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Bayesian identification of soil-foundation stiffness of building structures

Shirzad Ghaleroudkhani, N ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1002/stc.2090
  3. Publisher: John Wiley and Sons Ltd , 2018
  4. Abstract:
  5. A probabilistic method is presented for identifying the dynamic soil-foundation stiffnesses of building structures. It is based on model updating of a Timoshenko beam resting on sway and rocking springs, which respectively represent the superstructure and the soil-foundation system. Unlike those previously employed for this particular problem, the proposed method is a Bayesian one, which accounts for the prevailing uncertainties due to modeling and measurement errors. As such, it yields the probability distribution of the system parameters as opposed to average/deterministic values. In this approach, the joint probability density function of the parameters that control the flexible-base Timoshenko beam model, together with the fundamental natural frequency and mode shape of the system, forms the prior distribution. Using Bayes' theorem, a posterior distribution is obtained by updating the prior distribution with a sparsely measured mode shape and frequency. The most probable realizations of the system parameters are then determined by maximizing the posterior distribution. For this purpose, first- and second-order derivatives of the objective function are analytically computed via direct differentiation. The proposed method is verified using a synthetic example. Additionally, sensitivity analyses are carried out on both the system parameters and standard deviations of the sources of error. Subsequently, the proposed method is applied to real-life data recorded at the Millikan Library building, which is located at the California Institute of Technology campus in Pasadena, California, and the results are compared with a previous deterministic study. Copyright © 2017 John Wiley & Sons, Ltd
  6. Keywords:
  7. Soil-structure interaction ; System identification ; Timoshenko beam ; Identification (control systems) ; Particle beams ; Probability distributions ; Sensitivity analysis ; Soil structure interactions ; Soils ; Stiffness ; Uncertainty analysis ; Bayesian identification ; Bayesian updating ; California Institute of Technology ; Dynamic stiffness ; Joint probability density function ; Modeling and measurement ; Second order derivatives ; Timoshenko beams ; Probability density function
  8. Source: Structural Control and Health Monitoring ; Volume 25, Issue 3 , 2018 ; 15452255 (ISSN)
  9. URL: https://onlinelibrary.wiley.com/doi/full/10.1002/stc.2090