Taylor Expansion for Large R: Showing V Approximates $\frac{\pi a^2 \sigma}{R}$

In summary: So when R is very large, the expansion terms approach zero, but the original expression (1+a^2/R^2)^{1/2} still holds. This symmetry is due to the fact that the proper expansion parameter, a/R, is the same for both cases. Not coincidence... I believe it's the same Taylor expansion. If each of us continued our expansion we'd get the same terms.
  • #1
quasar987
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[tex]V = 2\pi \sigma(\sqrt{R^2+a^2}-R)[/tex]

Show that for large R,

[tex]V \approx \frac{\pi a^2 \sigma}{R}[/tex]

I figured if I could develop the MacLaurin serie with respect to an expression in R such that when R is very large, this expression is near zero, then the first 1 or 2 terms should be a fairly good aproximation. But I can't find such an expression.

Thanks for your help.
 
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  • #2
quasar987 said:
[tex]V = 2\pi \sigma(\sqrt{R^2+a^2}-R)[/tex]

Show that for large R,

[tex]V \approx \frac{\pi a^2 \sigma}{R}[/tex]

I figured if I could develop the MacLaurin serie with respect to an expression in R such that when R is very large, this expression is near zero, then the first 1 or 2 terms should be a fairly good aproximation. But I can't find such an expression.

Thanks for your help.

The given expression approaches zero for large R.

I get the given answer, if you find the Taylor series with respect to a. The first derivative term is 0, and the second derivative term is the answer. I think for a rigorous answer, you'll have to show that the condition for convergence is satisfied...
 
  • #3
I did a few similar exercices since my original post and now I clearly see how to do this one:

[tex]V = 2\pi \sigma(\sqrt{R^2+a^2}-R) = 2\pi \sigma R(\sqrt{1+a^2/R^2}-1)[/tex]

The first two terms of the binomial epansion of [itex](1+a^2/R^2)^{1/2}[/itex] give the answer.
 
  • #4
It's funny how your way works too though... it means there's no difference in how V "behaves" when it's R that's very large from when it's a that's very near 0. :eek: Is this pure coincidence? In which kind of function will this sort of symetry happen ?
 
  • #5
quasar987 said:
It's funny how your way works too though... it means there's no difference in how V "behaves" when it's R that's very large from when it's a that's very near 0. :eek: Is this pure coincidence? In which kind of function will this sort of symetry happen ?

Not coincidence... I believe it's the same Taylor expansion. If each of us continued our expansion we'd get the same terms.
 
  • #6
quasar987 said:
It's funny how your way works too though... it means there's no difference in how V "behaves" when it's R that's very large from when it's a that's very near 0. :eek: Is this pure coincidence? In which kind of function will this sort of symetry happen ?
The proper expansion parameter is a/R; hence, it doesn't matter whether a is small or R big. In both cases, a/R is small.
This is readily seen by rewriting V as:

[tex]V=\frac{2\pi\sigma{a}^{2}}{R(1+\sqrt{1+(\frac{a}{R})^{2}})}=2\pi\sigma{a}\frac{\epsilon}{\sqrt{1+\epsilon^{2}}},\epsilon=\frac{a}{R}[/tex]
 
Last edited:
  • #7
arildno said:
The proper expansion parameter is a/R; hence, it doesn't matter whether a is small or R big. In both cases, a/R is small.

...I see !
 

1. What is the Taylor Expansion for large R?

The Taylor Expansion for large R is a mathematical approximation technique used to estimate the value of a function at a large value of a variable. It involves expanding the function in a series of terms, with each term representing a higher power of the variable. The more terms included in the expansion, the more accurate the approximation becomes.

2. What is the significance of showing V approximates $\frac{\pi a^2 \sigma}{R}$?

This equation represents the volume of a sphere with radius R and surface area a, where $\sigma$ is a constant. By using the Taylor Expansion for large R, we can estimate the volume of a sphere with a large radius, which can be useful in various scientific and engineering applications.

3. How does the Taylor Expansion for large R work?

The Taylor Expansion for large R works by using a series of derivatives of the function to estimate its value at a large value of the variable. The more terms included in the expansion, the more accurate the approximation becomes. In this case, we are estimating the volume of a sphere using the surface area and radius as variables.

4. Can the Taylor Expansion for large R be used for any function?

Yes, the Taylor Expansion for large R can be used for any function, as long as it is differentiable and has continuous derivatives at the point of expansion. However, the accuracy of the approximation may vary depending on the complexity of the function and the number of terms included in the expansion.

5. What are the limitations of the Taylor Expansion for large R?

The main limitation of the Taylor Expansion for large R is that it is only accurate for a specific range of values. If the variable R becomes too large, the approximation may become less accurate. Additionally, the accuracy of the approximation also depends on the number of terms included in the expansion, with a larger number of terms resulting in a more accurate approximation.

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