Steel Fiber Reinforced Concrete Beams Research Articles

Design and flexural behavior of steel fiber-reinforced concrete beams with regular oriented fibers and GFRP bars

In this study, steel fiber-reinforced concrete (SFRC) beam structures with regular oriented steel fibers are designed and prepared by using an assembled solenoid device. Fiber orientation is not arranged in a single direction but is similar to the direction of tensile stress of the beam in bending load conditions. With application of inductive test method and image processing technology, fiber orientation coefficient of SFRC was evaluated and increased from 0.5 to 0.7–0.8 after fiber alignment. To describe and analyze the flexural behavior of SFRC beams with regular oriented fibers and glass fiber-reinforced polymer (GFRP) rebars, 14 concrete beams with different parameters were fabricated and subjected to a four-point bending test. Specifically, the parameters included fiber content, fiber orientation, GFRP reinforcement ratio and different layer sections. The results showed that optimizing fiber orientations to the tension zone of the section led to a higher flexural strength and can well restrain the development of crack widths with comparison to randomly distributed fibers. The peak load and energy absorption increased by 7 % and 12.4 % after fiber alignment with a fiber volume fraction of 1.5 %. The combination of randomly and regularly distributed steel fibers in the form of two-layer composite members can be an efficient solution to improve the flexural performance for purpose of the optimum distribution and direction of steel fibers, and reduce the engineering cost.

A numerical critical shear crack model and its application to post‐peak behavior assessment of RC and SFRC beams

AbstractIn this paper, a numerical critical shear crack model, in which the shear‐flexural coupling effect is considered and the full process of stress and strain is captured, is proposed to evaluate the post‐peak behavior of reinforced concrete (RC) and steel fiber reinforced concrete (SFRC) beams. The shape of critical shear crack is identified by combining the modified compression field theory considering the bridge effect of steel fibers and the section analysis method. Based on the shape of critical shear crack, the shear capacity of beam members is provided by the shear tension zone and the shear compression zone. The shear capacity of the shear tension zone is calculated by the modified compression field theory and that of the shear compression zone is determined by multiaxial strength criterion of concrete. The vertical displacements caused by the flexure deformation and shear deformation are deduced by the moment area method and integration of shear strain. To verify the proposed numerical approach, a test database of 486 RC beams and 313 SFRC beams was established to predict the shear strength, and the force‐displacement relationships of twelve beam members are used to validate the feasibility for full process analysis. The stochastic analysis of beams with different failure modes is conducted via GF‐discrepancy‐based point selection method and probability density evolution method. The limitation between different failure modes is defined according to the degradation percent of shear capacity and it is taken as threshold value of failure domain, and the failure probability analysis indicates that the designed flexure beam member suffered severe degradation of shear capacity, resulting in a significant decline in safety probability.

Numerical investigation of shear behavior of steel fiber reinforced concrete beams without stirrups subjected to an asymmetric point load

Steel fibers have been shown in numerous studies to enhance the shear performance of steel fiber reinforced concrete (SFRC) beams effectively, and to evaluate the shear behavior of these beams, a nonlinear finite element (NLFE) analysis is required. In the present study, from recent experimental results of asymmetrical loading tests on SFRC beams without stirrups, three NLFE models have been validated and further developed to evaluate the impact that the ratio of shear span-to-depth (a/d) and the compressive strength of steel fiber concrete (SFC) have on the shear behavior and shear strength of SFRC beams without stirrups. The validation shows a good agreement between the chosen NLFE model and the reported experimental results. Applying the NLFE model to five different values of the a/d ratio (e.g., 1.0, 1.5, 2.0, 2.54, and 3.1) reveals a gradual decline in shear strength, while the ductility of the beam increases with the increase in ratio. Meanwhile, with increasing SFC compressive strength, the shear strength and ductility of SFRC beams without stirrups significantly increase for the same ratio of shear span-to-depth. Moreover, the failure mode of SFRC beams without stirrups dominantly depends on the a/d ratio.

A modeling strategy for the shear and flexural performance prediction of SFRC beams without stirrups accounting for the variability of properties

AbstractThe behavior of steel fiber reinforced concrete (SFRC) is highly dependent on mix design, where the properties of its components, such as cementitious matrix and fibers, impact the physical and mechanical properties of the composite. Incorporating steel fibers into concrete modifies its physical properties, potentially leading to fiber segregation and resulting in a nonuniform distribution of the fibers within the material. In experimental studies, an increase in fiber volume has been found to change the failure mode of SFRC beams from shear to flexure, and numerical investigations have shown that randomness in fiber distribution can significantly influence the behavior of the composite. Therefore, this study aims to develop a numerical model that considers variations in material properties to simulate the change in the failure mode of SFRC beams due to variations in fiber volume. The failure and yielding parameters were initially established and integrated into the concrete damaged plasticity (CDP). Subsequently, the response of both steel and concrete to tension or compression stresses was ascertained. Finally, the appropriate meshes and finite elements were chosen for the simulation. In the final approach, two methods were employed to introduce randomness into the beam. One divided the beam into different vertical segments: 30, 45, and 90, and the other combined vertical and horizontal segments: 30 vertical with 4 horizontal, 45 vertical with 5 horizontal, and 90 vertical with 10 horizontal. A script was developed in Python to automatically insert the properties. The numerical model successfully captured the change in failure mode from shear to flexure resulting from fiber volume increase. Vertical and horizontal segments increased toughness due to crack deviation, better predicting cracking pattern and loading capacity for the highest fiber contents.

Numerical Analysis of Rubberized Steel Fiber Reinforced Concrete Beams Subjected to Static and Blast Loadings

In recent years, the alarming number of terrorist attacks has highlighted the critical need for extensive research aimed at fortifying structures against explosion-induced loads. However, the insufficient energy absorption and brittleness of conventional concrete make it ineffective in withstanding blast loading, encouraging researchers to explore innovative strategies for augmenting the energy dissipation capabilities of construction materials. This study specifically delves into the incorporation of recycled rubber, a sustainable and environmentally friendly solution to the pressing issue of scrap tire disposal. The primary focus of this research revolves around the integration of rubber recycling and steel fibers into concrete, with the ultimate goal of enhancing the dynamic response of reinforced concrete (RC) beams. This novel approach not only contributes to the structural resilience required for resisting blast impacts, but also aligns with eco-friendly practices by reusing recycled rubber. A meticulous numerical investigation was undertaken to comprehensively assess the static and blast response of these augmented beams. The numerical study involved developing finite element (FE) models using ABAQUS version 6.14 for static implicit analysis and LS-DYNA R11 for blast explicit simulations. The ABAQUS model was validated against previous experimental testing for load–displacement and failure patterns. Similarly, the LS-DYNA model was validated for blast pressure in accordance with UFC-3-340 standards and for material response under blast loading, utilizing existing experimental data. The numerical models were designed to accommodate varying weight percentages of rubber, ranging from 5% to 20%, and a consistent 1.0% incorporation of steel fibers. This comprehensive analysis aims to provide valuable insights into the efficacy of these materials in improving the structural integrity and blast resistance of RC beams, thereby contributing to the development of more secure and sustainable construction practices. By reducing the reinforcement ratio in order to meet the minimum code requirements, it became evident that the failures of the rubberized RC beams tended to exhibit ductility on the tension side under static loading. In addition, the increase in the reinforcement ratio correlated with a higher failure load and decreased deflection. Furthermore, the findings indicated an optimal concrete mixture characterized by improved ductility, energy absorption, and blast load capacity, achieved by combining 5–10% rubber with steel fibers.

Experimental study on flexural mechanical properties of steel fiber reinforced alkali-activated slag concrete beams

As an environmentally friendly alternative to ordinary concrete, slag concrete is subject to limitations such as drying shrinkage and micro-cracking during its promotion and application. In order to address these challenges, steel fibers, known for their excellent tensile, shear, crack-resistance, and toughness properties, have been introduced to enhance the ductility of alkali-activated slag concrete. This study utilized steel fiber content as a variable and produced eight steel fiber-reinforced alkali-activated slag concrete beams to investigate their flexural mechanical properties. By exploring the influence of steel fiber content variation on the mechanical behavior of alkali-activated slag concrete beams and conducting validation through finite element analysis, the study unveiled the impact of steel fibers on the performance of alkali-activated slag concrete beams. The research findings demonstrate a significant enhancement in the flexural mechanical properties of alkali-activated slag concrete beams with the addition of steel fibers, leading to a reduction in surface cracking and an improvement in the durability of the elements. The outcomes of this study hold crucial theoretical implications for the widespread application of steel fiber-reinforced alkali-activated slag concrete.

Nondestructive detection of fiber content in steel fiber reinforced concrete through percussion method coordinated with a hybrid deep learning network

Accurate inspection of the steel fiber content is necessary to assure the designed performance and required quality of steel fiber reinforced concrete (SFRC). This paper presents a percussion-based nondestructive methodology in detecting the steel fiber content in SFRC components, incorporating a deep neural network capable of intelligent detection and automated classification of steel fiber content without the need for signal transformation or manual feature extraction. This research makes several noteworthy contributions. First of all, the percussion acoustic signals were captured on a smartphone from SFRC cubes with varying fiber volumes in a range of 0–2%. Subsequently, a hybrid deep learning framework named 1D CNN-BiLSTM, which harnesses advantages from both the one-dimensional conventional neural network (1D CNN) and the bidirectional long short-term memory (BiLSTM) network, was established and trained to classify these acoustic signals labeled with specific fiber contents. The results well manifest the excellent performances of the proposed network in classifying the steel fiber content, achieving a testing accuracy of 98%, which outperforms conventional machine learning methods, 1D CNN and 1D CNN-LSTM. Moreover, the noise resilience and adaptability of 1D CNN-BiLSTM were also greatly enhanced in contrast to these baseline methods. The testing accuracy exceeds 90.0% under strong noisy conditions in an SNR range of 2–10 dB. In addition, the trained model also presents an exceptional adaptability to identifying previously unseen signals from SFRC beams, yielding an accuracy of 90.34%.

Investigation of optimized machine learning models with PSO for forecasting the shear capacity of steel fiber-reinforced SCC beams with/out stirrups

This article presents a comprehensive investigation of the applicability of optimized machine learning (ML) models with particle swarm optimization (PSO) for forecasting the shear strength of steel fiber-reinforced self-compacting concrete (SFR-SCC) beams with/without stirrups in engineering applications. Firstly, a database containing the results of 101 specimens with nine input features is adopted to train the models. As ML models such as random forest (RF), adaptive boosting regression (AdaBoost), extreme gradient boosting (XGBoost), support vector regression (SVR), and K-nearest neighbors regression (KNN) are considered, whereas the hyper-parameters of these models are set as default by the sklearn module. On the other hand, PSO-ML models (PSO-RF, PSO-AdaBoost, PSO-XGBoost, PSO-SVR, and PSO–KNN) are constructed using particle swarm optimization to find the optimal combination of the hyper-parameters of these default ML models. Afterwards, the forecasting ability of each model is extensively assessed using various performance metrics, error analysis, and score analysis, and the model with the best forecasting ability is determined and compared with existing empirical models. Moreover, Shapley additive explanation (SHAP) analysis is also utilized to ensure the interpretability of the forecasting models and to overcome the “black box” problem of ML methods. Lastly, based on the best forecasting model developed in this study, a graphical user interface (GUI) has been developed to easily forecast the shear strength of SFR-SCC beams in practical applications. The results of the study clearly illustrate that PSO-ML models exhibit better forecasting capabilities than default models. It can be emphasized from here that the PSO algorithm can be an effective tool to improve the performance of ML models. It should also be pointed out that the use of PSO in simpler algorithms instead of tree-based models can further improve forecasting efficiency. On the other hand, the PSO-RF model has the best performance, with a lower error value and a high final score. And this makes it a more reliable option for predicting the shear strength of the SFR-SCC beams compared to empirical equations. In addition, according to the results of SHAP feature importance analysis, the most important input parameters affecting the shear strength of SFR-SCC beams are stirrup rebar ratio (ρv), stirrup yield strength (fyv) and longitudinal rebar ratio (ρt). This information can assist engineers in paying special attention to these features in their design and assessment processes.

Avaliação da substituição da armadura transversal mínima por fibras de aço em vigas de concreto armado

Abstract The shear strength of fiber reinforced elements is usually predicted through analytical models calibrated from experimental tests. Few results obtained from these tests consider the mechanical characterization of the material, allowing to evaluate the different performances of fiber reinforced concrete. This work evaluates the possibility of replacing the minimum shear reinforcement of reinforced concrete beams with steel fibers. For this, comparations were made evaluating the shear strength of 240 experimental tests of steel fiber reinforced concrete (SFRC) beams using formulations from the literature and international standards, to define which equations are in better agreement with the experimental data. Thus, once this expression was identified, SFRC beam design abacuses were developed to determine the amount of steel fibers needed to replace the minimum shear reinforcement, according to NBR 6118 [1]. The results showed that the model by Kwak et al. [2] presented results similar to those obtained in experimental tests of beams. Finally, it is concluded that the developed abacuses will facilitate decision-making in the design of SFRC beams.

Nonlinear finite element analysis of steel fiber reinforced concrete beams subjected to impact loads

Steel fiber reinforced concrete, compared to the conventional concrete; is a composite building material that performs much better in terms of parameters such as ductility, energy absorption capacity, fracture toughness, fatigue resistance, and the use of steel fiber reinforced concrete (SFRC) in structures has become widespread. In this study, a nonlinear finite element model (FEM) has been developed that can represent the behavior of beams produced by using steel fiber concrete subjected to impact load. For this purpose, a finite element model of beam series produced with fiber-reinforced concrete obtained from the literature was created. The ABAQUS package program was used to create models simulating the behavior. Numerical results showed that the model could successfully capture the experimental results of beams selected from the literature. In addition to simulation, a parametric study was also performed to investigate the effect of stirrups, reinforcement ratio, and drop height on the behavior of SFRC beams under impact loads. The results of the parametric study showed that increasing the fiber ratio and reinforcement ratio positively affected the behavior of SFRC beams in terms of displacement recovery.Steel fiber reinforced concrete, compared to the conventional concrete; is a composite building material that performs much better in terms of parameters such as ductility, energy absorption capacity, fracture toughness, fatigue resistance, and the use of steel fiber reinforced concrete (SFRC) in structures has become widespread. In this study, a nonlinear finite element model (FEM) has been developed that can represent the behavior of beams produced by using steel fiber concrete subjected to impact load. For this purpose, a finite element model of beam series produced with fiber-reinforced concrete obtained from the literature was created. The ABAQUS package program was used to create models simulating the behavior. Numerical results showed that the model could successfully capture the experimental results of beams selected from the literature. In addition to simulation, a parametric study was also performed to investigate the effect of stirrups, reinforcement ratio, and drop height on the behavior of SFRC beams under impact loads. The results of the parametric study showed that increasing the fiber ratio and reinforcement ratio positively affected the behavior of SFRC beams in terms of displacement recovery.

MODELING THE BENDING BEHAVIOR OF STEEL FIBER-REINFORCED CONCRETE BEAMS

In this study, modeling of the bending behavior of large-scale steel fiber-reinforced concrete beams (SFRC) was investigated using the Modified Compression Field Theory (MCFT) based non-linear finite element (NLFE) method and an analytical method. The two analysis methods included different modeling approaches for the contribution of steel fibers to the tensile strength of reinforced concrete. In the first approach, the residual tensile strength of fibrous concrete was related to the crack width and adopted into the MCTF-based NLFE method. However, the residual tensile strength was free from the crack width in the second approach, which was employed in the analytical method. The capabilities of the mentioned analysis methods were investigated on an experimental study selected from the literature. The experimental study included the four-point bending tests of five four-meter-long simply supported SFRC beams having various ratios of longitudinal reinforcement and fiber content. Results revealed that the MCTF-based NLFE method performed superior in representing the large-scale member responses (such as load-carrying capacity, crack profiles, and flexural stiffness) for the selected loading and boundary conditions while the simplified analytical tool was found to be always conservative in the determination of strength regardless of conventional reinforcement and fiber ratio. However, the rate of error was apparently proven to be highly dependent on the tensile reinforcement ratio.

Experimental investigation on the flexural behavior of concrete reinforced by various types of steel fibers

The benefit of steel fiber on the mechanical behaviors of concrete has been well accepted. The flexural behavior of steel fiber reinforced concrete (SFRC) is complicated which depends on many factors, such as matrix properties, fiber material properties, fiber geometries, fiber volume contents, and interface properties. Thus, the investigations on the flexural behavior of SFRC are needed to be expanded. In this study, the effects of fiber type with varying shapes and aspect ratios on the flexural performance of SFRC were investigated. Five steel fibers were adopted in this study: milled fiber (M), corrugated fiber (C) and three hooked fibers with aspect radios of 45 (HA), 55 (HB), and 65 (HC). Two volume fractions (0.4% and 1.0%) of steel fiber and two compressive strengths (normal and high strengths) of matrix were considered. The load-deflection curves, energy absorption capacity and equivalent flexural strength were discussed. The results show that the flexural behavior of SFRC beams reinforced by 1.0% fibers is significantly higher than that of the beams reinforced by 0.4% fibers. Hooked fiber reinforced beams performed the best flexural load-deflection response compared to the beams reinforced by milled fiber and corrugated fiber reinforced, and exhibited an increasing trend of flexural performance as the fiber aspect ratio increased. The differences between specimens with different fibers for high strength matrix are more obvious compared to the normal strength matrix.

Effects of pre-cracked width and seawater erosion on the cracking behavior of SFRC beams with BFRP bars subjected to cyclic loading

This study aims to explore the effects of various pre-cracked widths, seawater erosion and BFRP reinforcement ratios on the cracking behavior of steel fiber reinforced concrete (SFRC) beams with Basalt Fiber Reinforced Polymer (BFRP) bars subjected to cyclic loading. Pre-cracked beams were made by applying loads to obtain a predetermined crack width, such as 0.02 mm, 0.2 mm, and 0.4 mm crack widths. Eleven beams were poured and tested by a four-point bending load under cyclic loading. The crack pattern and load-crack width curves of beams were drawn and analyzed. The effects of pre-cracked width, seawater erosion, and BFRP reinforcement ratio on crack behaviors of beams were investigated and discussed. The results showed that the tensile strength of BFRP bars degenerated after seawater corrosion, and its degradation rates increased with the increase of diameter. The failure mode of beams after seawater erosion may transform from concrete crushing failure to BFRP tensile failure; The maximum crack width of all beams under service load was less than 0.5 mm. Increasing the BFRP reinforcement ratio can significantly improve the crack resistance of beams, but pre-cracked width and seawater erosion had adverse effects on the crack behavior. Existing codes overestimated the crack width of SFRC beams reinforced with BFRP bars. Finally, a new calculation model of crack width of SFRC beams with BFRP bars after seawater corrosion was proposed, and its results were closer to the experimental results.

Bending damage and fractal characteristics of steel fiber-reinforced concrete under three-point bending test

Steel fiber-reinforced concrete (SFRC) has outstanding mechanical properties and is widely used in the construction industry. To investigate the damage characteristics of SFRC beams with different steel fiber (SF) contents (0, 15, 30, 45, and 60 kg/m3) accurately, this study analyzed the bending damage (including the load-crack mouth opening displacement curve, flexural–tensile strength, fracture toughness, and microstructure and macrostructure) and fractal characteristics of SFRC beams under three-point bending tests. The crack propagation process in the SFRC beams was monitored by the digital image correlation technique. Information on microcrack evolution and macrocrack development during the loading process was collected using acoustic emission techniques. Furthermore, the correlation dimension reflecting the development state of the cracks was obtained based on the Grassberger–Procaccia algorithm. Test results showed that the performance of concrete beams in terms of deformation and cracking significantly improved by adding SFs. The beam with an SF content of 45 kg/m3 had the highest flexural–tensile strength of 6.979 MPa, which was 1.668 times higher than that of a plain concrete beam. The beam with a 60 kg/m3 SF content had the highest fracture toughness of 1.691 MPam1/2, which was 53.87% higher than that of the plain concrete beam. The fractal analysis results showed that when the correlation dimension increased, numerous small-sized, low-evolution microcracks accumulated in the fracture process zone. When the correlation dimension decreased, the microcracks converged and formed macrocracks. The peak value of the correlation dimension can be used as precursor information for SFRC beam fracture prediction.

Global Resistance Methods for the Design of Fiber-Reinforced Concrete (FRC) Beams with Material Nonlinear Finite Element Analysis

This article explores the application of the global resistance methods (GRMs) on the design of hybrid glass fiber-reinforced polymer (GFRP) and steel fiber-reinforced concrete (SFRC) beams. Addressing challenges posed by GFRP-reinforced beams, this study aims to assess the impact of material uncertainties on the behavior of such hybrid beams. The investigation involves the experimental testing of I-shaped SFRC beams, which are used to develop and validate nonlinear finite element analysis (NLFEA) models. These models incorporate material non-linearities while minimizing uncertainties related to modeling assumptions. Through the application of GRM, the study evaluates the global resistance safety factor, offering insights into the structural performance of hybrid reinforcement SFRC beams. Ultimately, this research seeks to facilitate a transition from traditional localized approaches to more accurate and comprehensive analyses for the design of hybrid reinforcement SFRC beams, contributing to the advancement of structural engineering by promoting safer, more resilient, and sustainable construction systems.

Influence of Fiber Orientation on the Shear Properties of Steel Fiber-Reinforced Reactive Powder Concrete Beams

Steel fiber-reinforced reactive powder concrete (SFRPC) has good mechanical properties and is thus useful for engineering applications. Generally, the fibers in SFRPC are randomly distributed. To study the effects of the amount, length, and orientation of steel fibers on the shear strength of SFRPC beams, nonreinforced aligned steel fiber-reinforced reactive powder concrete (ASFRPC) beams were prepared using a large-scale electromagnetic field orientation device. Shear tests of specimens with a shear span ratio of 1.5 were performed under two fiber contents (1.0% and 2.0%) and three fiber lengths (20, 30, and 40 mm). The full-field strain during the loading process was obtained via the digital image correlation method, and the effects of fiber quantity and orientation on the shear strength of the beams were analyzed. The ASFRPC beams exhibited higher ductility but lower shear capacity than the SFRPC beams under the same conditions. The shear capacity increased with the quantity of steel fibers. According to the test results, the calculation formulas of the shear-bearing capacities of ASFRPC and SFRPC beams were established.

A novel analytical framework for assessing the impact response of SFRC beam

This paper presents a novel model for predicting the impact response of steel fiber reinforced concrete (SFRC) beams. The model utilizes the principles of energy conservation and impulse-momentum theorem to calculate the maximum reaction force and peak impact force. A tensile behavior model for simulating the concrete behavior is proposed considering the effect of volume fraction of steel fibers and the effect of strain rate on the concrete properties. Additionally, the conventional beam theory, along with a cross-section-layered approach, is used to express the total beam's reaction forces vs deflection relationship. Afterwards, the model calculates the maximum midspan deflection of SFRC beams subjected to impact loading by applying the principle of conservation of energy and considering the effect of strain rate. The proposed model is compared with 121 impact tests, and the results show that the model can estimate the maximum reaction force of SFRC beams with acceptable accuracy.

Numerical analysis of the shear behavior for steel fiber reinforced concrete beams with corroded reinforcing bars

Steel fiber reinforced concrete (SFRC), which improves mechanical properties after cracking, became an interesting material for reinforced concrete structures. However, there is limited research on the performance of SFRC beams in corrosive environments. This paper concerns numerical simulations to validate and evaluate the impact of design-oriented parameters contributing to the shear behavior of SFRC beams corroded under chloride attack. The finite element analysis (FEA) results were compared with the experimental data for both non-corroded and corroded SFRC beams. To minimize the differences, the comparison between the proposed models and experiment showed a close agreement on the load–displacement relationship, failure mode, and cracking pattern. After conducting parametric investigations, the numerical results reveal that the shear reinforcement ratio insignificantly affects the shear strength of corroded SFRC beams. In contrast, concrete compressive strength, shear span-to-depth ratio, and corrosion degree of tensile longitudinal reinforcements significantly impact the shear strength of corroded SFRC beams.

A Finite Element Approach to Evaluate and Predict the Shear Capacity of Steel Fiber-Reinforced Concrete Beams

Adding steel fibers to a concrete matrix enhances the shear capacity of reinforced concrete beams. A comprehensive understanding of this phenomenon is essential to evaluate engineering designs accurately. The shear capacity of Steel Fiber Reinforced Concrete (SFRC) beams is affected by many parameters, such as the ratio of the shear span to the effective depth of the SFRC beam, the compressive strength of concrete, the longitudinal reinforcement ratio, volume fraction, aspect ratio, and the type of fibers. Therefore, to cover the influence of these parameters on the shear capacity of SFRC beams, 91 beams from previous studies, divided into 10 groups, were considered in the current study. Two approaches have been used to predict the shear capacity of SFRC beams. The first approach used 7 predicting equations derived from previous studies and the second one used finite element analysis (ANSYS software) to simulate the 91 beams. Despite the many approaches to simulate the structure elements, there is no reliable approach able to simulate satisfactorily 91 SFRC beams as this study does. The log file of ANSYS software was used to simulate and calculate the shear strength capacity of the beams. The results show a reasonable agreement with the experimental tests. The extracted results were much closer and more realistic than those obtained by the predicting equations. Also, the χ factor (squared value of experimental shear capacity to the predicted shear capacity) of the ANSYS software results is 97%, while the closest proposed equation gives 91%.

Serviceability evaluation model of SFRC beams reinforced with FRP bars based on deformation control

This research investigated the flexural behavior of steel fiber-reinforced concrete (SFRC) beams reinforced with fiber-reinforced polymer (FRP) bars to promote its application in engineering. Ten beams with widths of 150 mm, heights of 250 mm and lengths of 1800 mm were tested under four-point bending. The experimental parameters included the reinforcement type, steel fiber volume fraction, concrete strength, and longitudinal reinforcement ratio of the FRP bars. Based on the test results, a prediction model was proposed for the balanced reinforcement ratio (ρfb), considering the influence of steel fibers. Deformation prediction equations in the current design codes in the US, China, and Canada were compared based on the experimental results. The increase in the reinforcement ratio (ρf) can improve both the service moment (Ms) and the ultimate moment (Mu). With an increase in ρf/ρfb, the Ms/Mu value decreased for under-reinforcement beams but increased for over-reinforcement beams. Based on the linear regression theory, a new calculation model for the flexural moment utilization efficiency of SFRC beams reinforced with FRP bars in serviceability limit states is established. The ductility indices of all beams are above the minimum limit of 4, as proposed by CSA S6-14.