Due to higher stiffness to weight, higher corrosion resistance, higher strength to weight ratios and good durability, concrete composite structures provide many advantages as compared with conventional materials. Thus, they have wide applications in the field of concrete construction. This research focuses on the structural behavior of steel-tube CFRP confined concrete (STCCC) columns under axial concentric loading. A nonlinear finite element analysis (NLFEA) model of STCCC columns was simulated using ABAQUS which was then, calibrated for different material and geometric models of concrete, steel tube and CFRP material using the experimental results from the literature. The comparative study of the NLFEA predictions and the experimental results indicated that the proposed constitutive NLFEA model can accurately predict the structural performance of STCCC columns. After the calibration of NLFEA model, an extensive parametric study was performed to examine the effects of different critical parameters of composite columns such as; (i) unconfined concrete strength, (ii) number of CFRP layers, (iii) thickness of steel tube and (iv) concrete core diameter, on the axial load capacity. Furthermore, a large database of axial strength of 700 confined concrete compression members was developed from the previous researches to give an analytical model that predicts the ultimate axial strength of composite columns accurately. The comparison of the predictions of the proposed analytical model was done with the predictions of 216 NLFEA models from the parametric study. A close agreement was represented by the predictions of the proposed constitutive NLFEA model and the analytical model.

Artificial neural networks are used as a useful tool in distinct fields of civil engineering these days. In order to control long-term quality of Self-Compacting Semi-Lightweight Concrete (SCSLC), the 90 days compressive strength is considered as a key issue in this paper. In fact, combined artificial neural networks are used to predict the compressive strength of SCSLC at 28 and 90 days. These networks are able to re-establish non-linear and complex relationships straightforwardly. In this study, two types of neural networks, including Radial Basis and Multilayer Perceptron, were used. Four groups of concrete mix designs also were made with two water to cement ratios (W/C) of 0.35 and 0.4, as well as 10% of cement weight was replaced with silica fume in half of the mixes, and different amounts of superplasticizer were used. With the help of rheology test and compressive strength results at 7 and 14 days as inputs, the neural networks were used to estimate the 28 and 90 days compressive strengths of above-mentioned mixes. It was necessary to add the 14 days compressive strength in the input layer to gain acceptable results for 90 days compressive strength. Then proper neural networks were prepared for each mix, following which four existing networks were combined, and the combinatorial neural network model properly predicted the compressive strength of different mix designs.

In this paper, the shell material has been taken as functionally graded material and their material quantity is located by the exponential volume fraction law. Moreover, the impact of ring supports around the shell circumference has been examined for their various positions along the shell axial length. These rings support restraints the radial displacement in the transverse direction. While the axial modal deformation functions have been estimated by characteristic beam functions and nature of materials used for construction of cylindrical shells. The fundamental natural frequency of cylindrical shell of parameter versus ratios of length- and height-to-radius for a wide range has been reported and investigated through the study. In addition, by increasing height-to-radius ratio resulting frequencies also increase and frequencies decrease on ratio of length-to-radius. Though the trends of frequency values of both ratios are converse to each other with three different boundary conditions. Also it is examined the position of ring supports with length-to radius ratio, height-to-radius ratio and varying the exponent of volume fraction. MATLAB software package has been utilized for extracting shell frequency spectra. The obtained results are confirmed by comparing with available literature.

In this research, the buckling analysis of sandwich beam with composite reinforced by graphene platelets (GPLs) in two face sheets is investigated. Three type various porosity patterns including uniform, symmetric and asymmetric are considered through the thickness direction of the core. Also, the top and bottom face sheets layers are considered composite reinforced by GPLs/CNTs based on Halpin-Tsai micromechanics model and extended mixture rule, respectively. Based on various shear deformation theories such as Euler-Bernoulli, Timoshenko and Reddy beam theories, the governing equations of equilibrium using minimum total potential energy are obtained. It is seen that the critical buckling load decreases with an increase in the porous coefficient, because the stiffness of sandwich beam reduces. Also, it is shown that the critical buckling load for asymmetric distribution is lower than the other cases. It can see that the effect of graphene platelets on the critical buckling load is higher than carbon nanotubes. Moreover, it is seen that the difference between carbon nanotubes and graphene platelets for Reddy and Euler-Bernoulli beam theories is most and least, respectively.

A method is proposed in this paper to estimate the workability of self-compacting concrete (SCC) in different mixing conditions with different mixers and mixing volumes by recording the mixing process based on deep learning (DL). The SCC mixing videos were transformed into a series of image sequences to fit the DL model to predict the SF and VF values of SCC, with four groups in total and approximately thirty thousand image sequence samples. The workability of three groups SCC whose mixing conditions were learned by the DL model, was estimated. One additionally collected group of the SCC whose mixing condition was not learned, was also predicted. The results indicate that whether the SCC mixing condition is included in the training set and learned by the model, the trained model can estimate SCC with different workability effectively at the same time. Our goal to estimate SCC workability in different mixing conditions is achieved.

This paper deals with the characteristics of reinforcement corrosion in concrete beams under the influence of sustained loads. The evolution and distribution laws of the reinforcement corrosion were measured periodically over time. The results show that sustained load exhibits a pronounced exacerbating effect on the reinforcement corrosion, and enlarges the nonuniformity level of corrosion as the load level increases. Accompanied with the continuous formation of the rust, the corrosion rate was also observed to be highly nonlinear and time-dependent. Moreover, to visually and quantitatively analyze the distribution of reinforcement corrosion, the 3D scanning technology combined with the probability statistics analysis was adopted, and the observed nonuniformity can be well described by the Gumbel distribution. Finally, an approach based on the three-phase spherical model was proposed to estimate the reinforcement corrosion, taking account of the effects of sustained load on the changes of concrete porosity and oxygen diffusivity.

This paper presents a numerical study on structural behavior of hammer head pier cap beams, extended on verges and reinforced with carbon fiber reinforced polymer (CFRP) plates. A 3-D finite element (FE) model along with a simplified analytical model are presented. Concrete damage plasticity (CDP) was adapted in the FE model and an analytical approach predicting the CFRP anchor strength was adapted in both FE and analytical model. Total five quarter-scaled pier cap beams with various CFRP reinforcing schemes were experimentally tested and analyzed with numerical approaches. Comparison between experimental results, FE results, analytical results and current ACI guideline predictions was presented. The FE results showed good agreement with experimental results in terms of failure mode, ultimate capacity, load-displacement response and strain distribution. In addition, the proposed strut-and-tie based analytical model provides the most accurate prediction of ultimate strength of extended cap beams among the three numerical approaches.

In this work, the analytical solution for the stresses in piezo-thermo-elastic homogeneous, transversely isotropic material under the effect of the rotation has investigated. The thermoelasticity theory has used to study the problem. The material subjected to boundary conditions. Finally, the numerical solution has carried out piezo - thermo-elastic material under the effect of rotation, to illustrate the analytical development. The corresponding simulated results of various physical quantities such as the displacements and the stresses, the temperature and the electrical displacement have presented graphically.

This work performed to analyses the impact of hooked end steel fibres on the mechanical properties of high performance concrete. The mechanical properties considered incorporate compressive strength, split tensile strength and flexural strength. Taking in to thought parameters, such as, volume fraction of fibres, fibre aspect ratio and grade of concrete, a logical strategy called Taguchi technique was utilized to discover the ideal blend of factors. L9 Orthogonal Array (OA) of Taguchi network comprising of three variables and three dimensions is utilized in this work. The evaluations of concrete considered were M60, M80 and M100. M60 contained 15% of metakaolin as bond swap though for M80 it was 5% of metakaolin and for M100 it was 10% metakaolin and 10% of silica smolder. The volume portion of fiber was fluctuated by 0.5%; 1% and 1.5% and the viewpoints proportions considered were 50, 60 and 80. The test outcomes demonstrate that incorporation of steel fibres enhance significantly the the strength characteristics of concrete, predominantly the splitting tensile strength and flexural strength. In light of relapse investigation of the test information scientific models were produced for compressive strength, split tensile strength and flexural strength of the steel fibre-reinforced high performance concrete.