3D Generalization of Surface Intregral

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In summary, the surface integral of a membrane in 3 dimensions is determined by the triple wedge product of the form (x,y,z) and is equivalent to the surface area of the manifold in 4 dimensions.
  • #1
maverick_starstrider
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Hi,

I'm pondering the relation for the surface integral of a membrane

[tex]\sqrt{1+\nabla \psi \cdot \nabla \psi}[/tex]

My two questions are:

1) Does this expression have an identical form if the "membrane" is a scalar field in 3 dimensions (like Temperature)
2) How does one derive this result for 3 dimensions (I see how it is done in 2D but that requires cross products which don't exist if we add another dimension)

Thanks for the help.
 
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  • #2
I know there is a similar results in spivak for higher dimensional manifolds I just really don't know enough about calculus on manifolds (or wedge products) to get an expression of gradients out of it. For physical reasons [tex]\sqrt{1+\nabla \phi \nabla \phi}[/tex] is just the solution I want I just don't know the derivation for 3 dimensional manifolds (i.e. volumes). Or if that is the correct results for that matter. Can the volume integral of a scalar function in any way be equated to something like

[tex]\sqrt{1+\left(\frac{df}{dx}\right)^2+\left(\frac{df}{dy}\right)^2+\left(\frac{df}{dz}\right)^2}[/tex]
 
  • #3
"Surface area" of a 3 dimensional manifold in 4 dimensional space, anyone?
 
  • #4
If anyone's curious I answered this myself. It does indeed generalize. It is determined by an integral of a triple wedge product of the form (in cartesian coordinates)

[tex]\int_V \left| \frac{\partial \vec{r}}{\partial x} \wedge \frac{\partial \vec{r}}{\partial y} \wedge \frac{\partial \vec{r}}{\partial z} \right| dV[/tex]

where [tex] r = (x,y,z, \phi(x,y,z))[/tex]. This becomes (if you do the product)

[tex]\int_V \left| (-\frac{\partial \phi}{\partial x},-\frac{\partial \phi}{\partial y},-\frac{\partial \phi}{\partial z},1) \right| [/tex]

which is

[tex]\sqrt{1 + \nabla \phi \cdot \nabla \phi}[/tex]

I can then use this to generate a series expansion for the fluctuations in Landau's theory of phase transitions (without saying some hand-wavy nonsense like [tex]\frac{1}{2} \nabla \phi \cdot \nabla \phi [/tex] is the "simplest" gradient term one can think of that obeys symmetries). I just expand this guy (which will be directly proportional to the amount of fluctuations) to get the first and as many higher order terms as I want.
 

FAQ: 3D Generalization of Surface Intregral

What is 3D generalization of surface integral?

3D generalization of surface integral is a mathematical concept that extends the idea of surface integrals from two-dimensional surfaces to three-dimensional spaces. It involves calculating the flux, or flow, of a vector field across a three-dimensional surface.

Why is 3D generalization of surface integral important?

3D generalization of surface integral is important in many areas of science and engineering, including fluid mechanics, electromagnetism, and computer graphics. It allows for the calculation of quantities such as fluid flow, electric and magnetic fields, and lighting in 3D space.

How is 3D generalization of surface integral different from 2D surface integrals?

In 3D generalization of surface integral, the surface is no longer restricted to a flat plane, but can be curved and oriented in any direction. This adds another dimension to the calculations and requires the use of vector calculus to properly account for the orientation of the surface.

What are some applications of 3D generalization of surface integral?

Some common applications of 3D generalization of surface integral include calculating the flow of fluids through pipes or channels, determining the electric or magnetic field strength around a 3D object, and simulating lighting effects in 3D computer graphics.

Are there any limitations to 3D generalization of surface integral?

One limitation of 3D generalization of surface integral is that it can become very complex and difficult to calculate for highly irregular surfaces or vector fields. In these cases, numerical methods may need to be used to approximate the solution. Additionally, the orientation of the surface can greatly affect the results, so care must be taken to correctly account for this in the calculations.

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