Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2098
Title: Seismic fragility analysis of axially loaded single pile
Authors: Ganesh, R
Pragalath D C, P
Davis, R
Sarkar, P
Singh, S P
Keywords: Fragility
axially loaded pile
openseesPL
Response spectrum
Issue Date: Dec-2013
Citation: International Conference on Structural Engineering and Mechanics December 20-22, 2013, Rourkela, India
Abstract: Performance-based seismic design is the latest trend to earthquake resistant design for Sub structure and Super structures. Many parameters involved in seismic design have uncertainty associated with them. Characterizing the probabilistic nature of these parameters can be done through the use of ‘Fragility Curves’. A fragility analysis assesses the probability that the seismic demand placed on the structure exceeds the capacity conditioned on a chosen IM representative of the seismic loading. Demand (D) and capacity (C) are assumed to follow a lognormal distribution, and the probability of exceeding a specific damage state for a particular component can be estimated with the standard normal cumulative distribution function as per Cornell et. al. [9]. This paper presents the performance of axially loaded single pile subjected to different earthquakes of varying PGAs. FEM software called openseesPL is used for Times history analysis. Floating pile is modelled by beam-column elements, and rigid beam-column elements are used to model the pile diameter. A nonlinearity of soil is introduced using pressure dependent multiplied model and the pile is modelled as elastic. Proper boundary conditions, simulating radiation effects are used. To conduct nonlinear dynamic analysis, forty four natural time history data are selected, and modified to match with Indian response spectrum (IS 1983-2002) using WavGen (Mukharjee and Gupta, 2002). Uncertainty in soil properties is included. A Latin hypercube sampling technique is adopted for generation of random variables which follows a normal distribution with mean and standard deviation. The numerical modelling was done from the generated random values which then subjected to different PGA for performance evaluation.
Description: Copyright belongs to proceeding publisher
URI: http://hdl.handle.net/2080/2098
Appears in Collections:Conference Papers

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