Search Results (66)

This study numerically examined the anchorage mechanism of rebar hooks under varying straight development lengths, including high stress levels. A three-dimensional rigid body spring model (3D RBSM) was used for the investigation and successfully reproduced the experimental pullout test stress–slip relationships and inner–outer strain distributions for the rebar hook with and without a straight development length. A validated numerical model was used to assess local concrete stresses and internal crack propagation, enabling a clear interpretation of how straight development length influences the anchorage mechanism. The results revealed that increasing straight development length increases stiffness, reduces rebar strains and concrete stresses in the hook region, promotes crack formation around the rebar surface, and forms maximum tensile stresses closer to the top surface, ultimately resulting in earlier splitting failure at high rebar stress levels. A comparison of cases with and without hooks shows that combining the hook with straight development length improves stress distribution, delays crack propagation, and increases anchorage by reducing tensile stress concentrations near the top surface and side faces. These findings provide valuable insights into the role of straight development length in the anchorage performance of 180-degree rebar hooks. Full article

Wind-induced roof-lifting accidents occur frequently in metal roofs, making the monitoring of wind uplift resistance an important part of building health monitoring. This paper proposes an integrated monitoring and reinforcement method for metal roofs using embedded fiber Bragg grating (FBG) smart rebars, develops smart rebars with both sensing and load-bearing functions, and conducts wind uplift tests in accordance with relevant standards. The experimental results show that: 1. The smart rebar can achieve high-frequency real-time monitoring at 100 Hz, accurately capture the dynamic force characteristics of the roof panel throughout the wind load application process, and precisely locate the damaged area. 2. The smart rebar and the roof panel form an integrally stressed “rebar–panel” system. Under wind load, they deform coordinately; the smart rebar uniformly transfers the load from local high-stress areas to the entire roof system, optimizing the force transmission path and avoiding premature damage caused by local stress exceeding the limit. During the experiment, it effectively restricts the deformation of the decorative panel and prevents secondary damage caused by “splashing”. 3. Based on the experimentally measured strain data and the degree of roof damage, a graded-control index system is established with a “first-level alarm threshold of 1800 με, second-level alarm threshold of 2400 με, and third-level alarm threshold of 3000 με”. Each level of alarm corresponds to relevant disposal measures, realizing closed-loop management from data monitoring to risk response. The smart rebar system serves both load-bearing and sensing functions, fulfilling the practical engineering needs of monitoring and enhancing the roof, thereby achieving the dual purposes of monitoring and reinforcement. Full article

This study investigated how increased Cr and Ni contents affect the corrosion behavior and rust layer evolution of HRB500 rebar in chloride-containing environments. Corrosion of the Cr- and Ni-alloyed rebars was characterized by distinct stages: in the initial stage, before a stable rust layer formed, the corrosion rate increased; with continued immersion, corrosion products progressively covered the surface and became more compact, and the overall corrosion rate decreased. Higher Cr and Ni contents were found to mitigate overall corrosion damage, markedly suppress localized corrosion, and shift the corrosion morphology toward a more uniform attack. Electrochemical measurements showed a noble shift in corrosion potential, a reduction in corrosion current density, and significant increases in low-frequency impedance and charge transfer resistance, indicating enhanced barrier properties against charge transfer and ionic migration. With corrosion progression, rust layer phases evolved from an Fe₃O₄-dominated assemblage to enrichment in stable iron oxyhydroxides; the fraction of α-FeOOH increased, raising the α/γ* index and suggesting improved rust layer stability and protectiveness. Mechanistically, Cr and Ni enrichment was found to facilitate the conversion of metastable products to α-FeOOH and to promote the formation of compact spinel oxides FeCr₂O₄ and NiFe₂O₄, thereby hindering chloride ion ingress and interfacial corrosion reactions and markedly improving corrosion resistance. Overall, this work elucidated the Cr–Ni co-alloying mechanism for rust layer stabilization and pitting suppression. At 504 h, the high Cr–Ni rebar reduced the maximum pit depth by approximately 61.8% and lowered i_corr to approximately 43% of that of the low Cr–Ni rebar, thereby providing quantitative guidance for marine-grade rebar design. Full article

Rebar binding is a labor-intensive and low-efficiency process in the production of reinforced concrete prefabricated components, in which consistent binding quality is difficult to guarantee. To address the engineering challenges faced by rebar binding robots in complex construction environments—particularly in terms of binding-point recognition accuracy, real-time performance, and manipulator path planning efficiency—this paper presents an integrated method for binding-point recognition, localization, and binding path planning tailored to rebar binding tasks. First, based on the YOLOv8n-pose architecture, a lightweight rebar binding-point recognition and localization model, termed YOLOv8n-pose-Binding, is developed by introducing multi-scale Ghost convolution structures and an adaptive threshold focal loss. The proposed model improves keypoint detection accuracy and real-time performance while effectively reducing computational complexity, making it suitable for deployment on resource-constrained mobile robotic platforms. Second, a dedicated target coordinate system for rebar binding points is constructed to enable accurate pose estimation in the manipulator base frame. Furthermore, considering the non-uniform obstacle distribution in rebar mesh environments and the high-dimensional motion characteristics of robotic manipulators, systematic improvements are introduced to the RRT-Connect framework from the perspectives of sampling strategies, tree expansion, node reconnection, and path pruning, resulting in an improved RRT-Connect path planning algorithm. Simulation and experimental results demonstrate that, while maintaining favorable real-time performance, the proposed method achieves stable improvements in recognition accuracy and inference efficiency compared with the baseline YOLOv8n-pose model. In addition, the improved RRT-Connect algorithm exhibits superior engineering performance in terms of path planning efficiency and path quality, providing a deployable technical solution for automated rebar binding operations. Full article

Designing buildings and structures that meet advanced mechanical safety standards is a relevant task in the present-day socio-economic environment, given that structural safety is evaluated by resistance to progressive collapse. The design of key elements, capable of withstanding accidental actions, means preventing the escalation of progressive collapse. This task also involves evaluating the bearing capacity of reinforced concrete beams under high-velocity impacts triggering supplementary dynamic loading by bending and torsion moments. The authors present their method for the dynamic load analysis based on the development of limiting surfaces. For this purpose, the value of the J-integral is computed to analyze the fracture of a rebar, and the inability of a rebar to take loads is simulated by a normalized time function. The resulting conclusion is that the proposed design method, applied to key elements of buildings and structures, improves their mechanical safety in the case of dynamic loading that causes local damage and triggers resistance to combined stress, including bending in two planes and torsion. It has been established that at a bending load level constituting 80% of its ultimate value or higher, a combined impact bending-torsional load, as low as 25% of its own ultimate capacity, can cause the rupture of tensile reinforcement and lead to a loss of mechanical safety in conventionally designed beams. Full article

To reduce the weight of prefabricated cap beams, a new type of hybrid pier with a steel cap beam and single concrete column with an innovative flange–rebar–ultra-high-performance concrete (UHPC) connection structure is proposed in this paper. Focusing on the static performance of hybrid piers, a specimen with a geometric similarity ratio of 1:4 was fabricated for testing. The results showed that the ultimate load-bearing capacity reached 960 kN, and the failure mode was characterized by an obvious overall vertical displacement of 70.2 mm at the cantilever end, accompanied by local buckling in the webs between transversal diaphragms and ribs. Due to the varying-thickness design, longitudinal strains were comparable between the middle section (thin plates) and the root section (thick plates) of the cantilever beam, showing a trend of an initial increase followed by a decrease from the end of the cantilever beam to the road centerline. Meanwhile, the cross-sections of the connection joint and concrete column transformed from overall compression to eccentric compression during the test. At the ultimate state, their steel structures remained elastic, with no obvious damage in the concrete or UHPC, verifying good load-bearing capacity. Furthermore, the finite element analysis showed the new connection joint and construction method of hinged-to-rigid could reduce the column top concrete compressive stress by 18–54%, tensile stress by 11–68%, and steel cap beam Mises stress by 10%. Finally, based on the experimental and numerical studies, the safety reserve coefficient of the new hybrid pier was over 2.7. Full article

Pullout bond tests using specimens with an expansion-agent-filled pipe (EAFP) simulating the cracking due to rebar corrosion were conducted to evaluate the deterioration of bond behavior when the crack width is not uniformly distributed along the longitudinal direction. The primary specimens for the pullout test are designed with a bond length equal to 20 times the bar diameter. To investigate the distribution of bond stress along the rebar in detail, a bond analysis was performed using the local bond stress–slip model as a function of the induced crack width that is developed based on the pullout test of the specimens with a bond length of four times the rebar diameter. The EAFP simulation showed a tendency for larger crack widths at the free end, likely due to filling the expansion agent from the load-end side. From the results of the pullout bond test, as the induced crack width increases, the maximum bond stress decreases. The results of the bond analysis, assuming the five patterns of crack width distributions along the longitudinal direction, showed that the bond stress–slip curve is little affected by the difference in the crack width distribution. Within a bonded length up to 20 times the rebar diameter, the differences in crack width variations had little effect on the distribution of the local bond stress. It is possible to evaluate the bond behavior based on the average crack width. Full article

Thousands of coastal reinforced concrete structures using HRB400 bars have served for over three decades in China. Their reinforcement simultaneously endures chloride corrosion and seismic action, yet studies on performance degradation remain limited. This paper investigates the low-cycle fatigue (LCF) behavior of HRB400 bars under various strain amplitudes, systematically analyzing corrosion morphology, cyclic stress–strain response, fatigue life, and underlying mechanisms. Corrosion is induced by an adjusted accelerated method that replicates field conditions. Observations reveal that corrosion pits act as primary crack initiation sites. Crack paths and fracture surfaces progressively follow the local pit geometry as strain and corrosion grow. The detrimental effect of corrosion on LCF life is more pronounced for smaller bars. At a γ of around 8%, 20 mm bars lose 60.7% of the half cycles to failure at ε = ±1.5%, but only 37.5% at ε = ±5.0%. Predictive corrosion-inclusive strain amplitude (ε_a)–fatigue life models are proposed, yielding R² = 0.952 (16 mm) and 0.928 (20 mm). A unified LCF predictive model, calibrated on a database of 310 corroded/uncorroded bar tests, is established. The final model comprehensively considers the characteristics of rebars, seismic action, and corrosion damage, improving the conventional relationship between LCF life and seismic loading. This work contributes to the understanding of the fatigue behavior of HRB400 bars and provides support for time-dependent seismic reliability analysis of aging reinforced concrete structures in corrosive environments. Full article

Non-destructive evaluation of reinforced concrete structures is essential for effective maintenance and safety assessments. This study explores the combined use of active microwave thermography and deep learning to detect and localize steel reinforcement within concrete elements. Numerical simulations were developed to model the thermal response of reinforced concrete subjected to microwave excitation, generating synthetic thermal images representing the surface temperature patterns of reinforced concrete, influenced by subsurface steel reinforcement. These images served as training data for a deep neural network designed to identify and localize rebar positions based on thermal patterns. The model was trained exclusively on simulation data and subsequently validated using experimental measurements obtained from large-format concrete slabs incorporating a structured layout of embedded steel reinforcement bars. Surface temperature distributions obtained through infrared imaging were compared with model predictions to evaluate detection accuracy. The results demonstrate that the proposed method can successfully identify the presence and approximate location of internal reinforcement without damaging the concrete surface. This approach introduces a new pathway for contactless, automated inspection using a combination of physical modeling and data-driven analysis. While the current work focuses on rebar detection and localization, the methodology lays the foundation for broader applications in non-destructive testing of concrete infrastructure. Full article

Compton backscattering is a versatile non-destructive technique for material characterization and structural evaluation in reinforced concrete. This methodology enables a single-sided inspection of large structures—which is particularly useful where only one side of the material is accessible for examination—is relatively inexpensive, and can be made portable for field applications. This study aims to assess the influence of basaltic coarse aggregates on the accurate localization and dimensioning of rebar in reinforced concrete using the gamma-ray Compton backscattering technique at two distinct incident photon energies—59.5 keV and 1170 keV. The analysis was performed through Monte Carlo simulations using the FLUKA code, providing insights into the feasibility and limitations of this non-destructive method for structural evaluation. Both photon energies successfully detected the rebar embedded at a 3 cm depth in mortar, achieving a good spatial resolution and contrast, despite the presence of a significant amount of iron oxide within the aggregate. Among the evaluated sources, ⁶⁰Co yielded the highest contrast and count values, demonstrating its potential for rebar detection at greater depths within concrete structures. The single-sided Compton scattering technique proved to be effective for the investigated application and presents a promising alternative for the non-destructive assessment of real-world reinforced concrete structures. Full article

The accurate detection and precise spatial localization of rebar intersection points are essential for advancing automation in construction tasks, such as robotic rebar tying. This paper presents a vision-based methodology that integrates RGB-D sensing, camera calibration, and coordinate transformation techniques to robustly detect and localize rebar crossing points. A structured detection framework efficiently extracts intersection coordinates from RGB-D imagery, subsequently mapping these points to a global reference frame using extrinsic camera calibration parameters. To achieve comprehensive site coverage and optimize operational efficiency, the path planning challenge is reformulated as a sequencing optimization problem of the identified intersections. We propose a greedy optimization algorithm that generates smooth, snake-like traversal paths in an efficient manner. Experimental validation confirms the effectiveness of our approach, demonstrating detection accuracy exceeding 99%, an average processing time below 125 ms per intersection point, and a maximum coordinate transformation error under 2 mm. The presented solution offers a lightweight, precise, and scalable framework, significantly facilitating the integration of vision-based methods into automated construction workflows. Full article

The corrosion behaviors in chloride environment of two commercial low-alloy steel bars were studied. Through cyclic wetting tests, accelerated corrosion experiments ranging from 1 to 576 h were conducted on low-alloy bars and original bars. Techniques such as OM, SEM, EDS, AFM, and XRD were employed to characterize the corrosion emergence and expansion behaviors of these bars in a simulated marine wetting and sun exposure environment. The designed low-alloy corrosion-resistant rebar achieved a 500 MPa yield strength. In each corrosion cycle, its corrosion loss and rate were lower than those of same-strength ordinary rebars. Analysis of the rust layer’s macro and micro morphology and alloy element distribution revealed alloy elements had little effect at corrosion initiation. In later corrosion, their enrichment led to a denser rust layer, effectively blocking corrosion expansion and chloride salt infiltration. After 72 h of accelerated corrosion, the corrosion rate growth of both bars slowed. The inner rust layer’s electrochemical potential increased, and local corrosion pits turned into uniform corrosion. The inner rust layer of the rebar formed more stable chromic acid with ionic compounds, reducing corrosion sensitivity. This study offers insights into steel bar corrosion and alloy element roles, guiding the preparation of low-alloy corrosion-resistant steel bars. Full article

Composite and mixed steel-concrete buildings, apart from high structural efficiency, have great potential in terms of reuse of structural elements at the end of the life of the buildings. The use of most demountable connectors can assure the reuse of steel elements; however, the reuse of reinforced concrete (RC) elements and embedded connectors remains relatively uncertain due to potential damage of connectors during disassembly. One of the possible solutions to assure the reuse of all components could be to use demountable connectors assembled from a demountable bolt and an embedded mechanical coupler with a rebar anchor. The key challenge for practical implementation of this type of demountable connector is adequate analysis under tension loads, due to a lack of design recommendations. This paper presents experimental investigations of the connection with demountable connectors with mechanical couplers and rebar anchors, located close to the concrete edge, under pure tension load. Nine pull-out tests on single connectors embedded in the RC element and six in-air tests on bare connectors were conducted in order to define the global behavior of the connection and the local behavior of the connector, respectively. The influence of concrete strength (concrete class C20/25 and C30/37), connector diameter (with M16 and M20 bolts), and bolt grade (grades 5.8 and 8.8) on the connection behavior was discussed in terms of resistance, stiffness, deformation capacity, and failure modes. Ultimate resistance varied from 77 kN to 135 kN, with failure modes shifting from taper thread stripping to bolt fracture based on bolt grade. Based on the obtained test results, analytical equations for the calculation of tension resistance and overall deformation capacity of the connection were proposed. Full article

Prefabricated cantilever systems (PCSs) are essential for mountainous road infrastructure, yet their structural behavior under traffic loads remains insufficiently studied. This study innovatively integrates scaled experiments, finite element simulations, and field test data to develop and validate a full-scale PCS model under extreme traffic conditions. The results reveal that the beam–column junction is highly vulnerable to stress concentrations, risking concrete cracking. To address this, a novel prestressed reinforcement design is proposed, optimizing rebar placement to reduce local stresses and enhance structural integrity. Ultimate load analysis confirms that prestressing improves stiffness, load resistance, and ductility. This study provides a systematic framework for PCS optimization, promoting its application in complex engineering environments. Full article

Rebar constitutes a crucial element within tunnel lining structures, where its precise arrangement plays a pivotal role in determining both structural stability and load-bearing capacity. Due to the rebar’s high dielectric constant approaching infinity, radar signal reflections are intensified, manifesting as distinct hyperbolic patterns within radar imagery. By performing convolutional operations, these hyperbolic features of rebar can be effectively extracted from radar images. Building upon the feature extraction capabilities of the ResNet50 model, this study introduces a Deformable Attention to Capture Salient Information (DAS) mechanism, employing deformable and separable convolutions to enhance rebar localization and concentrate on hyperbolic features resulting from multiple reflections. Before the Region Proposal Network (RPN) and region of interest (ROI) pooling stages in Faster R-CNN, this study integrates a hyperbolic attention (HAT) module. Through refined distance metrics, the hyperbolic attention mechanism enhances the network’s Precision in identifying rebar hyperbolic features within feature maps. To ensure robustness across diverse conditions, this study utilizes a simulated public dataset for tunnel linings, alongside real data from the Husa Tunnel, to create a comprehensive ground-penetrating radar image dataset for tunnel linings. Experimental results indicate that the proposed model achieved an Average Precision of 94.93%, reflecting a 3.14% increase compared to the baseline model. Lastly, in a random selection of 50 radar images for testing, the model achieved a rebar detection accuracy of 93.46%, representing an enhancement of 0.94% over the baseline model. Full article