Rami A. Hawileh

Behavior of reinforced concrete beams strengthened with externally bonded hybrid fiber reinforced polymer systems

Abstract This paper presents an experimental and an analytical investigation of the behavior of Reinforced Concrete (RC) beams strengthened in flexure by means of different combinations of externally bonded hybrid Glass and Carbon Fiber Reinforced Polymer (GFRP/CFRP) sheets. In order to obtain the mechanical properties of the hybrid sheets, multiple tensile coupon tests were conducted. In addition, an experimental program consisting of a control beam and four beams strengthened in flexure with GFRP, CFRP and hybrid FRP sheets was conducted. The series of the RC beams were tested under four point bending to study the flexural effectiveness of the proposed hybrid FRP sheets. The load–deflection response, strain readings at certain locations and associated failure modes of the tested specimens had been recorded. It is observed that the increase in the load capacity of the strengthened beams ranged from 30% to 98% of the un-strengthened control RC beam depending on the combination of the Carbon/Glass sheets. It was also observed that the ductility at failure loads of the beams strengthened with glass and hybrid sheets is higher than that with a single carbon sheet. Hence, the selection of the optimum combination of hybrid sheets can lead to a strengthening material which provides an improved ductility and strength in beam behavior. The load carrying capacity of the tested specimens was then predicted by the ACI 440.2R-08 guidelines. The predicted and measured results were in good agreement, within 5% for the control beam and for beams with one layer of strengthening sheet and between 13% and 17% for beams with two or more layers of hybrid strengthening sheets. Furthermore, an analytical model was developed to predict the load–deflection response of the tested specimens and the results were compared with the measured experimental data. The results showed that the developed analytical model predicted the response of the tested beam specimens with reasonable accuracy.

Modeling and simulation of low-cycle fatigue life of steel reinforcing bars using artificial neural network

This study presents a model for predicting the low-cycle fatigue life of steel reinforcing bars using Artificial Neural Network (ANN). A Radial Basis Function (RBF) artificial neural network topology with two additional hidden layers and four neurons (processing elements) in each of these layers is used. The input parameters for the network are the maximum tensile strain (e s,max ) and the strain ratio (R) and the output of the ANN is the number of cycles to fatigue failure (N f ). Low-cycle fatigue tests were conducted by the authors in a previous study for different types of steel reinforcing bars subjected to different strain amplitudes and at different strain ratios. The data resulted from these tests were used to train and test the ANN. It is observed that the ANN prediction of low-cycle fatigue life of steel reinforcing bars is within ±2 cycles of the experimental results for the majority of the test data. A parametric study had been carried out to investigate the effect of maximum strain and strain ratio on the fatigue life of steel reinforcing bars. It is concluded that both the strain ratio and the maximum strain have significant effect on the low-cycle fatigue life of such bars, especially at low values of maximum strain and their effect should be considered in both analysis and design. Other observations and conclusions were also drawn.

Behavior of Corroded Steel Reinforcing Bars Under Monotonic and Cyclic Loadings.

This paper investigates the monotonic and low-cycle fatigue properties of corroded steel reinforcing bars and compares their characteristics to that of un-corroded ones. Specifically, this paper investigates the effect of corrosion rate on the degradation of monotonic mechanical properties and low-cycle fatigue life of BS4449/2005 Grade B500B steel reinforcing bars. Twenty four samples of Grade B500B bars were corroded in the laboratory by immersing un-corroded steel bar samples in sealed flasks filled with a 10% concentration mixture of sulfuric and nitric acids as an accelerated corrosion substance. Three different corrosion levels were selected in this study, mainly 9–10%, 13–15%, and 19–20% measured as mass loss of un-corroded bar specimens. Monotonic tensile tests were carried out on 8 sample bars and 24 low-cycle fatigue tests were conducted at different strain amplitude mainly, ±4%, ±5% and ±6%. It is observed that the materials yield and ultimate tensile strengths and ductility, in addition to the fatigue life and the total dissipated energy of the steel bars, are reduced with increasing corrosion damage levels. Other conclusions and observations were also drawn.

Thermal-Stress Finite Element Analysis of CFRP Strengthened Concrete Beam Exposed to Top Surface Fire Loading

A detailed 3D time domain transient thermal-stress finite element analysis is performed to study the heat transfer mechanism within a CFRP strengthened reinforced concrete beam for fire conditions initiating at the top of the beam. This loading scenario has not been investigated previously either experimentally or analytically. Accordingly, a reinforced concrete T-beam strengthened with CFRP and fire-tested by other investigators is modeled here to compare the fire rating of top and bottom exposure. The finite element results correlated very well with the experimental measured results for the bottom fire exposure. In addition, the investigation of the top fire exposure yielded important findings on the resistance of concrete beams when subjected to such fire conditions. It is concluded that heating the top surface (slab) of reinforced concrete beams seems to be beneficial in minimizing mid-span deflection.

Experimental investigation of bond-slip behavior of aluminum plates adhesively bonded to concrete

Abstract The main objective of this investigation is to assess the feasibility of using aluminum alloy (AA) plates as externally bonded strengthening material for reinforced concrete members. Consequently, the main aim of this paper is to experimentally investigate the bond stress-slip behavior of AA plates adhesively bonded to concrete surface. In addition, the effect of different AA surface roughness on the bond stress and bond behavior of AA-concrete interface was also investigated. Twelve specimens with six different surface roughnesses were instrumented and tested under single shear. The tested specimens have two bonded lengths – long bonded lengths (75% of prism length) and short bonded length (30% of prism length). It was observed that the bond shear stress, loading capacity, and failure modes vary with AA surface roughness and bonded length. The load capacity and maximum bond stress increased by 143.6 and 342.6%, respectively, for long bonded length (75%) of randomly grinded AA surface compared with those of normal AA surface. Such increase in load capacity and bond stress demonstrated the potential of using AA as externally bonded strengthening material. In addition, the bond-slip behavior of the AA plates was predicted, with reasonable level of accuracy, using existing bond-slip models that were originally developed for fiber-reinforced polymer materials. However, a more elaborate study is warranted to develop bond stress-slip models, specifically, for AA-concrete interface.

Artificial Neural Network Predictions of Fatigue Life of Steel Bars Based on Hysteretic Energy

AbstractThe fatigue life of steel reinforcing bars depends on the energy dissipated during cyclic loading. Steel bars play a major role in energy dissipation in reinforced concrete structures under low-cycle fatigue loading during earthquakes. In this study, seven artificial neural network (ANN) models were developed to predict the fatigue life of steel bars based on energy dissipated in the first cycle (W1), average cycles (WA), and total energy dissipated in all cycles (WT). The ANN-predicted number of reversals to fatigue failure (2Nf) were comparable to the experimentally measured values and also to the values predicted using nonlinear regression (NLR) models. The best overall ANN result was obtained when W1, WA, and WT were used together as input for the ANN with correlation coefficient r=0.985, normalized mean square error (NMSE)=0.0517, and mean absolute percent error (MAPE)=10.8%. When WA was used as a single input, the predicted 2Nf are also relatively accurate. In conclusion, the developed ANN m...

Performance of RC T-Beams Externally Strengthened with CFRP Laminates under Elevated Temperatures

This paper presents a numerical study that investigates the performance of reinforced concrete (RC) T-beams externally strengthened with carbon fibre reinforced polymer (CFRP) plates when subjected to fire loading. A finite element (FE) model is developed and a coupled thermal-stress analysis was performed on a RC beam externally strengthened with a CFRP plate tested by other investigators. The spread of temperature at the CFRP-concrete interface and reinforcing steel, as well as the mid-span deflection response is compared to the measured experimental data. Overall, good agreement between the measured and predicted data is observed. The validated model was then used in an extensive parametric study to further investigate the effect of several parameters on the performance of CFRP externally strengthened RC beams under elevated temperatures. The variables of the parametric study include applying different fire curves and scenarios, different applied live load combinations as well as the effect of using di...

Retrofitting Pre-Cracked RC Beams Using CFRP and Epoxy Injections

The applications of Carbon Fiber Reinforced Polymers (CFRP) in construction have been grown drastically in the last 20 years because of the wide range of advantages and benefits of using CFRP in buildings, bridges and other type of structures. Nowadays, it is used for retrofitting concrete, masonry, steel and timber structures to resist both static and dynamic loads. Since the cost of replacing an existing structure is far more expensive than using FRP materials to strengthen it, CFRP strengthening techniques seem to be cost effective and easy to implement. Numerous experimental and numerical studies have been conducted to investigate the flexural and shear performance of uncracked reinforced concrete (RC) members externally strengthened with CFRP laminates or strips. However, the most practical usage of CFRP is to retrofit sections that had already been cracked and in need of maintenance. The fact that there have been limited studies to investigate the behavior and performance of pre-cracked beams strengthened with CFRP systems necessitated new and further investigations. In this study, the flexural performance of cracked RC beams retrofitted with CFRP plates and epoxy injections are investigated. The results of the cracked beams are compared with two control beams, a virgin un-strengthened beam and an uncracked beam strengthened with a CFRP plate covering 90% of the beam’s span. Load-midspan deflections for these beams were generated and compared. It is observed that the retrofitted cracked beams displayed more strength than the control beam. The results presented herein can aid designers in establishing a better understanding of the flexural performance of pre-cracked beams and how to economically retrofit such structural members.

Flexural Performance of Strengthened RC Beams with CFRP Laminates Subjected to Cyclic Loading

Seismic retrofitting of reinforced concrete (RC) beams by means of carbon fiber reinforced polymer (CFRP) composites is one of the state-of-the-art techniques that have been widely practiced lately. Such external strengthening schemes seem to enhance both stiffness and strength of RC beams when subjected to static and cyclic loading. Extensive research investigation has been carried out for beams subjected to monotonic static loading while limited research data is available for beams subjected to cyclic loadings. Therefore, this study is initiated and its aim is to present the results of full scale experimental testing of RC beams under four-point-bending loading and subjected to monotonic and cyclic loading histories up to failure of the specimens. An unstrengthened RC beam was tested monotonically to serve as a bench-mark. The remaining two externally strengthened RC beams with different anchorage schemes were tested under cyclic loading. The strengthening test matrix included beams bonded with a unidirectional CFRP plate that covers 90% of the beams soffit length, with one or two unidirectional layers of CFRP wraps at anchorage locations along the beams length. The anchorage locations were at the edges of the CFRP plate and at the middle of the beams span. The results presented herein show an increase in the overall strength for the strengthened beams over the unstrengthened ones. The different failure modes and the resulting ductility of the tested specimens are also discussed. This study is considered to be the first part of an extensive program that aims to investigate the different parameters that govern the external strengthening techniques of RC beams when subjected to cyclic loading.

Prediction of FRP-concrete ultimate bond strength using Artificial Neural Network

The ultimate bond strength between Fiber Reinforced Polymers (FRP) and concrete is one of the most important elements in the performance of the strengthened beam and its failure mode and failure mechanism. In this investigation an Artificial Neural Network (ANN) model has been developed to predict the ultimate bond strength (Pu) between FRP and concrete based on several factors that influence it. These factors, which were used as input to the ANN, include concrete prism width (bc), concrete compressive strength (fcu), concrete tensile strength (ft) as well as the FRP thickness (tf), width (bf), tensile strength (ff), elastic modulus (Ef) and the bond length (L) between FRP and concrete. The ANN predicted ultimate strength loads were compared with experimental values. It is concluded that the ultimate bond strength predicted by the ANN model are reasonably accurate compared to the experimental values and the accuracy can be further improved by using sufficient data generated by similar standardized tests. Based on the developed model, a parametric study can be carried out to investigate the influence of several parameters on the ultimate bond-strength between FRP and concrete and on the behaviour of bond slip compared to existing models.