This paper describes an experimental study of the cyclic performance of concrete beams reinforced with CFRP prestressed concrete prisms (PCP). The failure modes, hysteretic loops, skeleton curve, ductility, energy dissipation capacity and stiffness degradation of concrete beams reinforced with CFRP prestressed concrete prisms were analyzed. The results show that The CFRP prestressed prisms reinforced concrete beams have good seismic performance. The level of effective prestress and cross section of CFRP prestressed prisms had a little influence on the bearing capacity, the ductility and energy dissipation capacity of CFRP prestressed prisms reinforced concrete beams.

During the last two decades, CFRP have been extensively used for repair and rehabilitation of existing structures as well as in new construction applications. For rehabilitation purposes CFRP are currently used to increase the load and the energy absorption capacities and also the shear strength of concrete columns. Thus, the effect of CFRP confinement on the strength and deformation capacity of concrete columns has been extensively studied. However, the majority of such studies consider empirical relationships based on correlation analysis due to the fact that until today there is no general law describing such a hugely complex phenomenon. Moreover, these studies have been focused on the performance of circular cross section columns and the data available for square or rectangular cross sections are still scarce. Therefore, the existing relationships may not be sufficiently accurate to provide satisfactory results. That is why intelligent models with the ability to learn from examples can and must be tested, trying to evaluate their accuracy for composite compressive strength prediction. In this study the forecasting of wrapped CFRP confined concrete strength was carried out using different Data Mining techniques to predict CFRP confined concrete compressive strength taking into account the specimens' cross section: circular or rectangular. Based on the results obtained, CFRP confined concrete compressive strength can be accurately predicted for circular cross sections using SVM with five and six input parameters without spending too much time. The results for rectangular sections were not as good as those obtained for circular sections. It seems that the prediction can only be obtained with reasonable accuracy for certain values of the lateral confinement coefficient due to less efficiency of lateral confinement for rectangular cross sections.

Epoxy-coated reinforcing bars are widely used to protect the corrosion of the reinforcing bars in the RC elements under their in-service environments and external loads. In most field surveys, it was reported that the corrosion resistance of the epoxy-coated reinforcing bars is typically better than the uncoated bars. However, from the experimental tests conducted in the labs, it was reported that, under the same loads, the RC elements with epoxy-coated reinforcing bars had wider cracks than the elements reinforced with the ordinary bars. Although this conclusion may be true considering the bond reduction of the reinforcing bar due to the epoxy coating, the maximum service loads used in the experimental research may be a main reason. To answer these two phenomena, service performance of 15 RC beam specimens with uncoated and epoxy-coated reinforcements under different fatigue loads was experimentally studied. Influences of different coating thicknesses of the reinforcing bars, the fatigue load range and load upper limit as well as fatigue load cycles on the mechanical performance of RC test specimens are discussed. It is concluded that, for the test specimens subjected to the comparatively lower load range and load upper limit, adverse effect on the service performance of test specimens with thicker epoxy-coated reinforcing bars is negligible. With the increments of the coating thickness and the in-service loading level, i.e., fatigue load range, load upper limit and fatigue cycles, the adverse factor resulting from the thicker coating becomes noticeable.

The aim of this study is to investigate the pH threshold value for the corrosion of steel reinforcement in concrete. A method was designed to attain the pH value of the pore solution on the location of the steel in concrete. Then the pH values of the pore solution on the location of steel in concrete were changed by exposing the samples to the environment (CO25%, RH 40%) to accelerate carbonation with different periods. Based on this, the pH threshold value for the corrosion of steel reinforcement had been examined by the methods of half-cell potential and electrochemical impedance spectra (EIS). The results have indicated that the pH threshold value for the initial corrosion of steel reinforcement in concrete was 11.21. However, in the carbonated concrete, agreement among whether steel corrosion was initiatory determined by the detection methods mentioned above could be found.

In this paper, a finite element model (FEM) in ATENA-3D software was constructed to investigate the behavior of circular ultra high performance concrete (UHPC) filled steel tube stub columns (UHPC-FSTCs) under concentric loading on concrete core. The "CC3DNonLinCementitious2User" material type for concrete in ATENA-3D software with some modifications of material laws, was adopted to model for UHPC core with consideration the confinement effect. The experimental results obtained from Schneider (2006) were then employed to verify the accuracy of FEM. Extensive parametric analysis was also conducted to examine the influence of concrete compressive strength, steel tube thickness and steel yield strength on the compressive behavior of short circular UHPC-FSTCs. It can be observed that the columns with thicker steel tube show better strength and ductility, the sudden drop of load after initial peak load can be prevented. Based on the regression analysis of the results from parametric study, simplified formulae for predicting ultimate loads and strains were proposed and verified by comparing with previous analytical models, design codes and experimental results.

The aim of this study is to build Machine Learning models to evaluate the effect of blast furnace slag (BFS) and waste tire rubber powder (WTRP) on the compressive strength of cement mortars. In order to develop these models, 12 different mixes with 288 specimens of the 2, 7, 28, and 90 days compressive strength experimental results of cement mortars containing BFS, WTRP and BFS+WTRP were used in training and testing by Random Forest, Ada Boost, SVM and Bayes classifier machine learning models, which implement standard cement tests. The machine learning models were trained with 288 data that acquired from experimental results. The models had four input parameters that cover the amount of Portland cement, BFS, WTRP and sample ages. Furthermore, it had one output parameter which is compressive strength of cement mortars. Experimental observations from compressive strength tests were compared with predictions of machine learning methods. In order to do predictive experimentation, we exploit R programming language and corresponding packages. During experimentation on the dataset, Random Forest, Ada Boost and SVM models have produced notable good outputs with higher coefficients of determination of R2, RMS and MAPE. Among the machine learning algorithms, Ada Boost presented the best R2, RMS and MAPE values, which are 0.9831, 5.2425 and 0.1105, respectively. As a result, in the model, the testing results indicated that experimental data can be estimated to a notable close extent by the model.

A large number of residential buildings in regions subjected to severe earthquakes do not have enough load carrying capacity. The most of them have been constructed without receiving any structural engineering attention. It is practically almost impossible to perform detailed experimental evaluation and analytical analysis for each building to determine their seismic vulnerability, because of time and cost constraints. This fact points to a need for a simple evaluation method that focuses on selection of buildings which do not have the life safety performance level by adopting the main requirements given in the seismic codes. This paper deals with seismic assessment of existing reinforced concrete residential buildings and contains an alternative simplified procedure for seismic evaluation of buildings. Accuracy of the proposed procedure is examined by taking into account existing 250 buildings. When the results of the proposed procedure are compared with those of the detailed analyses, it can be seen that the results are quite compatible. It is seen that the accuracy of the proposed procedure is about 80% according to the detailed analysis results of existing buildings. This accuracy percentage indicates that the proposed procedure in this paper can be easily applied to existing buildings to predict their seismic performance level as a first approach before implementing the detailed and complex analyses.

Maximum deflection in a beam is a serviceability design criterion and occurs generally at or close to the mid-span. This paper presents a methodology using neural networks for rapid prediction of mid-span deflections in reinforced concrete beams subjected to service load. The closed form expressions are further obtained from the trained neural networks. The closed form expressions take into account cracking in concrete at in-span and at near the interior supports and tension stiffening effect. The expressions predict the inelastic deflections (incorporating the concrete cracking) from the elastic moments and the elastic deflections (neglecting the concrete cracking). Five separate neural networks are trained since these have been postulated to represent all beams having any number of spans. The training, validating, and testing data sets for the neural networks are generated using an analytical-numerical procedure of analysis. The proposed expressions have been verified by comparison with the experimental results reported elsewhere and also by comparison with the finite element method (FEM). The proposed expressions, at minimal input data and minimal computation effort, yield results that are close to FEM results. The expressions can be used in every day design since the errors are found to be small.

A robust finite element based reinforced concrete bridge deck corrosion initiation model is applied for time-dependent probabilistic sensitivity analysis. The model is focused on uncertainties in the governing parameters that include variation of high performance concrete (HPC) diffusion coefficients, concrete cover depth, surface chloride concentration, holidays in reinforcements, coatings and critical chloride threshold level in several steel reinforcements. The corrosion initiation risk is expressed in the form of probability over intended life span of the bridge deck. Conducted study shows the time-dependent sensitivity analysis to evaluate the significance of governing parameters on chloride ingress rate, various steel reinforcement protection and the corrosion initiation likelihood. Results from this probabilistic analysis provide better insight into the effect of input parameters variation on the estimate of the corrosion initiation risk for the design of concrete structures in harsh chloride environments.

Within the context of continuum mechanics, inelastic behaviours of constitutive responses are usually modelled by using phenomenological approaches. Elasto-plastic damage modelling is extensively used for concrete material in the case of progressive strength and stiffness deterioration. In this paper, a review of the main features of elasto-plastic damage modelling is presented for uniaxial stress-strain relationship. It has been reported in literature that the influence of Alkali-Silica Reaction (ASR) can lead to severe degradations in the modulus of elasticity and compression strength of the concrete material. In order to incorporate the effects of ASR related degradation, in this paper the constitutive model of concrete is based on the coupled damage-plasticity approach where degradation in concrete properties can be captured by adjusting the yield and damage criteria as well as the hardening moduli related parameters within the model. These parameters are adjusted according to results of concrete behaviour from the literature. The effect of ASR on the dynamic behaviour of a beam and a column are illustrated under moving load and cyclic load cases.

In this study, vibration and stability of concrete pipes reinforced with carbon nanotubes (CNTs) conveying fluid are presented. Due to the existence of CNTs, the structure is subjected to magnetic field. The radial fore induced with fluid is calculated using Navier-Stokes equations. Characteristics of the equivalent composite are determined using Mori-Tanaka model. The concrete pipe is simulated with classical cylindrical shell model. Employing energy method and Hamilton's principal, the motion equations are derived. Frequency and critical fluid velocity of structure are obtained analytically based on Navier method for simply supported boundary conditions at both ends of the pipe. The effects of fluid, volume percent of CNTs, magnetic field and geometrical parameters are shown on the frequency and critical fluid velocity of system. Results show that with increasing volume percent of CNTs, the frequency and critical fluid velocity of concrete pipe are increased.

In this paper, nonlinear vibration of embedded nanocomposite concrete is investigated based on Timoshenko beam model. The beam is reinforced by with agglomerated silicon dioxide (SiO2) nanoparticles. Mori-Tanaka model is used for considering agglomeration effects and calculating the equivalent characteristics of the structure. The surrounding foundation is simulated with Pasternak medium. Energy method and Hamilton's principal are used for deriving the motion equations. Differential quadrature method (DQM) is applied in order to obtain the frequency of structure. The effects of different parameters such as volume percent of SiO2 nanoparticles, nanoparticles agglomeration, elastic medium, boundary conditions and geometrical parameters of beam are shown on the frequency of system. Numerical results indicate that with increasing the SiO2 nanoparticles, the frequency of structure increases. In addition, considering agglomeration effects leads to decrease in frequency of system.