Download or read book Stochastic Finite-element Analysis of Reinforced Concrete Structures Subjected to Multiple Environmental Stressors written by Behrouz Shafei Pamsari and published by . This book was released on 2011 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: A stochastic finite-element (FE) framework is developed to investigate the deterioration of reinforced concrete (RC) structures subjected to multiple environmental stressors. This study identifies the key mechanisms and parameters that affect the deterioration of RC components. Among the involved parameters, those related to the concrete properties and diffusion characteristics are categorized as internal parameters, while relative humidity, ambient temperature, concentration of carbon dioxide, and surface chloride content are considered as external parameters. Further investigation of these parameters indicates that most of them have nonlinear time-dependent characteristics with mutual interactions. To model the penetration of corrosive agents into concrete, a series of coupled physical environments is introduced. Through the full-scale, three-dimensional (3D) models of RC components, the major physical environments are simulated based on transient field theory, and the extent of deterioration is determined using a recursive approach. The major mechanisms that cause structural degradation of deteriorating components are also studied. These mechanisms include early-age cracking due to the hydration process and temperature variation, deformations resulted from the mechanical loads, and cracking induced by rust expansion. From the FE analysis results, the state of crack propagation is specified at all time steps and the diffusion characteristics are adjusted accordingly. One of the unique capabilities of the developed FE framework is to integrate various sources of uncertainty in the estimation procedure. For a more accurate durability assessment of deteriorating RC components, both temporal and spatial uncertainties of the influential parameters are taken into account. For this purpose, non-Gaussian stochastic simulation techniques are employed and a set of large-scale stochastic fields is generated for both structural and environmental variables. Since material properties and boundary conditions of the developed FE models can be updated based on corresponding simulated fields, the robustness of predictions is significantly improved after considering various sources of uncertainty. The applicability of the proposed framework for the model updating and health monitoring of deteriorating structures is demonstrated through a number of corrosion scenarios. The suggested updating approach provides engineers and decision-makers with a reliable tool to assess the integrity of deteriorating RC structures, optimize inspection intervals, and choose the most appropriate maintenance actions.