Moment of inertia tensor calculation and diagonalization

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Homework Help Overview

The discussion revolves around calculating the moment of inertia tensor for a rigid body represented by three point masses located at specified coordinates. The problem includes finding the tensor and diagonalizing it to obtain eigenvalues and principal axes.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the calculation of the moment of inertia tensor, with one participant expressing uncertainty about their results and questioning the use of a calculator for solving the characteristic polynomial. Others confirm agreement on the matrix obtained and suggest alternative methods for diagonalization.

Discussion Status

The discussion is active, with participants sharing their calculations and results. Some participants are exploring the implications of using coordinates relative to the center of mass, while others are considering different approaches to diagonalization. There is no explicit consensus on the correctness of the initial calculations, but productive suggestions have been made.

Contextual Notes

Participants note the importance of using coordinates relative to the center of mass, which may complicate calculations but could lead to more accurate results. There is also mention of homework constraints regarding the use of calculators for solving equations.

BiGyElLoWhAt
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Homework Statement


Not sure if this is advanced, so move it wherever.
A certain rigid body may be represented by three point masses:
m_1 = 1 at (1,-1,-2)
m_2 = 2 at (-1,1,0)
m_3 = 1 at (1,1,-2)

a) find the moment of inertia tensor
b) diagonalize the matrix obtaining the eigenvalues and the principal axes (as orthogonal vectors)

Homework Equations


##I_{ij} = m_{\beta}(\delta_{ij}r_{\beta}^2 - x_{i\beta}x_{j\beta})##
##\vec{A} = \vec{P^{-1}}\vec{D}\vec{P}##
##I_{ij}=I_{ji}##

The Attempt at a Solution


I'm going to drop the beta's, but each xyz is associated with the mass attached to the term.
##I_{00} = m_1(x_0^2 + x_1^2 +x_2^2 - x_0^2) + m_2(...) + m_3(...)##
## = 1(5) + 2(1) + 1(5) = 12##
##I_{01} = m_1(-x_0x_1) + m_2(...) +m_3(...)##
##= -1(-1) -2(-1) -1(1) = 2##
##I_{02} = m_1(-x_0x_2) + m_2(...) + m_3(...)##
## = -1(-2) -2(0) -1(1) = 4##
##I_{11} = m_1(x_0^2+x_2^2) + m_2(...) + m_3(...)##
##= 1(5) +2(1) +1(5) = 12##
##I_{12} = m_1(-x_1x_2) + m_2(...) +m_3(...)##
##= -1(2) +2(0) - 1(-2) = 0##
##I_{22} = m_1(x_0^2 +x_1^2) + m_2(...) +m_3(...)##
##=1(2) +2(2) +1(2) = 8##
This gives me
##\vec{I} = \left (
\begin{array}{ccc}
12 & 2 & 4 \\
2 & 12 & 0 \\
4 & 0 & 8 \\
\end{array} \right )##

and

##det(I_{\lambda}) = 0 = -\lambda^3 + 32\lambda^2 - 316\lambda + 928##
I don't even know how to solve that equation, and online calculators give
diagonal(5.35139, 11.2841, 15.3627)
Did I mess up? There's nothing about using a calculator, but I don't know how else to solve this. Did I mess up? I am pretty sure I'm not supposed to end up with a bunch of stupid numbers like this.
 
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For what it's worth, I got the same matrix you did.
 
Well, maybe I'll just roll with it then. I thought I checked all my algebra carefully. I'm pretty sure I'm supposed to use P^-1 D P to get the diagonal since he said "obtaining the eigenvectors", but maybe I'll just do row operations or something to avoid the decimals. Thanks.
 
Not sure but it looks as if you are using vectors with respect to the origin. Shoudn't you be using vectors relative to the center of mass of the system
 
instead (for mass 1) of x0 = 1 x1 = -1 and x2 = -2 in line 1 of your calculation: try x0 = 1 - x0cm = 1 - 0 = 1 x1 = -1 = x1 cm = -1 - 1/2 = -3/2 and x2 = -2 - x2 cm = -2 - -1 , etc.

this means a lot more calculation because you need to subtract off the center of masses but I think it will lead to a better answer. On the other hand, I'm glad I am not doing the calculation.
 
I ended up with eigenvalues 11; 11/2 +/- sqrt(57) / 2.
 
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That is a lot neater. I didn't think about doing that. I will keep it in mind for next time.
 

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