Shear Strength Of Reinforced Concrete Beams Research Articles

Mesoscale modelling on shear behavior of RC beams at low temperature: Influences of structural size and shear span-to-depth ratio

The low-temperature brittle failure of materials could aggravate the brittle characteristics of shear failure of RC beams, which urgently needs scientific research. This paper aims to investigate the shear behavior and corresponding size effect of reinforced concrete (RC) beams at low temperature by numerical analysis. Firstly, a two-stage thermo-mechanical coupled mesoscale simulation method was developed, which considered the meso-structure characteristics of concrete as well as the ice-strengthening effect. Based on the mesoscale simulation method validated through a series of tests, the progressive shear failure process of RC beams at room and low temperatures was captured. The influences of temperature (T = 20, −30, −60 and −90 °C), structural size (cross-sectional height H = 300, 600, and 1200 mm) and shear span-to-depth ratio (a/h0 = 1.0, 1.6, and 2.3) on key indexes of shear behavior were quantitatively analysed. The results indicate that compared to that at room temperature, the shear failure process of RC beams at low temperature is more rapid, exhibiting more obvious brittle characteristic. When the temperature drops from 20 °C to −90 °C, the nominal shear strength of RC beams is enhanced with a maximum increase of 57.0 % (for H = 300 mm) while the mid-span displacement is reduced with a maximum decrease of 46.8 % (for H = 300 mm). Compared to that at room temperature, the size effect on nominal shear strength of RC beams at low temperature is enhanced, with a maximum increase of 20.4 %. Finally, considering the influences of low temperature and shear span-to-depth ratio on the nominal shear strength, an improved size effect analytical model for was established, which can predict the shear capacity of different sized RC beams at low temperatures. This paper can provide a reference for the safe application of reinforced concrete structures in low temperature environments, and lay a foundation for the formulation of reinforced concrete structure design specifications at low temperature.

Shear Strength Evaluation of Concrete Beams with FRP Transverse Rebar

Rebar corrosion in traditional reinforced concrete (RC) components may lead to a decrease in service life and carrying capacity. This condition is one of the reasons of the growing popularity of Fiber Reinforced Polymer (FRP) rebars as a corrosion-resistant alternative, particularly in RC infrastructure projects. Because the material properties and behavior of FRP rebar are very different from conventional steel rebar, the calculations used for reinforced concrete with conventional steel reinforcement should be updated for this material. The aim of this study is to propose a new shear strength prediction model for RC beams with transverse steel rebar in order to calculate the shear strength of RC beams with FRP transverse rebar according to TS-500, which is the Turkish Building Code. To achieve this goal, Finite Element Method (FEM) models were created for 27 RC beams with FRP transverse rebars and 9 RC beams without transverse rebars. Furthermore, for RC beams with FRP transverse rebars, a prediction model has been developed. Additionally, 13 prediction models obtained from regulations or scientific studies were compared to the proposed prediction model using a database of 105 tests obtained from previous experimental studies. It was observed that the proposed prediction model provides more consistent results with the test database from the literature compared to the models suggested by other regulations or studies. Therefore, by modifying the shear strength relations recommended in TS-500 for RC beams with transverse steel rebar, they can also be applied to RC beams with transverse FRP rebars.

Prediction on the shear strength of reinforced concrete beam with openings

This study investigates the shear behavior of reinforced concrete (RC) beams with web openings. Based on the experimental and numerical data collected, different parameters were analyzed to clarify their influence on the shear capacity strength of the beam. An artificial intelligence (AI) model was proposed to predict the beam’s shear strength. Compared to the experimental data, the AI model is a reliable tool for predicting the shear strength of RC beams with openings.

Long-term shear performance of concrete beam with carbon fiber-reinforced composite grid stirrups under sustained loadings and seawater immersion

Using carbon fiber-reinforced composite (CFRP) grid stirrups to replace traditional steel stirrups in reinforced concrete (RC) beams can effectively improve the corrosion resistance of structures in marine environments. In this study, the durability of RC beams with CFRP grid stirrups under the coupled effects of sustained loads and immersion in seawater was studied. The sustained loads were set at 24% and 48% of the ultimate bearing capacity of the RC beam, and the specimens were immersed in artificial seawater at room temperature for 90 days, 180 days, and 360 days, respectively. The crack load and shear capacity of the beam were measured at the scheduled time. The initial stiffness of the beam decreased as the immersion time increased, and the higher the sustained load was, the lower the initial stiffness of the conditioned beam. The contribution of the CFRP grid stirrup to the shear load capacity after the cracking load was reached was more significant than that before. The effects of the 48% sustained load on the ultimate tensile strain of the CFRP stirrup were more significant than those for the 24% sustained load. Both immersion and sustained loading improved the cracking load and shear capacity of the beam, and the contribution of sustained loading to the shear capacity decreased as the immersion time and the sustained load level increased. Equations were proposed for predicting the shear strength of RC beams with CFRP grid stirrups under sustained loading and seawater immersion.

Shear span behavior of reinforced concrete beams with circular and rectangular openings

In reinforced concrete (RC) beams, opening is frequently required for the passage of utility ducts and/or pipes. The presence of such web openings leads to a reduction of the strength and sitffeness of the beam. This paper aims to contribute to better understanding the shear behavior of RC beam with web opening in the shear span. The study is based on an experimental program carried out on three RC beams. All beam specimens were 850 mm long with a cross section of 150 × 250 mm and a shear span to beam depth ratio (a/d) of 1.48. One beam without any openings served as the control specimen, while the remaining two beams featured circular or rectangular openings within the shear span. The test results obtained from this experimental program offer insights into the shear behavior of beams with openings. Furthermore, a simplified calculation was conducted to determine the shear strength of the test specimens, considering the influence of openings. This calculation provided a deeper understanding of how openings contribute to the reduction in the shear strength of RC beams.

Prediction of shear strength of RC slender beams based on interpretable machine learning

The purpose of this paper is to explore a prediction model of the shear strength of reinforced concrete (RC) slender beams driven by experimental data and mechanisms. An experimental database containing 774 shear test specimens of RC slender beams with and without stirrups is collected. According to that, six machine learning models are applied and compared, and the interpretability of these models is further explored. Through the comparison of six machine learning models, namely k-nearest neighbor, decision tree, random forests, Adaboost, gradient boosting decision tree, and XGBoost, the XGBoost model performs well in prediction accuracy (R2 = 0.999 and 0.953 in the training set and testing set). The XGBoost model is also significantly better than the mechanism-driven model in terms of prediction accuracy and variance, which is selected for further interpretation analysis. The interpretation analysis consists of three steps: (i) to identify the importance of features, (ii) to analyze feature dependence, (iii) to explore a novel interpretable idea combined the shear mechanism and SHapley Additive exPlanations (SHAP) method. It is the novel interpretable idea that the shear contribution distribution of the RC slender beam obtained by the SHAP value is further discussed. Through the comparison and discussion of the two mechanism models, the results of interpretable analysis indicate that the contribution distribution of the model conforms to the mechanism. Finally, the proposed interpretable approach is feasible and the developed XGBoost model is recommended for predicting the shear strength of RC beams and even similar questions.

A new model for predicting the shear strength of RC beams strengthened with externally bonded FRP sheets

Externally bonded fibre reinforced polymer (FRP) reinforcements have been widely used for upgrading the shear resistance of reinforced concrete (RC) structures. This technique has been widely studied and numerous analytical models currently exist to predict the contribution of FRP for the shear resistance of RC beams. In this study, some of the most well-known models recommended in guidelines (including fib bulletin 90, CNR-DT 200 R1/2013, and ACI 440.2R-17) are selected, and their predictive performance are assessed using a large database of 344 beams compiled from published works. In addition, this study introduces a novel model that accounts for a missing influential predictive component in the existing models, namely the ratio of existing steel stirrups. The comparison of the results obtained with this model and those from the current models demonstrates the best predictive performance of the new one.

Verification of Truss-Arch model unified for RC beams with stirrups using shear database

A shear strength analysis model called “Truss-Arch Model Unified (TAMU)” was proposed for shear-critical reinforced concrete (RC) beams with transverse reinforcement. The TAMU has its roots in the Compatibility Strut-and-Tie Model (C-STM) which is a computational modeling approach for the overall force–deformation analysis of deep beams. The TAMU simplified the C-STM so that a limited analysis can be executed by hand methods of analysis to predict the maximum load-carrying capacity of RC deep beams. While the tensile stress of concrete is generally taken into account to evaluate the shear strength of RC beams, the TAMU limit analysis focuses on the strength reduction of the principal diagonal concrete arch due to the transverse principal tensile strain. In the present study, a shear database is assembled from previous works reported in the literature to further substantiate the validity of the TAMU approach. The shear database consists of tested RC beams with shear reinforcement whose shear span-depth ratios (a/d) are between 0.5 and 4.5. Comparative TAMU analysis results show satisfactory agreement with the ultimate strengths observed in 460 RC beam tests regardless of D- and B-regions, demonstrating the method’s ability to predict the maximum load-carrying capacity for shear-critical beams. Additionally, the TAMU approach shows better accuracy and consistency against the database compared to AASHTO sectional shear design methods. The probability of reasonable prediction of the TAMU method is 92% in d-regions and 78% in B-regions, respectively, which is significantly higher than those of AASHTO sectional shear design methods, especially in d-regions. Thus, the TAMU method may be a viable improvement as an alternative strength analysis method for shear-critical RC beams with transverse reinforcement.

Effect of bond surface area on the shear strength of carbon fibre reinforced polymer (CFRP) strengthened reinforced concrete beams

The use of carbon fiber reinforced polymer (CFRP) for shear strengthening of reinforced concrete (RC) elements has grown significantly over the last few decades. The effectiveness of a CFRP strengthened system depends primarily on the bond strength between the CFRP and RC substrate. Since cost of CFRP and bond materials (epoxy adhesive) is relatively high, it is important to reduce CFRP bond surface area to RC when carrying out structural strengthening. This paper reports the effect of bond surface area on the shear strength of RC beams externally bonded with CFRP. Seven RC beams were investigated. One of the beam specimens was not strengthened and was used as a reference. The remaining six beams were strengthened with 200 g/m2 and 300 g/m2 CFRP fabrics with three different bond surface areas, i.e., 0.15 m2, 0.2 m2 and 0.25 m2 in a U-wrap configuration. Static bending tests were performed on all the beams. Results show that the CFRP's contribution to shear strength increases as the bond surface area increases. Results also show that the shear strength of the RC beam was increased by 45% due to the presence of CFRP. Fundamentally, this work presents a parametric study to guide engineers on how shear strength and corresponding ductility of beams can be increased with an optimal configuration of the bond surface between CFRP and RC elements. An optimal and cost-effective configuration is proposed for carrying out nominal shear strengthening of RC elements after construction, especially in cases where the construction engineer has concerns about the shear stirrups provided before casting.

Data-Driven Prediction Models For Total Shear Strength of Reinforced Concrete Beams With Fiber Reinforced Polymers Using An Evolutionary Machine Learning Approach

The strength of Reinforced Concrete (RC) structural elements may need to be improved due to building usage changes or damages that occurred after exposure to extreme loads. Fiber Reinforced Polymer (FRP) is commonly being used to enhance the performance of reinforced concrete beams due to several advantages such as having high strength and being lightweight. To perform the analysis and design of the members, there is a need for accurate models to determine the total shear strength of the structural elements strengthened with FRP sheets. In this paper, genetic programming has been successfully utilized to develop models to predict the total shear strength of the reinforced concrete beams. A strategy is adopted here to find a simple yet accurate formula to estimate the shear strength. These models can correlate the total shear strength of the beams reinforced with FRP sheets to the geometric and material properties of RC beams and FRP sheets, without the need for expensive laboratory tests. A compressive database of the total shear strength of the RC beams with FRP sheets was created from the literature. External validation and sensitivity analysis, using various statistical criteria, were conducted to assess the precision and validity of the proposed models. Based on 785 RC beams strengthened by externally bonded FRP sheets, tested between 1992 and 2022, two data-driven models were developed to predict the total shear strength of RC beams strengthened with FRP. The calculated correlations for Models I and II are 0.883 and 0.940, respectively. Superior performance was obtained compared to other models from the literature in accuracy. The proposed models can be utilized for design purposes and the development of structural solutions for existing structures.

Meso-scale analysis of shear performance and size effect of CFRP sheets strengthened RC beams

In order to reflect and reveal the shear failure process and mechanism of carbon fiber reinforced plastic (CFRP) sheets strengthened reinforced concrete (RC) beam, a mechanical analysis model is established by using a 3D meso-scale simulation method. The model considers the heterogeneity of concrete materials, the interaction behaviors between reinforcements and concrete, and the complex interaction behaviors between CFRP sheets and concrete, simultaneously. Different types of meso-scale models of RC beam strengthened with CFRP sheets are designed to explore the influences of stirrup ratio and CFRP fiber ratio on the nominal shear strength and size effect behaviors. Test results indicate that: 1) The action mechanisms of stirrups and CFRP sheets are similar; 2) The nominal shear strength of CFRP sheets strengthened RC beams increases with the increase of stirrup ratio and CFRP fiber ratio, while the degree of the increasing range decreases; 3) The nominal shear strength of RC beams strengthened with CFRP sheets decreases with the increase of section size, nevertheless increasing the stirrup ratio and the CFRP fiber ratio will weaken the size effect; 4) Based on the numerical test results, a novel size effect law simultaneously considering the stirrup ratio, the CFRP fiber ratio and the mutual effects between them is proposed.

Machine Learning for Shear Strength of Reinforced-Concrete Beams

Machine Learning for Shear Strength of Reinforced-Concrete Beams

Experimental and numerical investigations of the effectiveness of engineered cementitious composites and stainless steel plates in shear strengthening of reinforced concrete beams

AbstractThis paper investigates the shear strengthening of reinforced concrete (RC) beams incorporating engineered cementitious composite (ECC) and stainless steel plates (SSPs). The use of ECC, characterized by strain‐hardening in conjunction with SSPs, was investigated in this study to improve the shear performance of RC beams. Total 10 RC beams were tested under static loading up to failure to investigate a few key parameters, namely: material of strengthening (ECC and SSPs), the thickness of ECC, and shape and configuration of SSPs. Experimental findings showed that the proposed strengthening methods can significantly improve the failure pattern and increase the ultimate shear capacity of the studied RC beams by 36%–97% compared to the unstrengthened beam. Experimental results were compared against the predicted ultimate shear strength of RC beams using design equations specified by various design codes. Nonlinear three‐dimensional finite element modeling was developed for beams strengthened with ECC layer and validated against the test results and found to be accurate. Based on the experimental and numerical results, new shear capacity formulae were proposed considering the ratio of ECC‐to‐concrete beam cross‐section (ρECC) and then verified against the numerical predictions.

Machine-learning-aided improvement of mechanics-based code-conforming shear capacity equation for RC elements with stirrups

The development of shear capacity equations for reinforced concrete (RC) beams and columns has been historically pursued starting from the conceptualization of a resisting mechanism. Recently, machine learning techniques are attracting more and more interest in this field. Mechanics-based and data-driven approaches (i.e., white box and black box modeling, respectively) have been considered independently so far. Conversely, this work aims at exploring a hybrid alternative way (i.e., gray box modeling) for deriving the shear capacity equation for RC beams and columns, in which a mechanics-based code-conforming formulation is improved thanks to a machine-learning-aided approach. Specifically, the capacity equation currently in use within Europe that relies on the variable-angle truss resisting mechanism is enriched by means of Genetic Programming. Easy-to-use novel expressions for the two fundamental coefficients ruling the concrete contribution are defined to better match experimental data. The performance of the newly obtained equation is first discussed within the largest comparative assessment ever presented so far among shear strength formulations reported into existing technical codes around the world. Afterward, it is recast into a code-formatted design capacity equation using a simple, yet reliable, procedure. Overall, the results demonstrate that merging mechanics-based and data-driven methods can be beneficial in the development of capacity equations since it allows preserving the physical meaning of the resisting mechanism while enhancing the accuracy of the final predictions by means of machine learning techniques. Although the methodology is here applied to evaluate the shear strength of RC beams and columns, it is very general and can be readily extended to the development of further capacity equations.

Contribution of Longitudinal NSM-CFRP Bars on the Shear Strength of RC Beams with Varying Depths and Concrete Strengths

To assess experimentally the effect of flexural near surface mounted (NSM) carbon fiber-reinforced polymer (CFRP) bars mounted on the sides of beams on the shear strength of reinforced concrete (RC) beams, 18 shear-deficient RC beams were built, strengthened with flexural NSM-CFRP bars, and tested under three-point bending until failure. The variables of the experimental program included the beam depth, the concrete compressive strength, and the flexural fiber-reinforced polymer (FRP) reinforcement ratio. It was observed that the strengthened beams exhibited up to 35% increase in shear capacity over the control beams. It was also observed that the increase in shear strength provided by concrete after strengthening was higher for beams with normal strength concrete when compared to those with higher strength concrete. The results have also revealed that the percent change in shear strength provided by concrete for the strengthened beams decreased with the increase in beam depth. Experimental data from this study showed that current standards become unconservative for beams with large depths. Five different beam shear strength models found in the literature were utilized to predict the shear strength of the tested beams. The models that exhibited the closest agreement with the experimental data were those of the University of Houston and the second order simplified modified compression field theory. It was concluded that flexural longitudinal NSM bars are a viable solution to enhance the shear strength of RC beams and that the shear strength provided by concrete can be accurately quantified using published models.

Shear strength of recycled-aggregate concrete beams with glass-FRP stirrups

The combined use of recycled concrete aggregate (RCA) and glass fiber reinforced polymer (GFRP) reinforcement in reinforced concrete (RC) structures is deemed plausible to achieve sustainable construction. This paper aims to examine the effect of such a combination (RCA + GFRP reinforcement) on the shear behavior of RC beams. Six medium-scale RC beams (150 × 260 × 2200 mm) critical in shear were tested under three-point loading until failure. The test variables were the aggregate type (natural/recycled) and the shear reinforcement (steel/GFRP/none). The failure modes, cracking patterns, load-carrying capacities, deformational and strain characteristics were analyzed and compared among the tested specimens. It was found that using 100% RCA in the concrete mix reduced the shear strength of RC beams (by 12% on average). Minor effects were observed on the shear strength of the beam specimens (∼2%) with altering the transverse reinforcement (GFRP versus steel). Theoretical load-carrying capacities of the tested beams were obtained as per contemporary design guides and compared with the experimental results.

Enhanced shear behaviour of reinforced concrete beams containing Nano-Titanium

Nanotechnology is an important field for researchers now and it has changed perceptions, expectations and abilities to control the material world. In this study, the effect of Nano-Titanium (NT) as an addition to cement for concrete mixes is examined on the material and structural levels. The results of standard material tests showed that compressive strength and split tensile strength increase respectively, by ratio 17.91% and 46.29% with 1.0% NT addition, and the rate of increase is no longer significant beyond 1.0% NT. On the structural level, eight reinforced concrete (RC) beams containing NT in various percentages (0.0%, 0.5%, 1.0%, and 1.5%) and 15% silica fume were tested to study the effects of NT addition, shear span to depth ratio (a/d), and spacing between stirrups on shear response. The experimental results are presented for the shear strength, load–deflection, and load–strain relationships. Increasing NT content to 0.5% and 1.0% resulted in an increase in the ultimate load respectively, by 22.3% and 34.7%, and a decrease in the vertical deflection by 31.81% and 45.45% when compared to the control beam. Also, for the constant addition of 1.0% NT, decreasing (a/d) or decreasing the spacing between stirrups resulted in an improved shear strength and stiffness. Furthermore, non-linear finite element analysis (NLFEA) based on ABAQUS software was conducted to validate the experimental results. The validation studies proved that the numerical predictions of the shear strength, deflection and steel strain are in good agreement with the experimental results. Finally, an empirical relation is proposed for the shear strength of RC beams containing NT.

Shear response of RC beams encompassing hybrid CFRP strips and steel stirrups: Beam depth effect

In this study, nonlinear finite element analysis (FEA) was conducted to investigate the shear behavior of reinforced concrete (RC) beams encompassing hybrid CFRP strips and steel stirrups. Primal FEA models were calibrated and verified by comparing the load–deflection response, cracking, and failure modes with the experimentally tested RC beams. A parametric case study was then implemented to evaluate the influence of critical parameters including: configurations of CFRP strips (strip width, orientation angle), size effect, and concrete compressive strength. The results showed that changing the individual CFRP strip width while maintaining a constant total width has no significant effect on the behavior of the RC beams. Increasing the concrete compressive strength improves the bond strength between the CFRP strips and concrete leading to higher load capacity. Changing the orientation angle of the CFRP strips up to 45° has minor effect on the RC beam shear capacity. The contribution of the CFRP strips was more pronounced as the beam depth increased. A comparison showed that internally-integrated CFRP strips leads to better enhancement in the shear strength of RC beams than externally strengthening with CFRP composites.

The shear strength of concrete beams hybrid-reinforced with GFRP bars and steel bars in main reinforcement without shear reinforcement

Abstract The investigation of the structural performance of reinforced concrete members in the construction process has become a critical issue for Hybrid GFRP bars with steel bars. The ultimate concrete shear strength of reinforced concrete beams contains both GFRP bars and Steel bars in main reinforcement are a main task of work. This paper examines the effect of sharing the fiber-reinforced polymer (FRP) bars with steel bars for reinforced concrete (RC) structures on the concrete shear strength of RC beams. Fourteen RC beams without shear reinforcement were constructed and tested up to failure. The test beams included two steel-RC beams, one GFRP-RC beam, and eleven steel bars and GFRP bars (hybrid GFRP/steel)-RC beams. The main parameters were the reinforcement ratio, shear span to depth ratio, depth of the beam, concrete compressive strength, and compression reinforcement. The test results are presented in terms of crack patterns, failure modes, load-deflection, and load-strain behavior. The test results showed that hybrid GFRP/steel bars causing significant improvement in the ductility with reduction of the deformation comparing with an only steel bar in main steel in tested beams. The dowel action can play a major role in the process by which shear is carried in a beam. Finally, the initial proposal equation that calculates the shear strength of hybrid reinforced elements can serve as a guideline for the introduction of hybrid bars (GFRP and Steel) at the main reinforcement in RC beams.

Shear Strength Determination in RC Beams Using ANN Trained with Tabu Search Training Algorithm

The shear failure of reinforced concrete (RC) beams is a critical issue and has attracted the attention of researchers. The specific challenges of shear failure are the numerous factors affecting shear strength, the nonlinear behavior, and the nonlinear relationship between affecting parameters and the concrete properties. This study tackles this challenge by employing Artificial Neural Network (ANN) models. Since, according to No Free Lunch theorem, the performance of optimization algorithms is problem-dependent, this paper aims to assess the feasibility of modeling the shear strength of RC beams using ANNs trained with the Tabu Search Training (TST) algorithm. To this end, 248 experimental results were collected from the literature, and a feed-forward ANN model was employed to predict the shear strength. To assess its feasibility, the ANNs were also modeled using the Particle Swarm Optimization, and Imperialist Competitive Algorithms. As a traditional technique, the multiple regression model was also employed. The shear design equations of ACI-318-2019 were also investigated and compared with Tabu Search Trained ANN model. The analysis of results suggests the superiority of Tabu Search Trained ANNs in comparison to other suggested models in literature and the ACI-318-2019 design code.