Divergence Theorem/Surface Gradient

In summary, the Divergence Theorem, also known as Gauss's Theorem, states that the flux of a vector field through a closed surface is equal to the volume integral of the divergence of the field within the enclosed volume. This theorem is a fundamental tool in vector calculus and has many applications in physics and engineering. The Surface Gradient, on the other hand, is a vector operator that represents the direction and magnitude of the most rapid increase of a scalar function on a surface. It is closely related to the normal vector of the surface and can be used to calculate surface integrals and solve differential equations. Both the Divergence Theorem and Surface Gradient are important concepts in mathematical analysis and have practical uses in various fields.
  • #1
Parmenides
37
0
There is a paper in chemical physics by Overbeek in which he describes the electrostatic energy of a double layer as the "energy of the surface charges and bulk charges in a potential field"; the transformation that he provides appears to be a variant of the divergence theorem in which he introduces scalar fields ##a## and ##b## that vanish at infinity, having values ##a_0## and ##b_0##, respectively, at a surface ##A##. The transformation is presented as:
[tex]
-\int_{A}a_0\nabla_nbdA = \int_{V}(a\nabla^2b + \nabla{a}\cdot\nabla{b})dV
[/tex]
Where he states that "##\nabla_n## is directed from the surfaces into the volume V". I have never encountered the gradient as being taken with respect to a normal ##n## and so this transformation is a bit perplexing. The only thing I have been able to go on is the rare definition of the so-called 'surface gradient' on wikipedia where we have ##\nabla_S{u} = \nabla{u} - \hat{n}(\hat{n}\cdot{\nabla{u}})## for some scalar ##u## on a surface ##S##, but this does not seem to be directly comparable. I can't seem to use the usual definition of the unit normal as ##\hat{n} = \frac{\nabla{a}}{\|a\|}## because ##a## (or ##b##) is not equal to 0.

I seem to have forgotten some concepts in multivariate calculus. Could someone provide some clarity? The paper can be found at http://www.sciencedirect.com/science/article/pii/016666229080132N
 
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  • #2
Solved. Sort of.

This is actually Green's first identity, with ##\nabla_n{a}## being the normal derivative of the scalar function ##a##. As this is in the mathematics section and not physics, I won't bother with the extension to electric fields and potential.
 

Related to Divergence Theorem/Surface Gradient

What is the Divergence Theorem?

The Divergence Theorem is a mathematical theorem that relates the flux, or flow, of a vector field through a closed surface to the divergence of the vector field within the enclosed volume.

What is the significance of the Divergence Theorem?

The Divergence Theorem is significant because it allows for the simplification of complicated surface integrals into much simpler volume integrals. This makes it a useful tool in many areas of physics and engineering.

How is the Divergence Theorem related to the Surface Gradient?

The Divergence Theorem and the Surface Gradient are closely related, as they both involve the concept of flux. The Surface Gradient is a vector field that describes the rate of change of a scalar field along a surface, while the Divergence Theorem relates the flux of a vector field to the divergence of that field.

What are some real-world applications of the Divergence Theorem and Surface Gradient?

The Divergence Theorem and Surface Gradient have many real-world applications, including fluid dynamics, electromagnetism, and heat transfer. They are also used in computer graphics and image processing to analyze and manipulate vector fields.

How can the Divergence Theorem and Surface Gradient be visualized?

The Divergence Theorem and Surface Gradient can be visualized using vector plots, contour maps, and animations. These visualizations help to better understand the concepts and applications of these mathematical tools.

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