Shear Of Concrete Beams Research Articles

Behavior prediction of reinforced concrete beams shear strengthened with CFRP

This work presents the computational modeling of reinforced concrete beams, strengthened to shear with carbon fiber-reinforced polymers (CFRP), using the finite element method (FEM) and the customized ANSYS software, version 19.2. It is important to emphasize that contact elements and bilinear cohesive zone models provided by ANSYS were used to model the concrete-reinforcement interface. These models were used to identify the modes of premature failure caused by the debonding of the reinforcement, which causes poor use of the CFRP's resistance properties. The structural elements used in this analysis were twelve simply supported reinforced concrete beams, without and with shear reinforcement using CFRP, which were experimentally tested by Khalifa (1999). From the analysis of the results, it was observed that the developed numerical models were able to accurately predict the behavior of the simulated beams, both in terms of load-displacement, as well as the load and rupture mode of the beams.

Machine learning models for predicting concrete beams shear strength externally bonded with FRP

This paper focuses on preparing a database that covers a wide range of experimental data encompassing all the variations in concrete design and fiber reinforced polymer (FRP) composition in reinforced concrete (RC) beams. Artificial intelligence technique is applied to develop 10 machine learning models for estimating the shear capacity of RC beams strengthened in shear using FRP. This study is unique in the sense that it covers the largest data regarding T-beams available in literature so far and is not limited to a particular beam cross section or FRP composition. A comparison among several design guidelines is done to evaluate the efficiency of the guidelines as well as the models developed in shear capacity estimation of FRP retrofitted RC beams. The results reveal that the ensemble learning models developed in this paper namely, random forest, CatBoost and XGBoost give the highest precision in estimating shear capacity of the FRP retrofitted RC beams. For rectangular beams the R2 and MAE values from CatBoost are 0.871 and 0.214 kN, respectively whereas those for XGBoost are 0.870 and 0.202 kN, respectively. The R2 and MAE values for T-beams using random forest are 0.897 and 0.128 kN, respectively and those using CatBoost are found to be 0.899 and 0.127 kN, respectively. The most significant input feature by Shapley Additive exPlanations is found to be the effective depth for the rectangular beams whereas height of FRP layers in the case of T-beams. The proposed ensemble models in this paper are proved to be superior to the existing mechanics-driven models currently being used for design practices.

Predictive Modeling of Recycled Aggregate Concrete Beam Shear Strength Using Explainable Ensemble Learning Methods

Construction and demolition waste (CDW) together with the pollution caused by the production of new concrete are increasingly becoming a burden on the environment. An appealing strategy from both an ecological and a financial point of view is to use construction and demolition waste in the production of recycled aggregate concrete (RAC). However, past studies have shown that the currently available code provisions can be unconservative in their predictions of the shear strength of RAC beams. The current study develops accurate predictive models for the shear strength of RAC beams based on a dataset of experimental results collected from the literature. The experimental database used in this study consists of full-scale four-point flexural tests. The recycled coarse aggregate (RCA) percentage, compressive strength (fc′), effective depth (d), width of the cross-section (b), ratio of shear span to effective depth (a/d), and ratio of longitudinal reinforcement (ρw) are the input features used in the model training. It is demonstrated that the proposed machine learning models outperform the existing code equations in the prediction of shear strength. State-of-the-art metrics of accuracy, such as the coefficient of determination (R2), mean absolute error, and root mean squared error, have been utilized to quantify the performances of the ensemble machine learning models. The most accurate predictions could be obtained from the XGBoost model, with an R2 score of 0.94 on the test set. Moreover, the impact of different input features on the machine learning model predictions is explained using the SHAP algorithm. Using individual conditional expectation plots, the variation of the model predictions with respect to different input features has been visualized.

Identificação dos modos de ruptura de vigas de concreto armado reforçadas ao cisalhamento com PRFC pelo método dos elementos finitos

Abstract The rehabilitation and strengthening of concrete structures using carbon fiber reinforced polymers (CFRP) has become an interesting alternative for a series of important aspects. This material has a low specific weight, high tensile strength, corrosion and fatigue resistance, a high modulus of elasticity, and is a versatile material, with ease and speed in its application. Nevertheless, its consideration and design tend to require more sophisticated analyses to evaluate and predict the behavior of the strengthened structural element. For this reason, numerical methods, such as the Finite Element Method (FEM), can be used in such complex analyses to simulate to a high degree the actual performance of the structure. Thus, this work presents computer simulations of reinforced concrete beams shear strengthened with CFRP through the Finite Element Method in a customized ANSYS model. Special attention is given to the bond behavior between the CFRP sheets and the concrete surface of the beams through contact elements and bilinear cohesive zone models, which allowed for the identification of the debonding failure modes. Twenty-one reinforced concrete beams reported in the literature were simulated: twelve simply supported and nine continuous, with and without CFRP shear strengthening. The beams showed failure modes in shear, bending, concrete splitting, and debonding of the strengthening CFRP sheets. The numerical model developed predicted with good accuracy the beams' behavior in terms of load vs. displacement, load vs. strain, as well as their ultimate loads and failure modes.

Prediction of the FRP reinforced concrete beam shear capacity by using ELM-CRFOA

In reinforced concrete structures, the utilization of composite rebar has been increased by considering their high corrosion resistance, anti-magnetic properties, and significant tensile strength. According to the lower elasticity modulus of composite rebar in comparison with steel rebar, concrete beams reinforced including composite rebar possess a relatively lower shear strength by comparing with steel rebar. In addition, in concrete beam, reinforced shear failure by composite rebar is commonly brittle and requires precise performance prediction of the members. Thus, the reinforced concrete beams' shear strength by composite rebar is predicted utilizing an Extreme Learning Machine network based on Chaos Red Fox Optimization Algorithm (ELM-CRFOA) according to a wide range of data. The most important parameters, which are considered in this investigation, are the web width, beam effective depth, the strength of concrete compressive, the ratio of the shear span to depth, FRP longitudinal bars elasticity modulus, and ratio of the longitudinal reinforcement. This method's precision has been proved by having a comparison among the model predictions and the accumulated data and available shear design equations. According to the study outcomes, the presented model has precise outcomes in computing the concrete beams' shear strength in comparison with other existing relations. For assessing input parameters' impact on the FRP-reinforced concrete beams' shear strength, a sensitivity analysis is executed.

Impact Testing of Reinforced Concrete Beams Shear- Strengthened with Fiber-Reinforced Polymer Wraps

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Numerical modelling of the reinforced concrete beam shear failure

Shear failure of reinforced concrete members is a complex process, which depends on a huge number of different factors. It is less investigated compared to other types of failure. Modern numerical methods, including finite-element method, allow predicting complex behavior of different structures when loaded. This article deals with the detailed nonlinear analysis of the shear failure of the reinforced concrete beam, using Drucker-Prager yield criterion. The results generated based on the finite-element model, developed in ANSYS software, were compared to the results of a laboratory experiment. In addition, the main advantages and disadvantages of this approach were described.

Mechanical behavior of concrete beams shear strengthened with textile reinforced geopolymer mortar

This paper presents results from static load tests on ten RC beams, including eight shear strengthened beams with textile reinforced geopolymer mortar (TRGM), one shear strengthened beam with textile and epoxy resin, and one un-strengthened beam. The effects of number of textile layers, textile geometry, adhesive type and anchorage measures using steel strips on shear capacity of strengthened beams were investigated. The effective strain of textile in TRGM strengthened beams at failure were compared to that in shear strengthened beams with ordinary textile reinforced mortar (TRM) in previous studies. The data from tests show that the enhancement of shear capacity achieved by one layer and two layers of TRGM strengthening with respect to the un-strengthened beam are 47% and 106% respectively. And the shear capacity can get further enhancement by 15–21% when steel strips anchorage is incorporated. The effective strain developed in textile of TRGM shear strengthened beams is comparable to or even higher than that in TRM strengthened beam with similar wrapping configuration. Although one layer of TRGM is about half as effective as its resin-based counterpart in terms of increasing shear capacity, TRGM is a very promising solution for retrofitting and strengthening RC members, due to its superior fire resistance, excellent corrosion resistance and good weatherability. The calculated shear capacity of TRGM strengthened beams, using the modified model for the effective strain for TRGM, shows a reasonable agreement with the tested results.

Soft computing-based techniques for concrete beams shear strength

Despite the abundance of research works, both experimental and theoretical, conducted since the middle of the previous century up to today, the determination of the shear stress value is still remains an open issue of great interest in structural engineering. The need for further research is indicated by the fact that the majority of available proposals, whether proposed by regulatory agencies or various individuals researchers, lead to the estimation of different shear stress values; moreover, the comparison of estimated values with experimental values demonstrates that the available proposals lead to an overestimation or to an underestimation of the “true” shear stress. In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, artificial neural network models have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the consequent results with the corresponding experimental ones as well as with available formulas from previous research studies or code provisions makes obvious the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, the preliminary results presented in this work reveal the crucial parameters that affect the value of the shear strength of reinforced concrete beams with or without transverse reinforcement.

Design Approach to Determine Shear Capacity of Reinforced Concrete Beams Shear Strengthened with NSM Systems

AbstractThis paper presents a design approach to predict the shear capacity of RC beams strengthened with fiber reinforced polymer (FRP) laminates/rods applied according to the near-surface mounted...

Data analysis on fiber-reinforced polymer shear contribution of reinforced concrete beam shear strengthened with U-jacketing fiber-reinforced polymer composites

Lots of studies have investigated the shear contribution of the fiber-reinforced polymer of reinforced concrete beams with externally bonded fiber-reinforced polymer (FRP). In this paper, based on more than 200 collected experimental results of reinforced concrete beams shear strengthened with U-jacketing fiber-reinforced polymer composites, four existing design guidelines on the fiber-reinforced polymer shear contribution of strengthened reinforced concrete beams are compared in terms of the effect of the shear span-to-effective depth ratio, beam size, and stirrup ratio. These three influence factors are found to play significant roles in the prediction accuracy of different design guidelines. This paper, therefore, proposes an advanced shear strength model, which considers the effect of shear span-to-effective depth ratio, beam size, and stirrup ratio. The proposed model can provide better predictions of fiber-reinforced polymer shear contribution.

Experimental and analytical study of reinforced concrete beams shear strengthened with different types of textile-reinforced mortar

Textile-reinforced mortar (TRM) is a composite material that overcomes some drawbacks of other RC (reinforced concrete) shear strengthening solutions. In this work, four different types of TRM are used as a shear strengthening system on RC beams tested until failure. A comparative study of their mechanical performance shows that the different TRM combinations used were able to increase the load bearing capacity and change their failure mode. Moreover, new methodologies that permit evaluating the bonding behaviour of TRM and the increment in flexural toughness are presented. The experimental results are compared with previous FRP and TRM analytical formulations. Finally, new formulae for calculating the shear contribution of TRM based on experimental results are proposed.

Evaluation of Minimum Stirrups Ratio in Reinforced Concrete Flexural Members

The minimum web reinforcement specified by many codes of practice is intend to maintain adequate reserve strength and ductility. So, reasonable value of minimum stirrup ratio in reinforced concrete flexural members is a noteworthy problem, which is to prevent members occur inclined tension brittle failure in shear design. Especially in seismic design, in order to ensure the structural members to achieve ‘strong shear weak bending’ the condition, reasonably determine the minimum stirrup stirrup ratio is a key component to ensure ductile failure occurs. Analogy to determine the principles flexural members minimum reinforcement ratio, combined with European norms to determine the principles of the minimum rate of stirrup, an expression has been proposed in non-seismic reinforced concrete beam shear design with considering the ratio of shear span. The minimum shear reinforcement predicted by the proposed expression makes the required minimum stirrup ratio have been harmonized in shear design of both cases which in general flexural members and under concentrated load members.

Studies on Fire Resistance of FRP Shear Strengthened Reinforced Concrete Beams

Fire-resistance performance experiments with static loading-fire are investigated about two carbon fiber sheet (CFS) shear strengthened reinforced concrete (RC) beams exposed to the ISO834 standard fire. Shear strengthened RC beams are wrapped with fire insulation material- thick painted fire retardant coatings. Relationship between measure points’ temperature and time are achieved. The results suggest that: the ratio of shear-span is the main factor to fire-resistance rating and failure modes of CFS shear strengthened RC beams in fire; shear-failure fire-resistance rating are increased by thickening fire insulation to shear strengthened RC beams. A computer program is developed to calculate the temperature fields of fire insulated concrete beams shear strengthened with CFS coated thick fireproof material. This program is validated comparing with experimental results. Researches can give a supplement to produce overall fire-resistance factors of CFS shear strengthened reinforced concrete beams at high temperatures.

MEASURING THE DEFLECTED SHAPE OF A DOWEL BAR EMBEDDED IN CONCRETE

The instrumentation produced excellent data with regard to the small deflections of a dowel bar embedded in concrete. In this study, dowel load versus deflection characteristics were successfully measured for combinations of concrete strength, dowel diameter, and joint opening widths within the ranges of practical interest. The deflections of embedded dowels were found to be significantly affected by these variables for the ranges tested. As indicated by the experimental data, the prediction equation based on theory of a beam resting on an elastic foundation did not properly represent the dowel deflections due to the nonlinear nature of the physical system, even at relatively low levels of applied load. The instrumentation technique should have application for other problems where internal displacements of elements embedded in concrete are desired, such as dowel action in the shear of concrete beams.

Shear Strength Prediction for Concrete Members

This study presents alternative shear strength prediction equations for steel-reinforced concrete members without web reinforcements. It uses the techniques of dimensional analysis, interpolation function, and multiple regression analysis. More than 350 data were obtained from existing sources of reinforced concrete beam shear test results covering a wide range of beam properties and test methods. This analysis was done for both normal-strength concrete and high-strength concrete members with compressive strength up to 104 MPa (15,110 psi). The derivation of accurate cracking and ultimate shear strength prediction equations incorporated the original use of an interpolation function that takes into account the difference in behavior between the arch action of short beams and the beam action of long beams. The use of the interpolation function was instrumental in producing accurate cracking and ultimate shear strength equations as evidenced by the excellent correlation between experimental and theoretical values.