Proceedings of the
The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK
Probabilistic Analysis of RC Doubly Curved Shells under Strong Ground Motions
1Department of Structural Engineering, College of Civil Engineering, Tongji University, 1239 Siping Rd., Shanghai, PR China.
2Department of Civil Engineering, College of Engineering, Minia University, Egypt /EADDRESS/
ABSTRACT
Recently there has been a growing trend for using RC thin shell structures such as doubly curved shells (DCS) to cover large column-free spaces. However, according to the investigation of the effects of the recent earthquakes, considerable damage was observed in these structures, which negatively affected their functionality in serving as shelters during earthquakes due to the apparent lack of a general understanding of their structural response. Thus, in this study, deterministic in tandem with probabilistic analyses considering different uncertainty sources have been performed to investigate the structural response and the reliability of these structures under strong earthquakes. Due to the lack of the design of these structures in the design codes, an innovative automatic finite element-based design algorithm named the developed advanced sandwich model (DASM) is developed and employed to obtain the steel reinforcement in preparation for the analysis. The multi-axial plasticity damage constitutive model is employed through the VUMAT subroutine to reproduce the concrete nonlinear behavior. Then, a complete framework is developed to investigate the stochastic response (SR) and quantify the reliability of these structures based on the developed design procedure, concrete plasticity damage model, and the probability density evolution method (PDEM), where both the SR and the instantaneous probability density function could be attained, and a reliability of 70.78% is obtained for the DCS under Northridge event.
Keywords: Doubly curved shells, Seismic excitation, DASM, Material nonlinearity, Nonlinear dynamic analysis, Reliability analysis.