Search Results (6)

Ultra-high-performance concrete (UHPC) jackets present a promising solution for enhancing the seismic resilience of seismically deficient reinforced concrete (RC) bridge columns. This study investigates jacket thickness optimization through integrated experimental and numerical analyses. Quasi-static cyclic tests on a control column and a specimen retrofitted with a 30-mm UHPC jacket over the plastic hinge region demonstrated significant performance improvements: delayed damage initiation, controlled cracking, a 24.6% increase in lateral load capacity, 139.5% higher energy dissipation at 3% drift, and mitigated post-peak strength degradation. A validated OpenSees numerical model accurately replicated this behavior and enabled parametric studies of 15-mm, 30-mm, and 45-mm jackets. Results identified the 30-mm thickness as optimal, balancing substantial gains in lateral strength (~12% higher than other thicknesses), ductility, and energy dissipation while avoiding premature failure modes—insufficient confinement in the 15-mm jacket and strain incompatibility-induced brittle failure in the 45-mm jacket. These findings provide quantitative design guidance, establishing 30 mm as the recommended thickness for efficient seismic retrofitting of existing RC bridge columns. Full article

Recent catastrophic bridge fire incidents have highlighted the critical need for effective post-fire assessment of bridges, thereby challenging the dominant practice of complete replacement following these destructive events. This study investigates the post-fire performance of bare, isolated, and Carbon Fiber Reinforced Polymer (CFRP)-repaired Reinforced Concrete (RC) bridge columns under single-unit truck impact followed by air blast. This extreme loading scenario was deliberately selected given the increased vulnerability of bridge columns to this loading scenario in the recent few years. Three-dimensional Finite Element (FE) models of the structural system and surrounding environment were developed and validated in LS-DYNA. The effectiveness of two in-situ retrofitting schemes in mitigating damage and enhancing structural integrity of three column diameters under the selected multi-hazards was assessed. Results demonstrated that wrapping the bottom half of the column height prevents shear failure and significantly reduces the damage under the coupled impact and blast. In contrast, employing a combination of CFRP bars and externally bonded sheets showed limited enhancement on post-fire impact and blast performance. This study provides critical insights into the feasibility and efficacy of retrofitting bridge columns that have experienced fire, thus laying the groundwork for the reconsideration of current design and rehabilitation protocols. Full article

Sustainable solutions in the building construction industry have emerged as a new method for retrofitting applications in the last two decades. Fiber-reinforced polymers (FRPs) have garnered much attention among researchers for improving reinforced concrete (RC) structures. The existing design guidelines for FRP-strengthened RC members were developed using empirical methods that are based on specific databases, limiting the accuracy of the predicted results. Therefore, the use of innovative and efficient prediction tools to predict the behavior of FRP-strengthened RC members has become essential. During the last few years, efforts have been progressively focused on the use of machine learning (ML) as a feasible and effective technique for solving various structural engineering problems. Its capability to predict the behavior of complex nonlinear structural systems while considering a wide range of parameters offers a distinctive opportunity to make the behavior of RC members more predictable and accurate. This paper aims to evaluate the current state of using various ML algorithms in RC members strengthened with FRP to enable researchers to determine the capabilities of current solutions as well as to find research gaps to carry out more research to bridge revealed knowledge and practice gaps. Scopus databases were searched using predefined standards. The search revealed ninety-six articles published between 2016 and 2023. Consequently, these articles were analyzed for ML applications in the field of FRP retrofitting, including flexural and shear strengthening of RC beams, flexural strengthening of slabs, confinement and compressive strength of columns, and FRP bond strength. The results reveal that 32% of the reviewed studies focused on the application of ML techniques to the flexural and shear strengthening of RC beams, 32% on the confinement and compressive strength of columns, 6.5% on the flexural strengthening of slabs, 22% on FRP bond strength, 6.5% on materials, and 1% on beam–column joints. This research also revealed that the application of various ML algorithms has shown a significant improvement in resistance prediction accuracy as compared with the existing empirical solutions. Supervised learning techniques were the most favorable learning method due to their good generalization, interpretability, adaptability, and predictive efficiency. In addition, the selection of suitable ML algorithms and optimization techniques is found to be mainly dictated by the nature of the problem and the characteristics of the dataset. Nonetheless, selecting the most appropriate ML model and optimization algorithm for each specific application remains a challenge, given that each algorithm is developed with different principles and methodologies. Full article

Non-prismatic reinforced concrete (RC) beams are widely used for various practical purposes, including enhancing architectural aesthetics and increasing the overall thickness in the support area above the column, which gives high assurance to services that this will not result in the distortion of construction features and can reduce heights. The hollow sections (recess) can also be used for the maintenance of large structural sections and the safe passage of utility lines of water, gas, telecommunications, electricity, etc. They are generally used in large and complex civil engineering works like bridges. This study conducted a numerical study using the commercial finite element software ANSYS version 15 for analysing RC beams, hollow longitudinally sectioned and retrofitted with carbon fibre reinforced polymers (CFRPs), which were subjected to concentrated vertical loads. The numerical analysis results on the simulated beam models were in excellent agreements with the previous experimental test results. This convergence was confirmed by a statistical analysis, which considered the correlation coefficients, individual arithmetic means and standard deviations for all the calculated deflections of the simulated beam models. A proposed numerical simulation model with the hypotheses can be considered suitable for modelling the behaviours of simple supported non-prismatic RC beams under vertical concentrated loads. The numerical results showed that altering the cross-section from solid to hollow could reduce the load carrying capacities of the beams by up to 53% and increase the corresponding deflections by up to 40%, respectively. Using steel pipes for making recesses could enhance the loading capacity by up to 56%, increase the ductility, and reduce the corresponding deflections by up to 30%, respectively. Finally, it was found that bonding the CFRP sheets in the lower middle tensile areas of the hollow beams could improve the resistance and reduce the deformations by up to 27%. The failure patterns for all the numerical models were shear failure. The cylinder compressive strength could be used as a mechanical parameter for modelling and assessing the structural behaviours of the beam models, as its increase could improve the load carrying capacities and reduce the deflections by 30–50%. Full article

From past earthquakes, it has been found that the large residual displacement of bridges after seismic events could be one of the major causes of instability and serviceability disruption of the bridge. The shape memory alloy bars have the ability to reduce permanent deformations of concrete structures. This paper represents a new approach for retrofitting and seismic rehabilitation of previously designed bridge columns. In this concept, the RC bridge column was divided into three zones. The first zone in the critical region of the column where the plastic hinge is possible to occur was retrofitted with near-surface mounted shape memory alloy technique and wrapped with FRP sheets. The second zone, being above the plastic hinge, was confined with Fiber-Reinforced Polymer (FRP) jacket only, and the rest of the column left without any retrofitting. For this purpose, five types of shape memory alloy bars were used. One rectangular and one circular RC bridge column was selected and retrofitted with this proposed technique. The retrofitted columns were numerically investigated under nonlinear static and lateral cyclic loading using 2D fiber element modeling in OpenSees software. The results were normalized and compared with the as-built column. The results indicated that the relative self-centering capacity of RC bridge piers retrofitted with this new approach was highly greater than that of the as-built column. In addition, enhancements in strength and ductility were observed. Full article

A structural progressive collapse is usually a local failure, in which the damage is concentrated at beams that bridge the removal column and the column itself. In many cases, retrofitting the damaged structure is more economical and more sustainable than reconstructing the entire structure. A progressive collapse test of a 1/3 scale, four-bay by two-story reinforced concrete (RC) frame was conducted, after which the structure was retrofitted with carbon fiber reinforced polymer (CFRP) wraps and retested. The center column in the first story was removed and the frame was pushed down quasistatically under displacement control to investigate the progressive collapse performances of the retrofitted RC frame. The test results were represented systematically at different areas in terms of the resistance forces, crack developments, and local and global failure modes. Numerical models were built to verify the test frame before and after the retrofitting. A design method was proposed to retrofit an RC frame using CFRP wraps after a progressive collapse. The test frame was redesigned to improve the retrofitting and used as an example to demonstrate the rationality of the proposed retrofit design method. The results indicated that the proposed retrofitting technology rapidly restored the frame structure to its original capacity before the progressive collapse occurred, whilst consistently satisfying the priorities of being economical and sustainable. Full article