Heavy-Tailed Response of Structural Systems Subjected to Stochastic Excitation Containing Extreme Forcing EventsSource: Journal of Computational and Nonlinear Dynamics:;2018:;volume( 013 ):;issue: 009::page 90914DOI: 10.1115/1.4039309Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: We characterize the complex, heavy-tailed probability density functions (pdfs) describing the response and its local extrema for structural systems subject to random forcing that includes extreme events. Our approach is based on recent probabilistic decomposition-synthesis (PDS) technique (Mohamad, M. A., Cousins, W., and Sapsis, T. P., 2016, “A Probabilistic Decomposition-Synthesis Method for the Quantification of Rare Events Due to Internal Instabilities,” J. Comput. Phys., 322, pp. 288–308), where we decouple rare event regimes from background fluctuations. The result of the analysis has the form of a semi-analytical approximation formula for the pdf of the response (displacement, velocity, and acceleration) and the pdf of the local extrema. For special limiting cases (lightly damped or heavily damped systems), our analysis provides fully analytical approximations. We also demonstrate how the method can be applied to high dimensional structural systems through a two-degrees-of-freedom (TDOF) example system undergoing extreme events due to intermittent forcing. The derived formulas can be evaluated with very small computational cost and are shown to accurately capture the complicated heavy-tailed and asymmetrical features in the probability distribution many standard deviations away from the mean, through comparisons with expensive Monte Carlo simulations.
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| contributor author | Kyul Joo, Han | |
| contributor author | Mohamad, Mustafa A. | |
| contributor author | Sapsis, Themistoklis P. | |
| date accessioned | 2019-02-28T11:11:51Z | |
| date available | 2019-02-28T11:11:51Z | |
| date copyright | 7/26/2018 12:00:00 AM | |
| date issued | 2018 | |
| identifier issn | 1555-1415 | |
| identifier other | cnd_013_09_090914.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4253716 | |
| description abstract | We characterize the complex, heavy-tailed probability density functions (pdfs) describing the response and its local extrema for structural systems subject to random forcing that includes extreme events. Our approach is based on recent probabilistic decomposition-synthesis (PDS) technique (Mohamad, M. A., Cousins, W., and Sapsis, T. P., 2016, “A Probabilistic Decomposition-Synthesis Method for the Quantification of Rare Events Due to Internal Instabilities,” J. Comput. Phys., 322, pp. 288–308), where we decouple rare event regimes from background fluctuations. The result of the analysis has the form of a semi-analytical approximation formula for the pdf of the response (displacement, velocity, and acceleration) and the pdf of the local extrema. For special limiting cases (lightly damped or heavily damped systems), our analysis provides fully analytical approximations. We also demonstrate how the method can be applied to high dimensional structural systems through a two-degrees-of-freedom (TDOF) example system undergoing extreme events due to intermittent forcing. The derived formulas can be evaluated with very small computational cost and are shown to accurately capture the complicated heavy-tailed and asymmetrical features in the probability distribution many standard deviations away from the mean, through comparisons with expensive Monte Carlo simulations. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Heavy-Tailed Response of Structural Systems Subjected to Stochastic Excitation Containing Extreme Forcing Events | |
| type | Journal Paper | |
| journal volume | 13 | |
| journal issue | 9 | |
| journal title | Journal of Computational and Nonlinear Dynamics | |
| identifier doi | 10.1115/1.4039309 | |
| journal fristpage | 90914 | |
| journal lastpage | 090914-12 | |
| tree | Journal of Computational and Nonlinear Dynamics:;2018:;volume( 013 ):;issue: 009 | |
| contenttype | Fulltext |