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Fractional Stochastic Dynamics in Structural Stability Analysis

dc.comment.hiddenThis is my newest version of PhD thesis. I wish to delay web access/display for four months from the date of submission.en
dc.contributor.authorDeng, Jian
dc.date.accessioned2013-08-30T20:05:43Z
dc.date.available2014-05-15T05:00:53Z
dc.date.issued2013-08-30T20:05:43Z
dc.date.submitted2013
dc.description.abstractThe objective of this thesis is to develop a novel methodology of fractional stochastic dynamics to study stochastic stability of viscoelastic systems under stochastic loadings. Numerous structures in civil engineering are driven by dynamic forces, such as seismic and wind loads, which can be described satisfactorily only by using probabilistic models, such as white noise processes, real noise processes, or bounded noise processes. Viscoelastic materials exhibit time-dependent stress relaxation and creep; it has been shown that fractional calculus provide a unique and powerful mathematical tool to model such a hereditary property. Investigation of stochastic stability of viscoelastic systems with fractional calculus frequently leads to a parametrized family of fractional stochastic differential equations of motion. Parametric excitation may cause parametric resonance or instability, which is more dangerous than ordinary resonance as it is characterized by exponential growth of the response amplitudes even in the presence of damping. The Lyapunov exponents and moment Lyapunov exponents provide not only the information about stability or instability of stochastic systems, but also how rapidly the response grows or diminishes with time. Lyapunov exponents characterizes sample stability or instability. However, this sample stability cannot assure the moment stability. Hence, to obtain a complete picture of the dynamic stability, it is important to study both the top Lyapunov exponent and the moment Lyapunov exponent. Unfortunately, it is very difficult to obtain the accurate values of theses two exponents. One has to resort to numerical and approximate approaches. The main contributions of this thesis are: (1) A new numerical simulation method is proposed to determine moment Lyapunov exponents of fractional stochastic systems, in which three steps are involved: discretization of fractional derivatives, numerical solution of the fractional equation, and an algorithm for calculating Lyapunov exponents from small data sets. (2) Higher-order stochastic averaging method is developed and applied to investigate stochastic stability of fractional viscoelastic single-degree-of-freedom structures under white noise, real noise, or bounded noise excitation. (3) For two-degree-of-freedom coupled non-gyroscopic and gyroscopic viscoelastic systems under random excitation, the Stratonovich equations of motion are set up, and then decoupled into four-dimensional Ito stochastic differential equations, by making use of the method of stochastic averaging for the non-viscoelastic terms and the method of Larionov for viscoelastic terms. An elegant scheme for formulating the eigenvalue problems is presented by using Khasminskii and Wedig’s mathematical transformations from the decoupled Ito equations. Moment Lyapunov exponents are approximately determined by solving the eigenvalue problems through Fourier series expansion. Stability boundaries, critical excitations, and stability index are obtained. The effects of various parameters on the stochastic stability of the system are discussed. Parametric resonances are studied in detail. Approximate analytical results are confirmed by numerical simulations.en
dc.description.embargoterms1 yearen
dc.identifier.urihttp://hdl.handle.net/10012/7816
dc.language.isoenen
dc.pendingtrueen
dc.publisherUniversity of Waterlooen
dc.subjectstochastic dynamicsen
dc.subjectdynamic stability of structuresen
dc.subjectfractional dynamicsen
dc.subjectrandom vibrationen
dc.subjectLyapunov exponentsen
dc.subjectmoment Lyapunov exponentsen
dc.subjectviscoelastic structuresen
dc.subjectstochastic differential equationsen
dc.subjectfractional differential equationsen
dc.subjectstochastic averagingen
dc.subjectcoupled systemen
dc.subjectgyroscopic systemen
dc.subject.programCivil Engineeringen
dc.titleFractional Stochastic Dynamics in Structural Stability Analysisen
dc.typeDoctoral Thesisen
uws-etd.degreeDoctor of Philosophyen
uws-etd.degree.departmentCivil and Environmental Engineeringen
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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