The majority of experimental studies investigating the stress-strain behavior of square concrete columns confined with carbon fiber-reinforced polymer (CFRP) composites have focused largely on unreinforced columns of small size. Research on the influence of larger cross section, height, internal steel reinforcement, and initial damage on the axial strength and compressive behavior of CFRP-confined square reinforced concrete (RC) columns is, however, limited. To address such knowledge gaps, this paper presents the results of an experimental investigation on the axial stress-strain behavior of 34 larger-sized square-sectioned RC columns confined with CFRP composite wraps. The primary test variables were (1) cross-sectional dimensions, (2) volumetric ratio of internal hoop steel reinforcement, (3) number of layers of CFRP wrap, (4) nature of loading (i.e., monotonic and cyclic), and (5) damage level before CFRP wrapping. The experiments showed the CFRP wrap to considerably enhance the axial strain ca...

For the seismic design of fiber reinforcement polymer (FRP) confined reinforced concrete (RC) columns, the development of an accurate axial stress-strain model that considers cyclic compression is necessary. In light of such a demand, this paper presents a cyclic axial stress-strain model for FRP-confined RC square columns. The model is informed from physical observations and test measurements obtained from an experimental investigation reported in the companion paper, in which FRP-confined square unreinforced and reinforced concrete columns of larger size under varying cyclic axial compression patterns were tested. In the current paper, the proposed stress-strain model is presented and it consists of three main components, namely (1) a monotonic stress-strain model to describe the envelope curve, (2) a polynomial expression for the unloading path, and (3) a straight line for the reloading path. The influence of internal longitudinal and hoop steel reinforcement is also considered in the proposed ...

In this study, the variability inherent in the performance of RC frame structures to bridge over a column loss was investigated, considering the uncertainties existing in gravity loads, material properties, and construction geometries. Uncertainty and sensitivity analysis were conducted in tandem to provide the influence and significance of the uncertain parameters on RC frames to resist progressive collapse. Quasi-static pushdown analysis was used to assess the residual load-resisting capacity of structures with an initialized damage. A set of structural models were generated for uncertainty analysis by using the correlation-reduced Latin hypercube sampling method. Sensitivity analysis was performed by independently varying parameters with one standard deviation away from their means. Two typical RC frame structures with different span aspect ratios were taken as the study cases. The macromodeling technique, which was validated by the test results, was used for analysis. The study results indicated that structural uncertainties have significant effects on the behavior of RC frame buildings for mitigating progressive collapse caused by the loss of a ground column. Among the studied uncertain parameters, the gravity loads and the properties of reinforcement have the most effects on the residual load-resisting capacities of damaged frames.

The concept of Value of Information (VoI) has attracted significant attentions within the civil engineering community over especially the last decade. Triggered by the increasing focus on structural health monitoring, availability of data and emerging techniques of Big Data analysis and Artificial Intelligence, important insights on how to take benefit from VoI in structural integrity management have been gained. This literature review starts out with a summary of the historical developments and contains (1) a summary of two different VoI analysis origins, (2) a compilation of existing VoI analyses research and (3) current engineering interpretations and applications of VoI in the field of civil and infrastructure engineering. VoI analysis has roots in communication theory and Bayesian decision analysis in conjunction with utility theory. Starting point is thus taken in brief introduction of these theoretical foundations, followed by a discussion on the relevant modelling aspects such as information, probability and utility modelling. A detailed review of relevant existing research is presented, divided into the following main areas: computational methods, optimal sensor placement and engineering risk management. Finally, by way of conclusion and outlook, challenges and some promising directions for VoI analysis in the field of civil and infrastructure engineering are identified.