Search Results (477)

In this study, the seismic performance of reinforced concrete (RC) L-shaped columns, strengthened with 100 mm and 150 mm wing walls, was determined using quasi-static tests. A total of nine L-shaped column specimens were designed and tested under cyclic loading. This study found that strengthening with wing walls increased the lateral stiffness and horizontal load bearing capacity of L-shaped columns. Notably, such improvement was found to be more significant under higher axial compression ratios, exhibiting maximum increases of 254% and 194% in load bearing capacity, in the positive and negative loading directions, respectively. Additionally, ductility was influenced by the wing wall length and axial compression ratios. Under a low axial compression ratio, the ductility coefficient first increased and then decreased with an increase in the wall length. Conversely, under a high axial compression ratio, ductility was consistently improved with increasing wall length. Furthermore, finite element (FE) models were established, and they successfully validated the experimental results, such as load–displacement responses, hysteresis behavior, skeleton curves and ultimate bearing capacity. The numerical results further strengthened the significant effect of the wing wall addition on the seismic performance of the L-shaped columns. Based on the results, a lateral capacity calculation formula is developed, providing a reliable method for assessing the seismic performance of the strengthened L-shaped columns. Therefore, the findings of this study present theoretical insights and practical guidance for the seismic retrofitting of existing RC structures with special-shaped columns. Full article

The objective of this study was to propose a correlation model of the damage class and deformation of reinforced concrete (RC) beams damaged by earthquakes with a focus on columns and walls. For this purpose, a series of full-scale RC beam specimens with different shear strength margins were tested under cyclic lateral loading to examine their deformation performance and damage states. Then, the damage class and seismic capacity reduction factor of RC beams were evaluated based on the test results. The results showed that the tendency of shear failure, such as shear crack pattern and shear deformation component, of specimens with small shear strength margins was more remarkable, and its maximum residual crack widths tended to be slightly larger and dominated by shear cracks. The results also indicated that the effect of the shear strength margin on the seismic capacity reduction factor which represents the residual seismic performance of RC beams was limited, whereas the specimen with a smaller shear strength margin exhibited lower ultimate deformation capacity. In addition, there was a difference in the boundary value of the lateral drift angle which classifies the damage class of specimens with different shear strength margins. Finally, correlation models between the damage class and deformation of RC beams with different deformation capacities were proposed. Full article

Earthquakes can cause significant damage to structures, resulting in considerable financial and social losses. Enhancing the seismic capacity of existing structures through retrofitting is essential. Traditional seismic retrofitting techniques, such as reinforced concrete (RC) jacketing and steel jacketing, primarily aim to increase structural resistance. But RC jacketing is intrusive and increases mass and stiffness, steel jacketing increases cost and demands careful detailing and both approaches are often inadequate for addressing the dynamic complexities of seismic loading. As an alternative, base isolation systems provide a promising solution by concentrating deformation and energy dissipation within isolation bearings, thereby protecting the superstructure from seismic forces. This study evaluates the effectiveness of base isolation compared with conventional retrofitting methods in enhancing the seismic performance of existing structures. The experimental program included cyclic testing of four RC frame structures: one control specimen and three others retrofitted with RC jacketing, steel jacketing, and lead rubber bearings (LRB). The results indicate that the base-isolated specimen demonstrates superior energy dissipation capacity due to the favorable deformation characteristics of the LRB. Moreover, structural damage is redirected from the original columns to the newly installed transition beams, effectively preserving the integrity of the primary structure. These findings highlight the advantages of base isolation in improving seismic performance and provide valuable experimental evidence supporting its application in the retrofitting of existing structures. Full article

In the Middle East, RC joist slab systems with wide beams are widely used for residential floors. However, when these beams support planted columns, excessive deflection beyond code limits is often observed, despite adequate flexural and shear design. This paper experimentally assesses, for the first time, the efficacy of using carbon-fiber-reinforced polymer (CFRP) sheets alone versus a novel hybrid system comprising CFRP sheets and CFRP/honeycomb plates in controlling deflection in RC wide beams with planted columns. Four RC wide beam specimens at half-scale, each featuring a planted column, were tested to failure. Two control specimens, the first one was designed to reflect standard construction practices. It was sufficiently designed in flexure and shear, but its deflection exceeded code requirements. The second was designed to satisfy the code deflection requirements. The remaining specimens were strengthened using two different techniques: one with externally bonded CFRP sheets and the other with the hybrid system. The findings demonstrated a marked improvement in the flexural performance of the retrofitted wide beams, with peak load increases of 65–71%, stiffness gains of 63–67%, and reduced deflections meeting serviceability requirements (deflection at peak load was reduced by 45–48%). Furthermore, an analysis procedure was developed to estimate the flexural strength and deflection of these beams. Full article

As the main load-bearing components of engineering structures, regular health assessment of reinforced concrete (RC) columns is crucial for improving the service life and overall performance of the structures. This study focuses on the health detection problem of in-service RC columns. By combining deep learning algorithms and acoustic emission (AE) technology, the AE sources of in-service RC columns are located, and the optimal sensor layout form for the health monitoring of in-service RC columns is determined. The results show that the data cleaning method based on the k-means clustering algorithm and the voting selection concept can significantly improve the data quality. By comparing the localization performance of the Back Propagation (BP), Radial Basis Function (RBF) and Support Vector Regression (SVR) models, it is found that compared with the RBF and SVR models, the MAE of the BP model is reduced by 7.513 mm and 6.326 mm, the RMSE is reduced by 9.225 mm and 8.781 mm, and the R² is increased by 0.059 and 0.056, respectively. The BP model has achieved good results in AE source localization of in-service RC columns. By comparing different sensor layout schemes, it is found that the linear arrangement scheme is more effective for the damage location of shallow concrete matrix, while the hybrid linear-volumetric arrangement scheme is better for the damage location of deep concrete matrix. The hybrid linear-volumetric arrangement scheme can simultaneously detect damage signals from both shallow and deep concrete matrix, which has certain application value for the health monitoring of in-service RC columns. Full article

Reinforced concrete (RC) columns play a vital role in structural integrity, and accurately predicting their failure modes is essential for enhancing seismic safety and performance. This study explores the use of a supervised machine learning approach—specifically, an artificial neural network (ANN) model—to classify failure modes of RC columns. The model is trained using data from the well-established Pacific Earthquake Engineering Research Center (PEER) structural performance database, which contains results from over 400 cyclic lateral-load tests on RC columns. These tests encompass a wide range of column types, including those with spiral or circular hoop confinement, rectangular ties, and varying configurations of longitudinal reinforcement with or without lap splices at critical sections. The ANNs were evaluated using a randomly selected subset from the PEER database, achieving classification accuracies of 94% for rectangular columns and 95% for circular columns. Notably, in certain cases, the model’s predictions aligned with or exceeded the accuracy of traditional building code-based methods. These findings underscore the strong potential of machine learning—particularly ANNs—for reliably postdicting failure modes (even the brittle ones) in RC columns, signaling a promising advancement in the field of earthquake engineering. Full article

This paper presents a compact dynamic optical frequency domain reflectometry (D-OFDR) platform enabling millimeter-scale, distributed strain sensing for real-time structural health monitoring (SHM) of reinforced concrete subjected to seismic loading. The proposed D-OFDR interrogator employs a dual-interferometer architecture: a main interferometer for strain sensing and an auxiliary interferometer for nonlinear frequency sweep compensation. Both signals are detected by photodetectors and digitized via a dual-channel FPGA-based DAQ board, enabling high-speed embedded signal processing. A dual-edge triggering scheme exploits both the up-chirp and down-chirp of a 50 Hz bidirectional sweep to achieve a 100 Hz interrogation rate without increasing the sweep speed. Laboratory validation tests on stainless steel cantilever beams showed sub-hertz frequency fidelity (an error of 0.09 Hz) relative to conventional strain gauges. Shake-table tests on a 2 m RC column under incremental seismic excitations (scaled 10–130%, peak acceleration 0.864 g) revealed distinct damage regimes. Distributed strain data and frequency-domain analysis revealed a clear frequency reduction from approximately 3.82 Hz to 1.48 Hz, signifying progressive stiffness degradation and structural yielding prior to visible cracking. These findings demonstrate that the bidirectional sweep-triggered D-OFDR method offers enhanced real-time monitoring capabilities, substantially outperforming traditional point sensors in the early and precise detection of seismic-induced structural damage. Full article

Reinforced concrete (RC) non-seismic frames in Middle Eastern multistory buildings often have beam–column connections with discontinuous bottom reinforcement, heightening the risk of progressive collapse if an outer column fails. This study aimed to reduce the potential for progressive collapse when a column is lost by investigating the use of bolted steel plates to enhance the beam–column joints of such frames. In this regard, high-fidelity finite element (FE) analysis was carried out on ten half-scale, two-span, two-story RC frames to simulate the removal of a center column. The numerical analysis accounted for the nonlinear rate-dependent response of steel and concrete, as well as the bond-slip model at steel bars/concrete interaction. The analysis matrix had three unstrengthened specimens that served as references for comparison, in addition to seven assemblies, which were strengthened using bolted steel plates. In the upgraded assemblies, the studied variables were the grade of steel plate (three grades were examined) and the upgrading scheme (three different schemes were investigated). The performance of the specimens was evaluated by comparing their failure patterns and the characteristics of load versus displacement of the middle column during both flexural and catenary action phases. Based on this comparison, the most efficient strengthening method was suggested. Full article

Many existing reinforced concrete (RC) frames with brick infill walls are vulnerable to earthquake damage, particularly when the walls contain window openings that reduce the lateral resistance. This study aims to examine the seismic performance of RC frames strengthened with U-shaped precast concrete (PC) wall panels. In the proposed method, the window-containing brick infill walls within the RC frames are replaced with factory-fabricated U-shaped PC wall panels, thereby converting the infill into a strong and rigid structural element while preserving the openings. The panels are anchored to the RC frame using post-installed anchors inserted through predrilled holes, allowing for rapid and secure installation with minimal on-site work. To validate the method, five full-scale, one-bay, one-story RC frames were constructed and tested under reversed cyclic lateral loading. Three frames were strengthened with U-shaped PC wall panels of varying thicknesses and large openings. Displacement-controlled cycles following ACI 374.1-05 (R7.0) were applied, with three cycles at each drift ratio stage, and no axial load was applied to the columns. Compared with the reference specimen with a U-shaped brick wall, the strengthened frames exhibited up to 3.29 times higher lateral strength, 4.39 times higher initial stiffness, and 4.33 times greater energy dissipation capacity. These findings demonstrate that the proposed strengthening technique significantly enhances seismic resistance while maintaining the architectural openings, offering a practical and efficient solution for upgrading low-rise RC buildings. Full article

Ultra-High Performance Concrete (UHPC), characterized by its superior mechanical properties and excellent durability, has emerged as a promising material for the repair and reinforcement of tunnels. This study aimed to clarify the reinforcement mechanism of UHPC for tunnel linings and the improvement in bearing capacity through numerical simulation and theoretical derivation. By simulating normal concrete (NC) and reinforced concrete (RC) eccentrically loaded columns under varying reinforcement configurations and working conditions, the study investigated the failure modes and mechanical behaviors of UHPC-reinforced tunnels. Analytical equations for the compression-bending capacity of UHPC-reinforced columns under secondary loading were established and validated. Subsequently, the influence of key parameters was systematically analyzed. The results show that UHPC reinforcement significantly enhances load-bearing capacity, deformation resistance, stiffness, and ductility, albeit with varying failure modes. Notably, the ultimate load-carrying capacity increases by up to 184.6% for NC columns at 180 mm eccentricity and 286.5% for RC columns at 200 mm eccentricity. Reinforcement effectiveness is highly influenced by eccentricity: inner-side reinforcement proves more advantageous under small eccentricities, whereas outer-side reinforcement outperforms under large eccentricities. Comparative analyses of various parameters reveal that initial strain has the greatest impact on reinforcement effectiveness, followed by UHPC thickness, UHPC strength, and the reinforcement ratio of the reinforcement layer, in descending order of influence. The research provides valuable insights into the application of UHPC in tunnel reinforcement, offering a reliable theoretical and numerical basis for engineering design. Full article

The prefabricated reinforced concrete columns–steel girder (RCS) hybrid frame structure using column–column connections is a kind of green and environmentally friendly building structure; its seismic performance is investigated. The seismic susceptibility and key influencing factors are systematically evaluated through the establishment of an analytical model and incremental dynamic analysis (IDA) method. A typical three-span, six-story prefabricated RCS hybrid frame structure is designed and numerically modeled with good agreement with the test data. Sa(T1,5%) and PGA double ground motion intensity parameters are selected for IDA analysis. A comparison between the quantile curve method and the conditional logarithmic standard deviation method reveals that using Sa(T1, 5%) as the intensity measure (IM) provides greater reliability for analyzing the vulnerability of the prefabricated RCS hybrid frame structure. The seismic probability demand model of the structure is fitted with Sa(T1,5%) as a parameter and the seismic fragility curves of the structure are plotted; this shows that the slope of the seismic fragility curves becomes smaller after the structure enters the elastic–plastic state, and exhibits good seismic performance. By studying the effects of concrete strength, longitudinal reinforcement strength, and the axial compression ratio on the seismic fragility, it can be seen that with the increase in concrete strength and longitudinal reinforcement strength, and the decrease in axial compression ratio, the overall ductility of the structure increases, the resistance to lateral deformation of the RCS hybrid frame structure is enhanced, and the seismic performance of the prefabricated structure is improved. Full article

Compared with conventional RC frame buildings, staggered-story frame buildings are prone to the formation of short columns due to the vertical staggering of beam members, which exerts an adverse impact on the seismic performance of the building. Therefore, steel tube-reinforced concrete (ST-RC) columns are usually adopted to address the issue of the insufficient ductility of short columns. For this purpose, to investigate the seismic performance of partial staggered-story RC frame buildings, an elastic–plastic model is established based on a specific practical building, with ST-RC columns installed in the staggered-story area. By varying the confinement coefficients of the ST-RC columns (1.087, 1.152, 1.224, and 1.307) and classifying the member-level performance states, the seismic performance of ST-RC columns in staggered-story buildings under different confinement coefficients is evaluated. The research results indicate the following: in the statistical analysis of the performance states of the positive sections of the ST-RC columns, the degree of damage of the ST-RC columns first decreases and then increases sharply with an increase in the confinement coefficient, and the member damage is minimized when the confinement coefficient is 1.224. In the statistical analysis of the performance states of the inclined sections of the ST-RC columns, the damage state of the ST-RC columns shows a decreasing trend as the confinement coefficient increases; when the confinement coefficients are 1.224 and 1.307, the ST-RC columns are completely in the elastic state. With an increase in the confinement coefficient, the shear force borne by the ST-RC columns first increases and then decreases, while the tensile strain and compressive strain generally show a decreasing trend. When the confinement coefficient is 1.224, the tensile strain and compressive strain of the ST-RC columns are the smallest. Therefore, when arranging ST-RC columns in staggered-story buildings, it is necessary to select an appropriate confinement coefficient according to the actual project conditions to maximize the ductility of the short columns. Full article

The skeleton curve plays a crucial role in evaluating the seismic capacity of damaged structures. The research explored the application of data-driven machine learning approaches to predict the skeleton curves of earthquake-damaged reinforced concrete (RC) columns. Various machine learning methods, including Lasso regression, K-nearest neighbor (KNN), support vector machine (SVM), decision tree, and AdaBoost, were employed to develop a machine learning prediction model (MLPM) for seismic-damaged RC columns. A substantial dataset for the MLPM was derived from finite element (FE) analysis results. The input parameters for the machine learning models included the design specifications of the numerical column model and the damage index (DI), while the coordinates of key points on the skeleton curves served as the output parameters. The findings indicated that the K-nearest neighbor algorithm exhibited the best predictive performance, particularly for the yielding and peak points. The most influential input feature for predicting peak strength was the shear span-to-effective depth ratio, followed by the DI. The ML-based models demonstrated higher efficiency than numerical simulations and theoretical calculations in predicting the skeleton curves of damaged RC columns. Full article

Corrosion is a phenomenon that significantly impacts the durability of reinforced concrete (RC) structures, particularly in highly corrosive environments like coastal regions. The existing numerical modelling often relies on complex approaches that are impractical for structural assessment. For this reason, this study proposes a simplified numerical modelling approach to simulate the cyclic behaviour of existing RC framed structures with corrosion levels (η) below 25%. The proposed modelling employs concentrated plasticity hinges for beams and fiber sections for columns, incorporating corrosion-induced degradation through modified backbone curves and material properties based on the corrosion level of the structural element. The modelling approach was validated against experimental results from the literature; the proposed model adequately captures hysteretic energy, lateral load, and deformation capacities, with maximum errors of 11% for maximum lateral load, 12% for ultimate load, and 33% for dissipated energy in RC frames. For isolated columns, the errors were 11, 12, and 22%, respectively. In addition, a maximum difference of 7% was found in the lateral load capacity of the corroded frames associated with the Life Safety limit state. Finally, it was concluded that the proposed methodology is suitable for representing the cyclic behaviour of corroded RC columns and frames and provides engineers with a tool to evaluate the behaviour of corroded structures without resorting to complex models. Full article

This study presents a high-performance external strengthening strategy for reinforced concrete (RC) beam–column joints, integrating near-surface mounted (NSM) Carbon Fiber Reinforced Polymer (C-FRP) ropes with externally bonded C-FRP sheets. The X-shaped ropes, anchored diagonally on both principal joint faces and complemented by vertical ropes at column corners, provide enhanced core confinement and shear reinforcement. C-FRP sheets applied to the beam’s plastic hinge region further increase flexural strength and delay localized failure. Three full-scale, shear-deficient RC joints were subjected to cyclic lateral loading. The unstrengthened specimen (JB0V) exhibited rapid stiffness deterioration, premature joint shear cracking, and unstable hysteretic behavior. In contrast, the specimen strengthened solely with X-shaped C-FRP ropes (JB0VF2X2c) displayed a markedly slower rate of stiffness degradation, delayed crack development, and improved energy dissipation stability. The fully retrofitted specimen (JB0VF2X2c + C-FRP) demonstrated the most pronounced gains, with peak load capacity increased by 65%, equivalent viscous damping enhanced by 55%, and joint shear deformations reduced by more than 40%. Even at 4% drift, it retained over 90% of its peak strength, while localizing damage away from the joint core—a performance unattainable by the unstrengthened configuration. These results clearly establish that the combined C-FRP rope–sheet system transforms the seismic response of deficient RC joints, offering a lightweight, non-invasive, and rapidly deployable retrofit solution. By simultaneously boosting shear resistance, ductility, and energy dissipation while controlling damage localization, the technique provides a robust pathway to extend service life and significantly enhance post-earthquake functionality in critical structural connections. Full article