Journal article
Stochastic dynamic systems with complex-valued eigensolutions
International journal for numerical methods in engineering, Vol.71(8), pp.963-986
2007
DOI: 10.1002/nme.1973
Abstract
A dimensional decomposition method is presented for calculating the probabilistic characteristics of complex-valued eigenvalues and eigenvectors of linear, stochastic, dynamic systems. The method involves a function decomposition allowing lower-dimensional approximations of eigensolutions, Lagrange interpolation of lower-dimensional component functions, and Monte Carlo simulation. Compared with the commonly used perturbation method, neither the assumption of small input variability nor the calculation of the derivatives of eigensolutions is required by the method developed. Results of numerical examples from linear stochastic dynamics indicate that the decomposition method provides excellent estimates of the moments and/or probability densities of eigenvalues and eigenvectors for various cases including large statistical variations of input
Details
- Title: Subtitle
- Stochastic dynamic systems with complex-valued eigensolutions
- Creators
- Sharif RAHMAN - Department of Mechanical & Industrial Engineering, The University of Iowa, Iowa City, IA 52242, United States
- Resource Type
- Journal article
- Publication Details
- International journal for numerical methods in engineering, Vol.71(8), pp.963-986
- Publisher
- Wiley; Chichester
- DOI
- 10.1002/nme.1973
- ISSN
- 0029-5981
- eISSN
- 1097-0207
- Language
- English
- Date published
- 2007
- Academic Unit
- Mechanical Engineering
- Record Identifier
- 9984064586302771
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