Mean and variability response functions for stochastic systems under dynamic excitation

Papadopoulos, V; Kokkinos, O

dc.contributor.author	Papadopoulos, V	en
dc.contributor.author	Kokkinos, O	en
dc.date.accessioned	2014-03-01T02:53:21Z
dc.date.available	2014-03-01T02:53:21Z
dc.date.issued	2011	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36255
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-80054802858&partnerID=40&md5=9dcc5836cda1d7a65b12bf18c74b5547	en
dc.subject	Dynamic variability response functions	en
dc.subject	Stochastic dynamic systems	en
dc.subject	Stochastic finite element analysis	en
dc.subject	Upper bounds	en
dc.subject.other	Centro earthquake	en
dc.subject.other	Distribution-free	en
dc.subject.other	Dynamic excitations	en
dc.subject.other	Dynamic variability	en
dc.subject.other	Integral form	en
dc.subject.other	Linear dynamics	en
dc.subject.other	Marginal probability	en
dc.subject.other	Monte Carlo Simulation	en
dc.subject.other	Non-Gaussian	en
dc.subject.other	Response functions	en
dc.subject.other	Single degree of freedom systems	en
dc.subject.other	Sinusoidal load	en
dc.subject.other	Standard deviation	en
dc.subject.other	Static systems	en
dc.subject.other	Stochastic dynamic response	en
dc.subject.other	Stochastic dynamic systems	en
dc.subject.other	Stochastic field	en
dc.subject.other	Stochastic field modeling	en
dc.subject.other	Stochastic finite element analysis	en
dc.subject.other	System property	en
dc.subject.other	Transient systems	en
dc.subject.other	Uncertain parameters	en
dc.subject.other	Upper Bound	en
dc.subject.other	Variability response functions	en
dc.subject.other	Civil engineering	en
dc.subject.other	Computational methods	en
dc.subject.other	Computer simulation	en
dc.subject.other	Delay control systems	en
dc.subject.other	Dynamic response	en
dc.subject.other	Dynamical systems	en
dc.subject.other	Earthquakes	en
dc.subject.other	Engineering geology	en
dc.subject.other	Finite element method	en
dc.subject.other	Integral equations	en
dc.subject.other	Monte Carlo methods	en
dc.subject.other	Power spectral density	en
dc.subject.other	Probability distributions	en
dc.subject.other	Scintillation	en
dc.subject.other	Spectral density	en
dc.subject.other	Statistics	en
dc.subject.other	Stochastic systems	en
dc.subject.other	Structural dynamics	en
dc.subject.other	Uncertain systems	en
dc.subject.other	Uncertainty analysis	en
dc.subject.other	Probability density function	en
dc.title	Mean and variability response functions for stochastic systems under dynamic excitation	en
heal.type	conferenceItem	en
heal.publicationDate	2011	en
heal.abstract	The concept of the so called Variability Response Function (VRF), recently proposed for statically determinate and indeterminate stochastic systems [1, 2], is extended in this work to linear dynamic stochastic systems. An integral form for the variance of the dynamic response of stochastic systems is considered, involving a Dynamic VRF (DVRF) and the spectral density function of the stochastic field modeling the uncertain system properties. As in the case of static systems, the independence of the DVRF to the spectral density and the marginal probability density function of the stochastic field modeling the uncertain parameters is validated using brute-force Monte Carlo simulations as well as a series of different moving power spectral density functions for the calculation of the DVRF. The uncertain system property considered is the inverse of the elastic modulus (flexibility). It is demonstrated that DVRF is a function of the standard deviation of the stochastic field modeling flexibility. The same integral expression can be used to calculate the mean response of a dynamic system using the concept of the so called Dynamic Mean Response Function (DMRF), which is a function similar to the DVRF [3]. These integral forms can be used to efficiently compute the mean and variance of the transient system response at any time of the dynamic response together with spectral- distribution-free upper bounds. They also provide an insight into the mechanisms controlling the dynamic mean and variability response. In this work this methodology is effectively utilized to estimate the stochastic dynamic response of a single degree of freedom system subjected to a) sinusoidal load at the end of its length and b) El Centro earthquake. In both cases results are drawn for different values of the stochastic field standard deviation and for various Gaussion and non-Gaussian probability distributions.	en
heal.journalName	ECCOMAS Thematic Conference - COMPDYN 2011: 3rd International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering: An IACM Special Interest Conference, Programme	en