Search Results (118)

This study adopts the east approach bridge of the Section II extra-long-span bridge on the Urumqi Ring Expressway (West Line) as an engineering prototype. A three-dimensional nonlinear finite element push-out model of headed stud connectors was developed in ABAQUS/Explicit and validated against existing test data. On this basis, parametric analyses were carried out to investigate the effects of material and geometric parameters on the shear performance of the studs. The results indicate that the load–slip response can be divided into four stages: elastic, plastic-damage development, plateau, and softening. Compared with C50 concrete, UHPC markedly increases the initial stiffness of the connectors and raises the peak shear resistance by approximately 30–40%. For the smallest stud diameter, the ductility decreases by up to about 10% and the post-peak degradation becomes more rapid, i.e., ductility deterioration is more pronounced; this unfavorable effect is particularly significant when small stud diameter is combined with shallow embedment depth. Increasing the stud diameter enhances both stiffness and peak shear resistance, whereas increasing the embedment depth delays post-peak degradation, improves residual capacity and energy dissipation, and promotes a transition in failure mode from concrete-governed failure to ductile bending–shear failure of the stud. Based on these parametric results, a larger stud height-to-diameter ratio is recommended for UHPC composite structures to achieve coordinated optimization of connection stiffness, load-carrying capacity, and ductility performance. Full article

This study presents a strut-and-tie modeling (STM) framework for reinforced concrete (RC) deep beams strengthened with intraply hybrid composites (IRCs), integrating comprehensive experimental data from beams with three different span lengths (1.0 m, 1.5 m, and 2.0 m). Although the use of fiber-reinforced polymers (FRPs) for shear strengthening of RC members is well established, limited attention has been given to the development of STM formulations specifically adapted for hybrid composite systems. In this research, three distinct IRC configurations—Aramid–Carbon (AC), Glass–Aramid (GA), and Carbon–Glass (CG)—were applied as U-shaped jackets to RC beams without internal transverse reinforcement and tested under four-point bending. All experimental data were derived from the authors’ previous studies, ensuring methodological consistency and providing a robust empirical basis for model calibration. The proposed modified STM incorporates both the axial stiffness and effective strain capacity of IRCs into the tension tie formulation, while also accounting for the enhanced diagonal strut performance arising from composite confinement effects. Parametric evaluations were conducted to investigate the influence of the span-to-depth ratio (a/d), composite configuration, and failure mode on the internal force distribution and STM topology. Comparisons between the STM-predicted shear capacities and experimental results revealed excellent correlation, particularly for deep beams (a/d = 1.0), where IRCs substantially contributed to the shear transfer mechanism through active tensile engagement and confinement. To the best of the authors’ knowledge, this is the first study to formulate and validate a comprehensive STM specifically designed for RC deep beams strengthened with IRCs. The proposed approach provides a unified analytical framework for predicting shear strength and optimizing the design of composite-strengthened RC structures. Full article

This study investigates the flexural behavior of reinforced concrete (RC) beams strengthened with externally bonded Carbon Fiber Reinforced Polymer (CFRP) or steel plate (SP), with partial debonding between internal steel reinforcement and surrounding concrete. A finite element model was developed using ABAQUS (v2021) and validated against existing experimental data by others. A total of 296 beam models were analyzed to assess the effects of shear span-to-depth ratio ($a_v/d$), reinforcement ratio ($\rho$), debonding degree ($\lambda$), strengthening material type (CFRP/SP), and material thickness ($t$) on residual flexural strength. Based on the finite element analysis (FEA) results, analytical models were proposed using a dimensionless parameter $\mathsf{\Psi }$, defined as the ratio of equivalent plastic region length to neutral axis depth. Analytical models were developed in IBM SPSS Statistics (Version 30) and showed strong agreement with FEA results. The findings provide insight into the influence of reinforcement debonding on structural behavior and support improved prediction of residual flexural capacity in strengthened RC beams with partially unbonded reinforcement. Full article

This study develops data-driven models for predicting the shear capacity of reinforced concrete (RC) beams longitudinally reinforced with fiber-reinforced polymer (FRP) bars and lacking transverse reinforcement. Owing to the comparatively low elastic modulus and linear–elastic–brittle behavior of FRP bars, reliable shear prediction remains a design challenge. A curated database of 402 tests was compiled from the literature, spanning wide ranges of beam size (width b, effective depth d), concrete compressive strength (f′c), FRP elastic modulus (Ef), longitudinal reinforcement ratio (ρf), and shear span-to-depth ratio (a/d). Multiple multivariate regression formulations—both linear and nonlinear—were developed using combinations of these variables, including a mechanics-informed reinforcement index (ρf·Ef). Model predictions were benchmarked against 15 existing expressions drawn from design codes, standards, and prior studies. Across the full database, the proposed models demonstrated consistently stronger agreement with experimental results than the existing predictors, yielding higher correlation and lower prediction error. The resulting closed-form equations are transparent and straightforward to implement, offering improved accuracy for the preliminary design and assessment of FRP-RC beams without stirrups while highlighting the influential roles of Ef, ρf, and a/d within the observed parameter ranges. Full article

Progressive collapse of building structures induced by accidental extreme loads has garnered significant attention. This study aimed to assess the impact resistance of steel-framed subassemblies with extended reverse channel connections under falling debris impact. It also sought to provide technical support for anti-collapse design. Drop-hammer impact tests were conducted to obtain baseline data. A validated finite element model using ANSYS/LS-DYNA was employed for the parametric analyses. The key parameters investigated included the impact location (mid-span vs. beam end), falling height of the impactor, and span-to-depth ratio of steel beams, with a focus on the impact resistance. The results reveal that the impact resistance depends on both the peak load capacity and the deformation capacity. The mid-span impacts exhibited higher resistance at falling heights ≥ 1.0 m due to greater plastic deformation. In contrast, the beam-end impacts performed better when the falling heights were ≤0.5 m. The impact resistance decreased with an increasing falling height. The reduction ratios exceeded the theoretical values due to the post-impact gravitational energy input. Smaller SDRs enhanced the peak resistance under both impact scenarios, with more pronounced effects in the mid-span cases. Catenary action significantly improved the mid-span impact resistance (19.3–66.7%). However, it contributed minimally to the beam-end impact resistance (0.61–1.09%), where shear action dominated. These findings offer critical technical support for optimizing steel structure designs to resist falling debris impact and enhance overall structural robustness. 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

Ultra-High-Performance Concrete (UHPC) is a game-changing, innovative material with the merits of exceptional tensile strength, making it suitable for stirrup-free UHPC beams. In this study, two 4.0 m-long large-scale stirrup-free I-shaped UHPC beams were experimentally explored in bending tests and shear tests. Cracking patterns, failure modes, and ultimate load-bearing capacity were obtained. Experimental findings revealed that the shear capacity of the stirrup-free I-shaped UHPC beams with a web thickness of merely 50.0 mm reached more than 20.0 MPa and demonstrated excellent post-cracking shear behavior. Finite element models were established and verified with experimental results to investigate the shear behaviors of stirrup-free I-shaped UHPC beams, considering the parameters of shear span-depth ratio and longitudinal reinforcement strength. The results demonstrated that as the shear span-depth ratio increases, the shear capacity of UHPC beams exhibits a declining trend, accompanied by increased mid-span deflection and a degradation in stiffness. French code and PCI report were suggested for design purposes, due to rationally conservative prediction and explicit physical indication. Full article

Ultra-high-performance concrete (UHPC) exhibits significantly superior compressive and tensile properties compared to conventional concrete, demonstrating substantial application potential in bridge engineering. This study conducted full-scale bending tests on a 30 m prestressed UHPC-NC composite box girder within an actual engineering context. The testing flexural capacity $M_t=\mathrm{34,469.2} \mathrm{k}\mathrm{N}·\mathrm{m}$ exceeded the design requirement $M_d=\mathrm{18,138.0} \mathrm{k}\mathrm{N}·\mathrm{m}$, with $M_t/M_d=1.90$. Finite element modeling (FEM) was employed to analyze and predict experimental outcomes, revealing a simulated flexural capacity of approximately 37,597.1 $\mathrm{k}\mathrm{N}·\mathrm{m}$. The finite element models further explored failure mode transitions governed by the loading position while the concentrated load-to-support distance exceeds 9.62 m (shear span to effective depth ratio λ = 6.3), and the box girder fails in flexure; while less than 9.62 m, the box girder fails in shear. The flexural capacity of the test girder was also estimated using Response-2000 software and the recommended formulas from the Chinese code T/CCES 27-2021 (Technical specification for ultra-high-performance concrete girder bridge). The Response-2000 software yielded a flexural capacity estimate of $M_r=\mathrm{30,816.1} \mathrm{k}\mathrm{N}·\mathrm{m}$. The technical specification provided two estimating results: (with safety factors) $M_{u1}=\mathrm{25,414.4} \mathrm{k}\mathrm{N}·\mathrm{m}$ and (without safety factors) $M_{u2}=\mathrm{33,810.9} \mathrm{k}\mathrm{N}·\mathrm{m}$. All estimated values of Response-2000 and Chinese code were rationally conservative ($M_r,{ M}_{u1}, M_{u2}<M_t$). Comparative analysis demonstrates that Abaqus FEM accurately simulates the flexural behavior of the prestressed UHPC-NC composite box girders. Both Response-2000 calculations and the Chinese code T/CCES 27-2021 provide critical references for similar applications of prestressed UHPC-NC composite box girders. Full article

The study presents an analysis of steel-Ultra-High Performance Concrete (UHPC) composite girders. Five composite girder specimens were designed and tested. Analytical strain solutions for the composite girders under asymmetric axial loading were derived using the energy variation method. Results indicate that asymmetric axial forces significantly exacerbate the shear lag effect. Decreasing the width-to-span ratio reduces the shear lag coefficient, while reducing the width-to-depth ratio increases it. The parametric analysis indicates that, under asymmetric axial loading, increasing the strength of the concrete is an effective method to reduce the shear lag effect of the composite girders. Increasing the thickness of the UHPC slab proves to be effective in reducing the shear lag effect. Furthermore, the study indicates that when the b₂/b₁ ratio is less than 1, it has a tiny impact on the shear lag effect; however, when the b₂/b₁ ratio is greater than 1, the shear lag effect becomes more pronounced with increasing b₂/b₁. Additionally, the thickness of the flange plate and web plate of the steel girder has no significant effect on the shear lag effect. The results of the analysis can provide references for similar designs and constructions of composite structures. Full article

Reinforced concrete deep beams (RCDBs) provide significant strength and serviceability for building structures. However, a simple, general, and universally accepted procedure for predicting their shear strength (SS) has yet to be established. This study proposes a novel data-driven approach to predicting the SS of RCDBs using an enhanced CatBoost (CB) model. For this purpose, a newly comprehensive database of RCDBs with shear failure, including 950 experimental specimens, was established and adopted. The model was developed through a customized procedure including feature selection, data preprocessing, hyperparameter tuning, and model evaluation. The CB model was further evaluated against three data-driven models (e.g., Random Forest, Extra Trees, and AdaBoost) as well as three prominent mechanics-driven models (e.g., ACI 318, CSA A23.3, and EU2). Finally, the SHAP algorithm was employed for interpretation to increase the model’s reliability. The results revealed that the CB model yielded a superior accuracy and outperformed all other models. In addition, the interpretation results showed similar trends between the CB model and mechanics-driven models. The geometric dimensions and concrete properties are the most influential input features on the SS, followed by reinforcement properties. In which the SS can be significantly improved by increasing beam width and concert strength, and by reducing shear span-to-depth ratio. Thus, the proposed interpretable data-driven model has a high potential to be an alternative approach for design practice in structural engineering. Full article

Flat slab structures are extensively utilized in modern construction owing to their efficient load transfer mechanisms and optimized space utilization. Nevertheless, the persistent issue of brittle punching shear failure at connection zones continues to pose significant engineering challenges. This study proposes an innovative cross-shaped steel-reinforced concrete (SRC) column–slab connection. Through combining test and numerical analyses, the failure mechanisms and performance control principles are systematically analyzed. A refined finite element model incorporating material nonlinearity, geometric characteristics, and interface effects is developed, demonstrating less than 3% error upon test validation. Using the validated model, the influence of key parameters—including concrete strength (C30–C60), reinforcement ratio (ρ = 0.65–1.77%), shear span–depth ratio (λ = 3–6), and limb height-to-thickness ratio (c₁/c₂ = 2–4)—on the punching shear behavior is thoroughly investigated. The results demonstrate that increasing concrete strength synergistically improves both punching shear capacity (by up to 49%) and ductility (by 33%). A critical reinforcement ratio threshold (0.8–1.2%) is identified. When exceeding this range, the punching shear capacity increases by 12%, but reduces ductility by 34%. Additionally, adjusting the shear span–depth ratio enables controlled failure mode transitions and a 24% reduction in punching shear capacity, as well as a 133% increase in displacement capacity. These results offer theoretical support for the design and promotion of this novel structural system. Full article

Steel-reinforced concrete (SRC) deep beams have been widely used in engineering applications such as high-rise buildings and long-span bridges, with their structural behavior and mechanical properties attracting significant research attention. To investigate the shear cracking behavior of SRC deep beams, seven specimens with a scale of 0.4 times were designed for static loading tests, and the influence of the shear-span-to-depth ratio λ, the width ratio of the steel flange, and the height ratio of the steel web on the width and spacing of the diagonal crack was considered. The cracking behavior of the diagonal cracks in the shear span area were recorded by the digital image correlation (DIC) technique. The results show the following: (1) the use of the DIC technology revealed the entire process of crack occurrence, development, and evolution and obtained the distribution characteristics of crack development; (2) the steel flange width has a slight effect on the spacing and width of the diagonal cracks. The diagonal crack width increased with the improvement of the height of the steel web, but the influence of the steel web on the spacing of diagonal cracks was not significant. When the height ratio increased from 0.3 to 0.45 and 0.6, the maximum oblique crack width increased by 13% and 14.5%. Based on the above experimental results and relevant analysis conclusions, an improved method was proposed to calculate the diagonal crack width of composite deep beams by further considering the influence of the crack angle. Finally, the experimental results verified its high accuracy in a qualitative analysis. The calculation method proposed in this article can be used to predict and estimate the width of diagonal cracks in SRC deep beams. Full article

This research investigates the structural behavior of high-strength concrete beams reinforced with carbon fiber-reinforced polymer (CFRP) bars and varying percentages of recycled concrete aggregate (RCA). The study examined 15 reinforced concrete beams (200 × 250 × 2000 mm) constructed with different RCA proportions (0%, 25%, 50%, 75%, and 100%) and tested at three shear span-to-depth ratios ($a/d$ = 1.5, 2.5, and 3.5), addressing a critical knowledge gap in sustainable structural engineering. Specimens exhibited compressive strengths of 55–67 MPa and reached ultimate load capacities of up to 198.4 kN. Notably, beams with 75% RCA achieved 35.7% higher capacity than control specimens at $a/d$ = 1.5, challenging conventional expectations about RCA performance. Failure modes transitioned from shear-dominated at $a/d$ = 1.5 to flexure-dominated at $a/d$= 3.5, with optimal ductility indices (up to 2.75) observed at $a/d$ = 2.5. Statistical analysis revealed significant correlations between $a/d$ ratio and performance metrics, with a perfect parabolic relationship for the ductility index (R² = 1.0, $p<0.001$). Comparison with ACI 440.1R15 predictions showed generally conservative estimates (mean experimental-to-predicted ratio = 1.02, COV = 16.9%). The findings demonstrate that high-strength concrete can successfully incorporate substantial RCA quantities (up to 75%) without compromising performance when using CFRP reinforcement, potentially reducing virgin material consumption by approximately 33% for sustainable construction applications. Full article

The dynamic behavior of three-layer composite beams, consisting of concrete slabs and steel beams, is influenced by the structural configuration of each layer as well as the shear connectors. The interlayer shear stiffness in three-layer composite beams governs their global dynamic behavior, while interlayer slippage-induced localized vibration effects represent a key limiting factor in practical applications. Based on the dynamic test results of steel–concrete double-layer composite beams, the feasibility of a finite element solid model for composite beams, which accounts for interlayer shear connectors and beam body characteristics, has been validated. Utilizing identical modeling parameters, an analytical model for the inherent vibration characteristics of three-layer steel–concrete composite beams has been developed. This study encompasses two types of composite beams: concrete–steel–concrete (CSC) and concrete–concrete–steel (CCS). Numerical simulations and theoretical analysis systematically investigated the effects of interface shear connector arrangements and structural geometric parameters on dynamic performance. Research indicates that the natural frequency of steel–concrete three-layer composite beams exhibits a distinct two-stage increasing trend with the enhancement in interlayer shear stiffness. For CSC-type simply supported composite beams, the fundamental vertical vibration frequency increases by 37.82% when achieving full shear connection at both interfaces compared to the unconnected state, while two-equal-span continuous beams show a 38.06% improvement. However, significant differences remain between the fully shear-connected state and theoretical rigid-bonding condition, with frequency discrepancies of 24.69% for simply supported beams and 24.07% for continuous beams. Notably, CCS-type simply supported beams display a 12.07% frequency increase with full concrete-to-concrete connection, exceeding even the theoretical rigid-bonding frequency value. Longitudinal connector arrangement non-uniformity significantly impacts dynamic characteristics, while the transverse arrangement has minimal influence. Among structural parameters, steel flange plate thickness has the most significant effect, followed by concrete slab width and thickness, with steel web thickness having the least impact. Based on the observation that the first-order vertical vibration frequency of three-layer composite beams exhibits a two-stage decreasing trend with an increase in the span-to-depth ratio, it is recommended that the span-to-depth ratio of three-layer steel–concrete composite beams should not be less than 10. Full article

Ultra-high-performance concrete (UHPC) has attracted considerable attention from both the construction industry and researchers due to its outstanding durability and exceptional mechanical properties, particularly its high compressive strength. Several factors influence the shear capacity of UHPC deep beams, including compressive strength, the shear span-to-depth ratio (λ), fiber content (FC), vertical web reinforcement (ρ_sv), horizontal web reinforcement (ρ_sh), and longitudinal web reinforcement (ρ_s). Considering these factors, this research proposes a novel hybrid algorithm that combines an adaptive neuro-fuzzy inference system (ANFIS) with an artificial neural network (ANN) to predict the shear capacity of UHPC deep beams. To achieve this, ANN and ANFIS algorithms were initially employed individually to predict the shear capacity of UHPC deep beams using available experimental data for training. Subsequently, a novel hybrid algorithm, integrating an ANN and ANFIS, was developed to enhance prediction accuracy by utilizing numerical data as input for training. To evaluate the accuracy of the algorithms, the performance metrics R² and RMSE were selected. The research findings indicate that the accuracy of the ANN, ANFIS, and the hybrid ANN-ANFIS algorithm was observed as R² = 0.95, R² = 0.99, and R² = 0.90, respectively. This suggests that despite not using experimental data as input for training, the ANN-ANFIS algorithm accurately predicted the shear capacity of UHPC deep beams, achieving an accuracy of up to 90.90% and 94.74% relative to the ANFIS and ANN algorithms trained on experimental results. Finally, the shear capacity of UHPC deep beams predicted using the ANN, ANFIS, and the hybrid ANN-ANFIS algorithm was compared with the values calculated based on ACI 318-19. Subsequently, a novel reliability factor was proposed, enabling the prediction of the shear capacity of UHPC deep beams reinforced with fibers with a 0.66 safety margin compared to the experimental results. This indicates that the proposed model can be effectively employed in real-world design applications. Full article