[Math] Why, intuitively, do different shapes with the same surface area have different volumes

geometryvolume

This is something that's always bothered me. I am well aware that you can easily see why this is the case with math. I mean, even in the 2-D case, take a square with side length $1$, and it has a perimeter of $4$ and an area of $1$. Now take a rectangle with side lengths $0.5$ and $1.5$, then the perimeter is $4$, but now the area is $0.75$.

But where did all the extra area go? We have the same amount of material there. Intuitively I'd like to say that the same area is covered, but it's just distributed differently, but this clearly isn't the case. I know that different shapes with the same surface area have different volumes, but I can't picture why. I can take a sheet of (ideal) paper, turn it to a sphere, and then turn it into a cube, and they'll have different volumes, despite using the same sheet of paper.

To extend on this question a little further, what makes one shape "better" with volume than another?

I hope this isn't a remarkably trivial issue wherein I'm missing something obvious.

Best Answer

Tie the two ends of a thread several inches long together. Fill your kitchen sink with water. Let the waves settle down. Let the loop of thread float on the placid surface, but place it so that the thread meanders erratically --- it's not a circle but a meandering curve returning to its starting point. Then drop a tiny drop of liquid dish detergent into the part of the surface surrounded by the thread. The detergent is a surfactant: it decreases the surface tension. But it does so in the region surrounded by the thread and not outside it. The result: surface tension on the outside pulls the thread outward and it suddenly assumes a circular shape!

Conclusion: the circle surrounds a larger area than does any other closed curve of the same length.

So think about that.

That's the "physicists' solution" of the isoperimetric problem. Dym & McKean's book on Fourier transforms solves the same problem by using Fourier series.