Uniqueness of eigenvectors and reliability

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Discussion Overview

The discussion revolves around the uniqueness of eigenvectors in the context of eigenvalue problems, particularly in engineering applications such as linear elasticity. Participants explore the implications of eigenvector multiplicity on the reliability of solutions derived from them, questioning how boundary conditions and scaling factors affect the validity of these solutions.

Discussion Character

  • Debate/contested
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • Some participants assert that while eigenvalues are unique and provide reliability to solutions, eigenvectors are not unique, leading to questions about the validity of solutions based on them.
  • Others argue that the scaling of eigenvectors (e.g., 10*X, 20*X) raises concerns about the reasonableness of solutions in practical applications, particularly in engineering contexts.
  • One participant suggests that boundary conditions are necessary to determine which eigenvector scaling is appropriate for a given problem, implying that without them, any scalar multiple could be considered valid mathematically but not practically.
  • Another participant mentions that the global stiffness matrix (K) and the corresponding load vector (F) must be adjusted according to the eigenvectors used, raising further questions about coherence in solutions derived from eigenvalue problems.
  • A later reply emphasizes that all scalar multiples of eigenvectors satisfy the eigenvalue criteria, but stresses the importance of boundary conditions in selecting the correct eigenvector scaling for practical applications.
  • One participant introduces the concept of the K matrix being singular and the necessity of boundary conditions to ensure a unique solution, linking this to the dynamics of the eigenvalue problem and the uniqueness of the corresponding eigenvector in relation to natural frequencies and vibration modes.

Areas of Agreement / Disagreement

Participants express differing views on the reliability of solutions based on eigenvectors, with some emphasizing the need for boundary conditions and others questioning the validity of arbitrary scalar multiples. There is no consensus on how to reconcile the multiplicity of eigenvectors with practical engineering applications.

Contextual Notes

Participants note that the discussion involves assumptions about the nature of eigenvalue problems, the role of boundary conditions, and the implications of using scalar multiples of eigenvectors. The relationship between eigenvalues, eigenvectors, and practical solutions remains unresolved.

Ronankeating
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Dear All,

In general eigenvalue problem solutions we obtain the eigenvalues along with eigenvectors. Eigenvalues are unique for each individual problem but eigenvectors are not, since the case is like that how we can rely that solution based on the eigenvector is correct. Because if solution is X(eigenvectors) then 10*X, 20*X, 30*X, etc..will also conform with (K-w2*M)*X=0 eigenvalue problem. And sometimes we use those eigenvectors to find exact solution e.g. K*X = F and how reliable can be those solution even if the eigenvector is normalised?

Regards,
 
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I think the eigenvalues are what makes the solution reliable because eigenvalues are particular while eigenvectors are general.
 
I think the eigenvalues are what makes the solution reliable
No doubt about that,

But as I show in my previous post, sometimes we go directly for the solution originating from eigenvectors e.g. linear elasticity problems. Suppose that you solve an engineering problem K*x = F can you say that K*10*x = F is also solution, it really doesn't look very reasonable?
 
Hrm. In that case, wouldn't you have to set up boundary conditions? I.E. set reasonable limits as to which answers "make sense" and which do not. From a pure mathematics POV, yeah, the answers you choose would be arbitrary answers because there will be other, perfectly good answers that you could've picked but chose not to. But in engineering there are such things as a ludicrous answer.
 
Your constant K would be adjusted accordingly. Or your set of constants, if the problem had multiple constants.
 
Your constant K would be adjusted accordingly. Or your set of constants, if the problem had multiple constants.
Can you elaborate that a bit more? How the K will be adjusted?

That K is global stiffness matrix which depends on element cross sectional mechanical properties and X is global displacement/rotations matrix. After matrix multiplication two of them the result is F global load vector. The glitch here is that, in my case X are eigenvectors obtained from eigenevalue solution and since X and 10*X are both solution it becomes something like 5kN and 50kN are both solution which is not coherent.

Regards,
 
Well any set of eigenvectors (or eigenfuctions if you are in function space) and their scalar multiples all equally satisfy the criteria of being eigenvectors for the particular system. However, your system likely has boundary conditions, which should determine the correct scaling for the eigenvectors so that you get the ones that should fit properly into your Hooke's Law equation.

Full disclosures, it has been a long time since I have done any elasticity problem. I am going off memory here.
 
Dear All,

Thank you in advance does anybody can shed more detailed light on that one.

Regards,
 
for F=kX ,is the linear static formulation of the system.
the K matrix is generally singular, you must add some boundary conditions to eliminate the singularity,thus the function has an unique solutioin.

for eigenvalue problem , it's the scope of dynamics.the eigenvalue is related to the system natural frequency, eigenvector is the vibration mode of the correspoding frequency. component of the eigenvector is the relative vibrating amplitude of each node.
once the initial conditons and the boundary conditions are specified,the vibrating amplitude of each node is unique, i think u can reference books on mechanical vibration.
 

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