AbstractThis paper presents a nonlinear analysis procedure for the seismic performance assessment of deteriorated reinforced concrete bridges using a modified damage index. A finite-element analysis program, RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), is used to analyze deteriorated two-span simply supported reinforced concrete bridges. The new nonlinear material models for deteriorated reinforced concrete behaviors were proposed, considering corrosion effects as shown in a reduction in reinforcement section and bond strength. A modified damage index aims to quantify the seismic performance level in deteriorated reinforced concrete bridges. Several parameters of two-span simply supported deteriorated reinforced concrete bridge have been studied to determine the seismic performance levels. The newly developed analytical method for assessing the seismic performance of deteriorated reinforced concrete bridges is verified by comparison with the experimental and analytical parameter results.
The proposed study develops fragility functions for non-seismically designed reinforced concrete structures considering different pounding configurations. The study addresses an existing research gap, since large-scale seismic risk assessment studies involving the seismic performance assessment of building portfolios usually do not involve fragility functions accounting for the possibility of pounding. The selected structures include configurations involving different separation distance values and exhibiting floor-to-floor pounding, floor-to-column pounding, pounding between structures with a significant height difference, and pounding between structures with a significant mass difference. The behaviour of these pounding configurations was analysed using incremental dynamic analysis and compared with that of the corresponding control cases (i.e., individual structures with no interaction with other structures). The results indicate the type of failure mechanism that contributes to the global collapse of the different configurations and the influence of the separation distance. Results highlight the main differences between the expected performance of different pounding configurations with respect to the occurrence of the failure mechanism that governs their collapse. Finally, results indicate that large-scale seismic risk assessment studies should consider fragility functions accounting for different pounding configurations when the possibility of pounding is not negligible, except in cases involving floor-to-floor pounding.
This study covers the application of Static and Dynamic nonlinear analysis to an old moment-frame reinforced concrete building. The case study selected is a template one designed in 1982 without shear walls and built throughout Albanian region in the communism era using old standards (KTP 2-78). For the capacity calculation, Pushover analysis is performed using an inverse triangular load pattern. The demand calculation is conducted using Incremental Dynamic Analysis (IDA) as a method which provides the response behavior of the structure from the elastic range until collapse. For the dynamic analysis is used a set of 18 earthquakes with no marks of directivity. Limit states are defined for both Pushover and IDA based on the FEMA 356 guidelines. The mathematical model is prepared in the environment of Zeus-NL, a software developed especially for earthquake applications. The parameters defined for the IDA analysis are 5% damped first mode spectral acceleration (Sa(T1,5%)) for the intensity measure (IM) and maximum global drift ratio (ϴmax) for the damage measure (DM). In addition, limit states are selected for the pushover curve as Immediate Occupancy (IO), Life Safety (LS) and Collapse Prevention (CP). Similarly, for the IDA curve the limit states are selected as IO, CP and Global Instability (GI) based on FEMA guidelines. Furthermore, IDA curves are summarized into 16%, 50% and 84% fractiles as suggested in the literature. Additionally, a comparison between Pushover and IDA median (50% fractile) is shown from the same graph to illustrate the correlations between performance levels. Finally, structural performance is interpreted based on the outcomes.