Stochastic dynamic analysis of a layered half-space |
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| Affiliation: | 1. BK21 Safe and Sustainable Infrastructure Research, Department of Civil and Environmental Engineering, Seoul National University, Seoul 151-744, Republic of Korea;2. Department of Civil and Environmental Engineering, Seoul National University, Seoul 151-744, Republic of Korea;3. Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712-0273, USA;4. Korea Railroad Research Institute, Uiwang, Gyeonggi-do 437-757, Republic of Korea;1. Advanced Control and Test Laboratory, Department of Mechanical Engineering, University of Bristol, Queen׳s Building, University Walk, Bristol BS8 1TR, UK;2. E-Defence, National Research Institute for Earth Science and Disaster Prevention, 1501-21 Nishikameya, Mitsuda, Shijimi-cho Miki, Hyogo 673-0515, Japan;1. Federal Institute for Materials Research and Testing, 12200 Berlin, Germany;2. University of Duisburg-Essen, 45141 Essen, Germany |
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| Abstract: | A stochastic thin-layer method is developed for the analysis of wave propagation in a layered half-space. A random field of shear moduli in the layered system is considered in terms of multiple correlated random variables. Expanding the random moduli and uncertain responses by means of Hermite polynomial chaos expansions and applying the Galerkin method in the spatial as well as stochastic domains, stochastic versions of thin-layer methods for a layered half-space in plane strain and antiplane shear are obtained. In order to represent the infinite half-space, continued-fraction absorbing boundary conditions are included in the thin-layer models of the half-space. Using these stochastic methods, dynamic responses of a layered half-space subjected to line loads are examined. Means, coefficients of variance, and probability density functions of the half-space responses with a varying correlation coefficient of the shear moduli are computed and verified by comparison with Monte Carlo simulations. It is demonstrated that accurate probabilistic dynamic analysis is possible using the developed stochastic thin-layer methods for a layered half-space. |
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