Having solved the obstacle problem for a string, let us turn to a more difficult one, in which an elastic string is replaced with an elastic rod (or plate, if we are looking at a cross-section). Elastic rods resist bending much in the same way that strings don’t. This can be modeled by minimizing the bending energy
subject to the boundary conditions , , and the same obstacle as before: . The boundary conditions for mean that the rod is clamped on both ends.
As before, the obstacle permits one-sided variations with smooth and compactly supported. The linear term of is , which after double integration by parts becomes . Since the minimizer satisfies , the conclusion is whenever . Therefore, everywhere, at least in the sense of distributions. In the parts where the rod does not touch the obstacle, we can do variation of either sign and obtain ; that is, is a cubic polynomial there.
So far everything looks similar to the previous post. But the fourth derivative of the obstacle function is , which is positive. Since the minimizer must satisfy , it cannot assume the shape of the obstacle. The contact can happen only at isolated points.
Therefore, is a cubic spline with knots at the contact points and at . The distributional derivative consists of negative point masses placed at the contact points. Integrating twice, we find that is a piecewise affine concave function; in particular it is continuous. The minimizer will be -smooth in .
How many contact points are there? If only one, then by symmetry it must be at , and the only three-knot cubic spline that satisfies the boundary conditions and passes through with zero derivative is . But it does not stay below the obstacle:
With a smaller circle, or a longer bar, the one-contact (three-knot) spline would work. For example, on :
But with our parameters we look for two contact points. By symmetry, the middle piece of the spline must be of the form . The other two will be and , also by symmetry and to satisfy the boundary conditions at . At the positive knot the following must hold:
where the last condition comes from the fact that is concave and therefore continuous. With five equations and five unknowns, Maple finds solutions in closed form. One of them has , as above, and is not what we want. The other has and coefficients such as . Ugly, but it works:
This time, the bar does stay below the obstacle, touching it only at two points. The amount by which it comes off the obstacle in the middle is very small. Here is the difference :
And this is the second derivative .
Again, the minimizer has a higher degree of regularity (Lipschitz continuous second derivative) than a generic element of the function space in which minimization takes place (square-integrable second derivative).
If the rod is made shorter (and the obstacle stays the same), the two-contact nature of the solution becomes more pronounced.
Assuming the rod stays in one piece, of course.