Impose Uniqueness on Diagonalization of Inertia Tensor?

AI Thread Summary
The discussion revolves around the diagonalization of the inertia tensor of a rigid body, highlighting that while a rotation can diagonalize the tensor, the resulting transformation matrix R is not unique due to potential 180-degree rotations and the rearrangement of entries. To impose uniqueness, one suggestion is to sort the entries of the diagonalized tensor, but this does not resolve the ambiguity of the 180-degree rotation. It is noted that the direction of principal axes is unique when eigenvalues are distinct, yet there remains freedom in the orientation of the axes. The idea of restricting R to an SO(3) matrix (orthogonal with determinant +1) is proposed, but this still allows for switching eigenvectors. Ultimately, the consensus is that while uniqueness may be desirable, having a body-fixed basis where the inertia tensor is diagonal is sufficient for practical purposes.
robg
Messages
1
Reaction score
0
Given an inertia tensor of a rigid body I, one can always find a rotation that diagonalizes I as I = RT I0 R (let's say none of the value of the inertia in I0 equal each other, though). R is not unique, however, as one can always rotate 180 degrees about a principal axis, or rearrange the entries of I0 via rotations. I'm curious if there a set of conditions that one can impose on R to make it unique, however. One can eliminate the ordering issue by insisting that the entries of I0 are in sorted order. What about the 180 degree rotation issue, is there an additional condition that one can impose to eliminate this ambiguity?
 
Physics news on Phys.org
You can always diagonalize a symmetric matrix with a orthogonal transformation. The direction of the principal axes is unique if no two eigenvalues are the same. So the only freedom you have after ordering the eigenvalues in the diagonal for ##R## is the direction of the axes. As an additional constraint you can only impose the condition that the transformation matrix is not only orthogonal but even a rotation, i.e., an SO(3) matrix (with determinant +1). Then still you have the freedom to switch any two of the chosen eigenvectors.

So I don't think that you can make the transformation matrix unique, but why should you want this anyway? It's good enough to have one body-fixed basis where the inertia tensor is diagonal.
 
robg said:
<snip>I'm curious if there a set of conditions that one can impose on R to make it unique, however. <snip>

Interesting question. I wonder if you can impose conditions based on the symmetry (or lack) of the material itself: Cosserat media, materials that internally generate forces and moments ('active' media), or has some other chiral property that does not have inversion symmetry. Not sure, tho.
 
The rope is tied into the person (the load of 200 pounds) and the rope goes up from the person to a fixed pulley and back down to his hands. He hauls the rope to suspend himself in the air. What is the mechanical advantage of the system? The person will indeed only have to lift half of his body weight (roughly 100 pounds) because he now lessened the load by that same amount. This APPEARS to be a 2:1 because he can hold himself with half the force, but my question is: is that mechanical...
Some physics textbook writer told me that Newton's first law applies only on bodies that feel no interactions at all. He said that if a body is on rest or moves in constant velocity, there is no external force acting on it. But I have heard another form of the law that says the net force acting on a body must be zero. This means there is interactions involved after all. So which one is correct?
Thread 'Beam on an inclined plane'
Hello! I have a question regarding a beam on an inclined plane. I was considering a beam resting on two supports attached to an inclined plane. I was almost sure that the lower support must be more loaded. My imagination about this problem is shown in the picture below. Here is how I wrote the condition of equilibrium forces: $$ \begin{cases} F_{g\parallel}=F_{t1}+F_{t2}, \\ F_{g\perp}=F_{r1}+F_{r2} \end{cases}. $$ On the other hand...
Back
Top