Sensitivity analysis of optimum stochastic nonstationary response spectra under uncertain soil parameters

Local ground characteristics play a fundamental role in seismic design and analysis of structural response. In spite of this, it is usually assumed that these are implicitly deterministic with only few possible values. This work presents a stochastic approach to define response spectra of a single-d...

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Bibliographic Details
Published in:Soil dynamics and earthquake engineering (1984) 2008-12, Vol.28 (12), p.1078-1093
Main Authors: Marano, Giuseppe Carlo, Trentadue, Francesco, Morrone, Emiliano, Amara, Lucia
Format: Article
Language:English
Subjects:
Clough–Penzien model
Covariance analysis
Design sensitivity
Earth sciences
Earth, ocean, space
Earthquakes, seismology
Engineering and environment geology. Geothermics
Engineering geology
Exact sciences and technology
Internal geophysics
Lyapunov equation
Natural hazards: prediction, damages, etc
Optimization
Stochastic dynamics
Uncertainty
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Summary:Local ground characteristics play a fundamental role in seismic design and analysis of structural response. In spite of this, it is usually assumed that these are implicitly deterministic with only few possible values. This work presents a stochastic approach to define response spectra of a single-degree-of-freedom (SDOF) system subjected to a nonstationary seismic action. The ground shaking is here modelled by means of a Clough–Penzien filtered white noise and the mechanical parameters are determined by means of a best fitting procedure. Results are compared with the design Eurocode 8 spectra. Subsequently, a sensitivity analysis with respect to the obtained parameters is performed. It has been developed to evaluate influence of uncertainty in their determination with reference to structural response and to investigate how scattering of parameters could induce variation in response spectra. The stochastic approach is here considered by solving Lyapunov matrix differential equation in the space state. Typical stiff and soft soils are taken into account, supposing filter parameters to be time invariant. The latter are assumed having a probability density distribution with fixed levels of coefficient of variation (COV) between mean and variance. The developed algorithm achieves tests to verify the efficiency of the proposed approach.
ISSN:0267-7261
1879-341X
DOI:10.1016/j.soildyn.2007.12.003