/tex]
Then Gauß's theorem gives
[tex]\int_V \mathrm{d}^3 \vec{x} \vec{a} \cdot \vec{\nabla} p = \vec{a} \cdot \int_V \mathrm{d}^3 \vec{x} \vec{\nabla} p = \int_{\partial V} \mathrm{d}^2 \vec{F} \cdot \vec{a} p = \vec{a} \int_{\partial V} \mathrm{d}^2 \vec{F} p.[/tex]
Since this is true for all [itex]\vec{a}[/itex] you have proven your vector identity.
 
  • #8
vanhees71 said:
I'd apply Gauß's theorem to the vector field
[tex]\vec{V}(\vec{x})=\vec{a} p(\vec{x})[/tex]
for a constant vector [itex]\vec{a}[/itex]. Then you have
[tex]\vec{\nabla} \cdot \vec{V}=\vec{a} \cdot \vec{\nabla} p.[/tex]
Then Gauß's theorem gives
[tex]\int_V \mathrm{d}^3 \vec{x} \vec{a} \cdot \vec{\nabla} p = \vec{a} \cdot \int_V \mathrm{d}^3 \vec{x} \vec{\nabla} p = \int_{\partial V} \mathrm{d}^2 \vec{F} \cdot \vec{a} p = \vec{a} \int_{\partial V} \mathrm{d}^2 \vec{F} p.[/tex]
Since this is true for all [itex]\vec{a}[/itex] you have proven your vector identity.

Sure. It's matter of taste, really, which one approach is used.
After all, my method is just as general as the one you present.
 

Related to Question on divergence/gradient theorem

1. What is the divergence theorem?

The divergence theorem, also known as Gauss's theorem, is a fundamental theorem in vector calculus that relates the surface integral of a vector field to the volume integral of its divergence over a closed region in space.

2. How is the divergence theorem related to the gradient theorem?

The divergence theorem is a special case of the general gradient theorem, which states that the line integral of a vector field over a curve is equal to the surface integral of the gradient of the vector field over the surface enclosed by the curve.

3. What is the physical interpretation of the divergence theorem?

The divergence theorem has a physical interpretation as it relates the flow of a vector field through a closed surface to the sources and sinks of the field within the enclosed volume. It can be used to calculate flux and net flow of a vector field in a given region.

4. Why is the divergence theorem important in physics and engineering?

The divergence theorem is important in physics and engineering as it allows for the conversion of a difficult surface integral into a more manageable volume integral. It is used in various applications, such as calculating electric and magnetic fields, fluid flow, and heat transfer.

5. Are there any limitations or assumptions of the divergence theorem?

The divergence theorem only applies to continuous vector fields and closed regions in space. It also assumes that the vector field is differentiable and that the region is simply connected. Additionally, the surface and volume integrals must exist for the theorem to hold.

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