Eigenvalue formulation to find the principal stresses, directions

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SUMMARY

The discussion focuses on using eigenvalue formulation to determine the principal stresses and directions from a three-dimensional stress state matrix. The stress matrix provided is: [ 105 0 0; 0 -140 210; 0 210 350]. The eigenvalues calculated are 105, 427.68, and -217.68. The process to find the corresponding eigenvectors involves solving the equation (A - S*I)*X = 0 for each eigenvalue. The discussion emphasizes the importance of row-reduced form in solving these equations to find the principal directions.

PREREQUISITES
  • Understanding of eigenvalue problems in linear algebra
  • Familiarity with stress analysis concepts in mechanics
  • Proficiency in MATLAB for computational solutions
  • Knowledge of Mohr’s circle for visualizing stress states
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  • Learn how to compute eigenvectors from eigenvalues using MATLAB
  • Study the application of Mohr’s circle in three-dimensional stress analysis
  • Explore row-reduced echelon form techniques in linear algebra
  • Investigate advanced stress analysis methods for complex loading conditions
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Mechanical engineers, students in engineering mechanics, and professionals involved in stress analysis and material failure assessment will benefit from this discussion.

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Homework Statement



3.) Stress analysis at a critical point in a machine member gives the three-dimensional state of stress in MPa as the following:

y =

[ 105 0 0
0 -140 210
0 210 350 ]
Using the eigenvalue formulation to find the principal stresses (eigenvalues) and principal directions (eigenvectors). Show these stresses on a properly oriented element. Use the three-dimensional Mohr’s circle to obtain the maximum shear stress and show this on a properly oriented element. Repeat this problem using MATLAB.

Homework Equations



I can do all except finding the directions. I'm not sure how to find that. Do i just plug back my eigenvalues into mhy homogeneous eqn?

The Attempt at a Solution

skipping some steps:

det( 105 - s 0 0
0 -140 - s 210 = [0]
0 210 350 - s )

Solving for S (using characteristic eqn): S = 105, 427.68, -217.68
These are my eigenvalues.

In a previous step, my homogeneous eqn was:

[ 105 - s 0 0
0 -140 - s 210 * [l;m;n] = [0]
0 210 350 - s ]

If i plug my S values back in, i don't know how to solve.
 
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As you mentioned, the equation for, e.g., your third eigenvalue, S3 = -217.684056, is (A - S3*I)*X = 0, where I = identity matrix, A is your given matrix under item 1, and X = eigenvector column vector (x1,x2,x3). Therefore, solve for x1, x2, and x3 in the following. The equation (A - S3*I)*X = 0, for your third eigenvalue, is as follows.

[322.684056 0.0 0.0]
[0.0 77.684056 210.0]*(x1,x2,x3) = (0,0,0)
[0.0 210.0 567.684056]

First, you need to get the above system of equations in row-reduced form. If you are not familiar with row-reduced form, look it up in your linear algebra textbook. In row-reduced form, the above system of equations becomes as follows.

[1.0 0.0 0.0]
[0.0 1.0 2.7032574]*(x1,x2,x3) = (0,0,0)
[0.0 0.0 0.00000]

Therefore, e.g., let x2 = t. Thus, the second equation (row) shown above, 0*x1 + x2 + 2.7032574*x3 = 0, becomes 0 + t + 2.7032574*x3 = 0; and solving for x3 gives x3 = -0.369924*t. The first equation (row) shown above, x1 + 0*x2 + 0*x3 = 0, becomes x1 + 0*t + 0*t = 0; and solving for x1 gives x1 = 0*t. Normalizing the current results, we have (0.0,1.0,-0.369924)*t/sqrt(0.0^2 + 1.0^2 + 0.369924^2), for t not equal to zero. Therefore, the eigenvector corresponding to your third eigenvalue (S3 = -217.684056) is X = (0.0,0.937885,-0.346946).
 
ah that rings a bell. So i also have to do thv same thing for my other two eigenvalues too?
 
Yes.
 

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