Concrete Beams Research Articles

End anchorage‐reinforcement CFRP systems for heat‐damaged beams with side NSM CFRP rope

AbstractThe efficiency of retrofitting systems with side near surface mounted (SNSM) CFRP ropes in boosting the flexural performance of intact/heat‐damaged reinforced concrete (RC) beams was investigated using a total of 14 RC beams (250 × 150 × 1450 mm) in two groups. In the first group, the beams were strengthened using SNSM CFRP ropes of a parabolic profile without and with end fan or hock anchorages, coupled with the implantation of lateral and/or vertical CFRP dowels in the high‐shear zone. The beams of the second group were repaired using similar configurations after being heated to 400°C in an electrical furnace for 2 h. A control beam in each group was designated as a reference. The mechanical performance and cracking sequence in all beams was evaluated under four‐point loading test setup. Heat‐damage resulted in reductions in load capacity and stiffness at 11% and 10%, yet an increase in toughness and displacement ductility by 18% and 20%, respectively. Implementing end hocks with end vertical and lateral dowels prevented concrete‐cover separation; imparting the best enhancement in structural performance for the repaired and post‐heated beams. All beams experienced flexural failure mode except for the heat‐damaged one, repaired with end‐hock anchorage without lateral doweling.

Study of FRP on Preloaded Beam as A Method of Retrofitting - A Review

Over the past two decades, fiber-reinforced polymers have gained prominence in structural engineering due to their unique properties, offering an alternative to traditional materials like steel and concrete. FRPs consist of high-strength fibers embedded in a polymer matrix, resulting in superior strength-to-weight ratios, excellent corrosion resistance, and fatigue durability. These materials are widely used in aerospace, automotive, and infrastructure applications. Key types of FRPs include carbon fiber reinforced polymer, glass fiber reinforced polymer, aramid fiber reinforced polymer, and basalt fiber reinforced polymer, each offering specific advantages. CFRP is recognized for its high tensile strength, while GFRP is widely chosen for its affordability and adequate performance in less demanding structural applications. This review paper focuses on retrofitting predamaged reinforced concrete beams using carbon fiber-reinforced polymer and glass fiber-reinforced polymer sheets. It examines how preloading, fiber material, and fiber arrangement affect the structural performance of these beams, particularly in terms of flexural strength, ductility, stiffness, and failure mechanisms. Going through several papers the studies showed that CFRP and GFRP significantly enhance load-bearing capacity, energy absorption, and delay failure due to deboning. Key factors such as preload levels and fiber configuration were compared by go thronging several paper. The paper highlights real-world applications, where CFRP is commonly used in bridge rehabilitation and GFRP is favored for less demanding tasks, such as retrofitting low-rise building beams, both playing a critical role in extending the service life of structures while reducing costs.

Electromagnetic wave-driven deep learning for structural evaluation of reinforced concrete strength

Monitoring the performance of reinforced concrete structures, particularly in terms of strength reduction, presents significant challenges due to the practical limitations of traditional detection methods. This study introduces an innovative framework that incorporates a non-destructive technique using electromagnetic waves (EM-waves) transmitted via Radio Frequency Identification (RFID) technology, combined with two-dimensional (2-D) Fourier transform, fractal dimension analysis, and deep learning techniques to predict reductions in structural strength. Experiments were conducted on three reinforced concrete beam (RCB) specimens exhibiting various levels of reinforcement corrosion. From these, a dataset of 1,800 EMwave images was generated and classified into “normal” and “reduced strength” categories. These categories were used to train and validate a Convolutional Neural Network (CNN), which demonstrated robust performance, achieving a high accuracy of 0.91 and an F1-score of 0.93 in classifying instances of reduced structural strength. This approach offers a promising solution for detecting strength reduction in reinforced concrete infrastructures, enhancing both safety and maintenance efficiency.

Correction: An Updated Review on the Effect of CFRP on Flexural Performance of Reinforced Concrete Beams

Correction: An Updated Review on the Effect of CFRP on Flexural Performance of Reinforced Concrete Beams

Performance of RC beams strengthened using NSM FRP and cement based adhesives after exposure to elevated temperatures

A popular method for strengthening of reinforced concrete (RC) structures is the use of carbon fiber reinforced polymers (CFRP) bonded to the structural elements using the near surface mounted (NSM) techniques. While this method possesses many advantages, poor fire resistance as a result of the low glass transition temperatures (TG) of organic resins remains a significant drawback. Replacement of organic resins with cement based adhesives (CBA) could potentially improve the fire performance of NSM FRP systems and reduce the amount of insulation required to achieve the required fire endurance period. This paper presents an experimental program consisting of fifteen RC beams strengthened in flexure using NSM FRP bonded using CBA and subjected to the standard fire time temperature curve up to a target temperature of 600 °C. Twelve of the beams were strengthened using NSM-FRP laminates and bars including both smooth and rough FRP laminates and the remaining three specimens acted as control beams. Further, the use of plasterboard was explored as fire protection to further increase the residual strength of the specimens after heating. Results showed that the reinforced concrete beams strengthened with NSM CFRP retained 82 % to 61 % of their unheated strengthened ultimate load after heat exposure. This was a result of the superior performance of the cement-based adhesive at high temperature and the fire protection provided to the CFRP through embedment in the grooves. Moreover, the use of plasterboard as fire protection decreased the CFRP temperature by 42–24 %. The insulated beams behaved similarly to strengthened beams prior to fire exposure.

Numerical simulation of post fire-behaviour of high strength lightweight reinforced concrete beams strengthened with basalt fiber-reinforced polymer grid and engineered cementitious composites jacket

Numerical simulation of post fire-behaviour of high strength lightweight reinforced concrete beams strengthened with basalt fiber-reinforced polymer grid and engineered cementitious composites jacket

Enhancing concrete beam performance with PVA fibers, coal ash, and graphene fabric: a comprehensive structural analysis

ABSTRACT This study evaluates the structural performance of Polyvinyl Alcohol Cementitious Composites (PVCC)-layered reinforced concrete beams with coal ash under static loading. Experimental investigations included first crack load, ultimate load, load-deflection behavior, ductility, stiffness, and energy absorption. Results highlight the influence of Polyvinyl Alcohol-(PVA) fiber dosage on structural behavior. The control specimen exhibited an initial crack load of 80kN, with subsequent specimens showing varied crack initiation loads influenced by PVA fiber content. Optimal performance was observed at 1.2% PVA fiber dosage, with higher dosages leading to earlier crack initiation. Ultimate load carrying capacity increased with PVA fiber addition, reaching a peak at 1.2% dosage before slight decreases occurred with higher dosages. Load-deflection behavior demonstrated the superior performance of PVCC layered beams, particularly specimen BP3, attributed to optimal fiber content. Ductility, stiffness, and energy absorption increased with PVA fiber reinforcement, with 1.2% dosage yielding optimal results. Excessive fiber content led to diminishing returns. Energy index analysis revealed superior energy dissipation in specimens with higher PVA fiber content, emphasizing the effectiveness of fiber reinforcement in enhancing structural performance. Overall, the study underscores the importance of optimizing PVA fiber dosage to maximize structural resilience and load-bearing capacity in PVCC-layered concrete beams with coal ash.

The Effect of Fiber Type on The Shear Capacity of Beams Manufactured By Using Geopolymer Concrete Based on Fly Ash

Ordinary Portland cement is currently generally used cementitious material in the construction industry. However, it has significant drawbacks as it not only depletes natural resources but also releases a substantial amount of carbon dioxide during its production process. On the other hand, alkali-activated cement is an alternative option that is derived from raw materials like slag, fly ash, and metakaolin, which contain silicon dioxide (SiO2) and aluminum oxide (Al2O3). This study investigates the shear capacity of fibre-reinforced geopolymer concrete (GPC) beams under shear loads. In the study, the shear behavior of beams produced from fly ash-based geopolymer of three different fiber types was determined by applying a three-point shear test. Four beams of 100x100x400 mm dimensions were produced: reference, steel fiber, basalt fiber and glass fiber. The results showed that using steel fiber has the greatest impact on shear capacity. In addition, the shear capacity of fibrous samples is greater than the shear capacity of the reference sample. The steel fiber sample has 203% more shear capacity than the reference sample.

Flexural behavior of hybrid C-PET FRP-strengthened RC beams with U-strip anchorages

In this study, a comprehensive experimental and theoretical work was conducted on the bending performance of hybrid carbon-polyethylene terephthalate (C-PET) fiber-reinforced polymer (FRP) strengthened reinforced concrete (RC) beams with U-strip anchorages. Eleven RC beams were tested under a four-point bending load to investigate the influence of stacking sequence and U-strip anchorages. The bending performance of strengthened beams was carefully examined and discussed with regard to failure mode, flexural strength, ductility coefficient, and FRP strain development. The hybrid strengthened beams with U-strip anchorages exhibited 10.54 %−21.97 % higher flexural strength and 4.30 %−206.27 % higher ductility factors than the corresponding strengthened beams without U-strip anchorages. In addition, a theoretical analysis model with high accuracy was proposed to simulate the load-deflection curves of the strengthened beams based on the section analysis and plastic hinge model. Finally, this paper evaluated the accuracy of design guidelines (including GB 50608, ACI 440.2 R, and CNR DT 200 R1) in calculating the load-bearing capacities of strengthened beams.

Shear Strengthening of RC Beams Incorporating Post-Tensioned Bars and Engineered Cementitious Composite Reinforced with Palm Fronds

This paper investigates, experimentally and numerically, the shear strengthening of Normal Concrete (NC) beams using post-tensioning steel bars and Engineered Cementitious Composite (ECC) reinforced with chemically cured Palm Fronds (PFs). The benefits of strain-hardening ECC and the tensile strength of PFs cured with 6% wt Alkali NaOH solution beside post-tensioned bars have been employed herein. Seven full-scale Reinforced Concrete (RC) beams were fabricated and experimented with under three-point loading until failure. The test parameters include the strengthening technique, type, and configuration of the material used for strengthening. The strengthening process has been implemented through two techniques: Externally Bonded Reinforcement (EBR) and Near-Surface Mounted (NSM) Reinforcement. The strengthening materials have been configured and placed in horizontal, vertical, and inclined positions. The effectiveness of the strengthening methods has been evaluated by examining their cracking propagations, load-deflection responses, collapse modes, elastic stiffness, and absorbed energy. It was found that the proposed strengthening systems could significantly control the crack pattern and failure mode, and they could enhance the ultimate load amplitude up to 37% and 50% for NSM ECC with PFs and EBR post-tensioning steel bars, respectively. Nonlinear three-dimensional finite element models of the tested beams were developed and validated with the test data, where it was found that finite element models predict the structural performance of tested beams with a maximum error of only 2%.

Machine Learning Ensemble Methodologies for the Prediction of the Failure Mode of Reinforced Concrete Beam–Column Joints

One of the most critical aspects in the seismic behavior or reinforced concrete (RC) structures pertains to beam–column joints. Modern seismic design codes dictate that, if failure is to occur, then this should be the ductile yielding of the beam and not brittle shear failure of the joint, which can lead to sudden collapse and loss of human lives. To this end, it is imperative to be able to predict the failure mode of RC joints for a large number of structures in a building stock. In this research effort, various ensemble machine learning algorithms were employed to develop novel, robust classification models. A dataset comprising 486 measurements from real experiments was utilized. The performance of the employed classifiers was assessed using Precision, Recall, F1-Score, and overall Accuracy indices. N-fold cross-validation was employed to enhance generalization. Moreover, the obtained models were compared to the available engineering ones currently adopted by many international organizations and researchers. The novel ensemble models introduced in this research were proven to perform much better by improving the obtained accuracy by 12–18%. The obtained metrics also presented small variability among the examined failure modes, indicating unbiased models. Overall, the results indicate that the proposed methodologies can be confidently employed for the prediction of the failure mode of RC joints.

Ductility assessment of GFRP reinforced concrete beams with a wedge-based mechanical model accounting for discrete fibers and confinement

Glass fiber-reinforced polymer (GFRP) bars for internal reinforcement for concrete have gained attention due to their non-corrosive properties, high resistance, and electromagnetic transparency. On the other hand, the brittle behavior and low modulus of elasticity of FRP bars limit their application and diffusion in the civil construction market. From this perspective, this work investigates the influence of three components on the increase of ductility of GFRP beams: i) discrete alkali-resistant glass fibers added to the concrete; ii) confinement of the concrete with GFRP stirrups; and iii) use of longitudinal reinforcement on the compression zone. An experimental program including four over-reinforced beams with different reinforcement configurations was conducted. The beams were tested in four-point bending configuration and the use of fibers, stirrups and compression reinforcement contributed to substantially increasing the beam ductility index. Finally, a concrete wedge model was developed to obtain equivalent stress-strain relationships for the concrete in compression. The model was successfully validated against experiments and proved to be a useful tool for rationally evaluating GFRP RC beams’ ductility.

Evaluating the Performance of Ensemble Machine Learning Algorithms Over Traditional Machine Learning Algorithms for Predicting Fire Resistance in FRP Strengthened Concrete Beams

In recent years, fiber-reinforced polymers (FRP) have emerged as a highly effective solution for strengthening reinforced concrete (RC) structures. However, accurately assessing the fire resistance of FRP-strengthened members remains a significant challenge due to the limited guidance available in current building codes, often leading to conservative and cost-intensive evaluations. Experimental testing and numerical analysis required for such assessments are resource-demanding, highlighting the need for more efficient methods. This study investigates the application of machine learning (ML) techniques to predict the fire resistance of FRP-strengthened RC beams. Twelve ML models, including eight ensemble methods and four traditional approaches, were employed. The models were trained using a comprehensive dataset comprising over 21,000 data points obtained from numerical simulations and experimental tests. The dataset captured variations in geometric configurations, insulation strategies, loading conditions, and material properties. To enhance predictive accuracy, Bayesian optimization and k-fold cross-validation were applied for model tuning, while the Shapley Additive Explanations (SHAP) method was utilized to assess the relative importance of features influencing fire resistance. Among the models tested, Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Light Gradient Boosting (LGBoost), and Gradient Boosting (GRB) demonstrated superior performance, achieving accuracy rates exceeding 92%. Key factors identified as significantly affecting fire resistance included loading ratio, area of tensile reinforcement, insulation depth, concrete cover thickness, and FRP area. The findings underscore the potential of ensemble ML techniques over traditional methods for accurately predicting the fire resistance of FRP-strengthened RC beams, offering critical insights for optimizing design practices and enhancing structural fire safety.

Experimental and numerical investigation on RC beams with web openings subjected to pure torsion strengthened by ferrocement technique or GFRP sheets

The main objective of the current experimental and numerical study is to investigate the effect of strengthening by ferrocement layers on the behavior of reinforced concrete (RC) beams with openings subjected to pure torsion and compare it with the beams that were strengthened by Glass Fiber Reinforced Polymer (GFRP). The experimental investigation consists of twelve reinforced concrete (RC) beams that have been divided into four groups. The parameters under investigation included the strengthening technique (ferrocement or External Bonded Glass Fiber Reinforced Polymer EB-GFRP), type of steel mesh (welded wire mesh and expanded metal mesh), number of layers of mesh (1, 2, 3), extension length outside opening (50, 100 or 200) mm, strengthening configuration (full or U-shape) wrapping, and the anchoring system effect. The experimental work consists of one solid beam and eleven beams with openings. The tested beams yielded results such as cracking and ultimate torques, angle of rotation, and mechanism of failure. Creating an opening in the control solid beam resulted in a 38.46 % decrease in ultimate torque, while using different techniques during this research proved efficiency in the strengthening process. Using GFRP U-wrapping and fully wrapping to strengthen the area around the beam's opening increased the ultimate torque by 50 % and 81.25 %, respectively, compared to the un-strengthened beam with an opening. Adding fully wrapped ferrocement layers to the beam with an opening greatly improved its torsional strength. The ultimate torque increased by 40.63 % to 81.25 % compared to the beam with an unreinforced opening. Increasing the number of welded steel mesh layers from 1 to 3 in the ferrocement strengthening technique led to an increase in ultimate torque from 40.63 % to 75 % compared with the un-strengthened beam with the opening. The tests showed that using expanded metal mesh instead of welded wire mesh in strengthened beams with holes led to a 9.43 % higher ultimate torsional capacity, indicating that the expanded metal mesh worked better than the welded wire mesh. Using the U-shape ferrocement wrapping with anchors was better than without anchors, resulting in a 9.1 % increase in the ultimate torsional capacity. Applying a fully wrapped GFRP sheet or expanded metal mesh ferrocement strengthening achieved the highest ultimate torque, 81.25 % more than the un-strengthened beam with an opening. Moreover, a 3D non-linear finite element analysis is conducted using ABAQUS software to forecast the torsional properties of beams strengthened by either ferrocement or EB-GFRP. The numerical model captured the failure patterns, twisting angle, and ultimate load of tested beams. The experimental and analytical results were in good agreement. The research concluded the effectiveness of using the ferrocement reinforced with different steel mesh types in strengthening reinforced concrete beams with openings under pure torsion, the cost-efficiency and simplicity of ferrocement as a solution compared to its results with EB-GFRP techniques.

Numerical analysis of load-bearing capacity of shear-strengthened reinforced concrete beams without shear reinforcement using side-bonded CFRP sheets

As CFRP (carbon fiber-reinforced polymer) offers high retrofit efficiency for structural members in bending and shear due to its superior mechanical properties compared to steel, sheets made from this material have become ubiquitous in strengthening existing reinforced concrete (RC) structures. However, there needs to be more research on RC beams with no stirrups that have been shear-strengthened with side-bonded CFRP sheets. As such, this study aims to investigate this specific topic and assess design-related parameters that impact the load-bearing capacity of these shear-strengthened beams. To achieve this, nonlinear finite element models of four RC beams, including one control beam and three beams strengthened with side-bonded CFRP sheets, were built and verified regarding shear capacity, crack patterns, and failure mechanisms. The simulated beams demonstrated a high level of accuracy in all mentioned aspects. Numerical models were then developed to evaluate the design-oriented parameters that affect the response of shear-strengthened beams, including the concrete compressive strength, the amount of steel reinforcement, the number of CFRP layers, the CFRP bonding configuration, and the shear span-to-effective depth ratio. The results showed that not only the compressive strength of the concrete but also the amount of steel longitudinal reinforcement had a significant relationship with the load-bearing capacity of shear-strengthened beams. Meanwhile, the bonding configuration and the layer number of side-bonded CFRP sheets considerably influenced the ductility, the crack pattern, and the failure mode of shear-strengthened beams.

A study on the flexural behaviour and self-healing of fibre reinforced bacterial concrete beams

A study on the flexural behaviour and self-healing of fibre reinforced bacterial concrete beams

Corrosion level estimation in reinforced concrete beams by acoustic emission sensing and selective crack measurements

AbstractAccurate corrosion assessment plays an important role in ensuring structural safety of reinforced concrete (RC) structures. However, on‐site assessment of existing concrete structures presents many challenges, including high costs, limited inspection timeframes, and difficult accessibility. To facilitate inspection‐based corrosion assessment, this paper presents a novel approach by combining short‐term acoustic emission (AE) monitoring with selective crack width measurements for corrosion level (CL) assessment. AE sensing is a monitoring technique which can detect ongoing internal degradation mechanisms by analyzing ultrasonic waves emitted by the damage process. Yet, two major challenges arise on site: (1) practical limitations prevent continuous AE monitoring over the structure's entire lifetime and (2) AE can only generate relative results in the absence of reference measurements. This paper addresses both challenges to bridge the gap between laboratory experiments and on‐site monitoring of corroding RC structures. First, short periods of AE monitoring data are analyzed to investigate the potential of AE sensing over limited timeframes. Second, AE data of corroding RC beams are combined with sparse crack width measurements in order to obtain absolute CLs. The proposed methodology is experimentally validated by corroding eight beams with varying dimensions, corrosion zones, and reinforcement layouts. The experimental results prove that the estimated CLs closely match the rebar mass losses, with a mean absolute error of 1.53% CL for beams reaching up to 14% CL, confirming the potential of the combined AE and crack width measurement technique as an efficient and accurate condition assessment approach. Moreover, AE sensing provides detailed spatial variability of the rebar corrosion in the monitored zone, which is challenging to obtain with conventional techniques. By using this dual‐technique approach, shorter monitoring periods prove nearly as effective as continuous AE monitoring in accurately estimating CLs.

Numerical Simulation of Rubber Concrete Considering Fatigue Damage Accumulation of Cohesive Zone Model.

Rubber concrete (RC) has been used in fatigue-resistant components due to its durability, yet the numerical simulation of its fatigue properties remains in its early stages. This study proposes a cohesive zone model (CZM) that accounts for the accumulation of fatigue damage at the mesoscale to investigate the fatigue performance of RC. The model integrates static and fatigue damage in the CZM, effectively capturing damage caused by fatigue loading. Validation was conducted using experimental data from the existing literature. Based on this validation, four concrete beams with varying rubber replacement rates (0%, 5%, 10%, and 15%) were tested. The CZM was employed to describe the mechanical behavior of the interface transition zones (ITZs) and the mortar interior, which were simulated and analyzed under different stress levels. The results demonstrate that the model accurately simulates crack propagation paths, interface damage evolution, and the fatigue life of RC beams under fatigue loading. A functional relationship between fatigue life and stress level was established for various rubber replacement rates. This study provides a reference model for numerical simulations of RC under fatigue loading conditions and introduces new approaches for analyzing the fatigue performance of other materials.

Influence of web reinforcement on shear behavior and size effect of lightweight aggregate concrete deep beams: Experimental and theoretical studies

In practice, deep beams with web reinforcement are the predominant form of deep beams. Understanding the effect of web reinforcement in deep beams made of lightweight aggregate concrete (LWAC) is essential for the structural application of LWAC deep beams, but it is still a pending subject. In this study, eight LWAC deep beams and two normal weight concrete deep beams were tested to investigate the influence of web reinforcement and beam depth on the shear behavior and size effect of LWAC deep beams. The experimental results showed that all deep beams failed in shear–compression mode, which is independent of the web reinforcement ratio and beam depth. The web reinforcement confined the concrete within the strut area and limited the concrete spalling, which positively affected the normalized serviceability/ultimate shear strength. Moreover, web reinforcement effectively mitigated the size effect by resisting the transverse tensile stress and improving the boundary confinement of the concrete struts, but could not eliminate the size effect in LWAC deep beams. Based on these results, a modified strut-and-tie model (MSTM) was developed to quantify the contribution of web reinforcements to the shear capacity more accurately than the conventional strut-and-tie model. The predictions obtained using the MSTM with the Warwick-Foster’s strut efficiency factor were in excellent agreement with the experimental results.

Finite element analysis of ductility and flexural capacity of FRP and steel bars hybrid reinforced concrete beams

AbstractTo study the flexural behavior of hybrid reinforced concrete (hybrid‐RC) beams with FRP and steel bars, this paper used ABAQUS finite element (FE) software to model and nonlinear analyze the hybrid‐RC beams and investigate the effects of effective reinforcement ratio, concrete strength, and FRP bars type on the flexural behavior of hybrid‐RC beams. In addition, the FRP bars stress, flexural bearing capacity, and ductility formulas for hybrid‐RC beams were fitted based on the FE results, and existing literature data were used to verify their accuracy. The FE model results indicated that the effective reinforcement ratio, FRP bars type, and concrete strength significantly impacted the flexural bearing capacity and deformation performance of hybrid‐RC beams. Increasing the strength of concrete improved the flexural bearing capacity and ductility of hybrid‐RC beams; increasing the effective reinforcement ratio and the elastic modulus of FRP bars increased the flexural bearing capacity of the hybrid‐RC beams but decreased its ductility. In addition, the fitted FRP bars stress, flexural bearing capacity, and ductility calculation formulas can quickly and conveniently predict the flexural bearing capacity and ductility of hybrid‐RC beams.