In this investigation, Elman neural networks were utilized for predicting the mechanical properties of Self-Compacting Concretes (SCCs). Elman models were designed by using experimental data of many different concrete mixdesigns of various types of SCC that were collected from the literature. In order to investigate the effectiveness of the selected input variables on the network performance in predicting intended properties, utilized data in artificial neural networks were considered in two sets of 8 and 140 input variables. The obtained outcomes showed that not only can the developed Elman ANNs predict the mechanical properties of SCCs with high accuracy, but also for all of the desired outputs, networks with 140 inputs, compared to ones with 8, have a remarkable percent improvement in the obtained prediction results. The prediction accuracy can significantly be improved by using a more complete and accurate set of key factors affecting the desired outputs, as input variables, in the networks, which is leading to more similarity of the predicted results gained from networks to experimental results.

In this study, 3D Meso-scale finite-element model is presented to study the mechanical behavior of steel microfiber-reinforced polymer concrete considering the random distribution of fibers in the matrix. The composite comprises two separate parts which are the polymer composite and steel microfibers. The polymer composite is assumed to be homogeneous, which its mechanical properties are measured by performing experimental tests. The steel microfiber-polymer bonding is simulated with the Cohesive Zone Model (CZM) to offer more-realistic assumptions. The CZM parameters are obtained by calibrating the numerical model using the results of the experimental pullout tests on an individual microfiber. The accuracy of the results is validated by comparing the obtained results with the corresponding values attained from testing the steel microfiber-reinforced polymer concrete incorporating 0, 1 and 2% by volume of microfibers, which indicates the excellent accuracy of the current proposed model. The results show that the microfiber aspect ratio has a considerable effect on the mechanical properties of the reinforced polymer concrete. Applying microfibers with a higher aspect ratio improves the mechanical properties of the composite considerably especially when the first crack appears in the polymer concrete specimens.

Design equations to evaluate the bursting force in a post-tensioned anchorage zone have been introduced in many design codes, and one equation in AASHTO LRFD is widely used. However, this equation may not determine the bursting force exactly because it was designed on the basis of two-dimensional numerical analyses without considering various design parameters such as the duct hole and shape of the bearing plate. To improve the design equation, modification of the AASHTO LRFD design equation was considered. The behavior of the anchorage zone was investigated using three-dimensional linear elastic finite element analysis with design parameters such as bearing plate size and diameter of sheath hole. Upon the suggestion of a modified design equation for evaluating the bursting force in an anchorage block with a rectangular anchorage plate (Kim and Kwak 2018), additional influences of design parameters that could affect the evaluation of bursting force were investigated. An improved equation was introduced for determining the bursting force in an anchorage block with a circular anchorage plate, using the same procedure introduced in the design equation for an anchorage block with a rectangular anchorage plate. The validity of the introduced design equation was confirmed by comparison with AASHTO LRFD.

PLC and its expansion module, electric ball valve and cooling pipe, electric heating steel plate and various components of the system, which is used to control test and process data. By automatically adjusting the opening of the valve, the system makes the top temperature and cooling speed develop along the ideal temperature diachronic curve. Moreover, the system enables the temperature difference between inside and surface of test block limited in a given range by automatically controlling the surface board heating. The method of physical simulation test by sandbox with built-in cooling water pipe and heating rod is adopted. On the premise of a given standard value, the operation of the system is checked under different working conditions. Further, an extension of this system is proposed, which enables its application to obtain some thermal parameters when cooperating with numerical simulation.

In this paper, dynamic stress, strain and deflection analysis of concrete pipes conveying nanoparticles-water under the seismic load are studied. The pipe is buried in the soil which is modeled by spring and damper elements. The Navier-Stokes equation is used for obtaining the force induced by the fluid and the mixture rule is utilized for considering the effect of nanoparticles. Based on refined two variables shear deformation theory of shells, the pipe is simulated and the equations of motion are derived based on energy method. The Galerkin and Newmark methods are utilized for calculating the dynamic stress, strain and deflection of the concrete pipe. The influences of internal fluid, nanoparticles volume percent, soil medium and damping of it as well as length to diameter ratio of the pipe are shown on the dynamic stress, strain and displacement of the pipe. The results show that with enhancing the nanoparticles volume percent, the dynamic stress, strain and deflection decrease.

Today, concrete remains the most important, durable, and reliable material that has been used in the construction sector, making it the most commonly used material after water. However, cement continues to exert many negative effects on the environment, including the production of carbon dioxide (CO2), which pollutes the atmosphere. Cement production is costly, and it also consumes energy and natural non- renewable resources, which are critical for sustainability. These factors represent the motivation for researchers to examine the various alternatives that can reduce the effects on the environment, natural resources, and energy consumption and enhance the mechanical properties of concrete. Geopolymer is one alternative that has been investigated; this can be produced using aluminosilicate materials such as low calcium (class F) FA, Ultra-Fine GGBS, and high calcium FA (class C, which are available worldwide as industrial, agricultural byproducts.). It has a high percentage of silica and alumina, which react with alkaline solution (activators). Aluminosilicate gel, which forms as a result of this reaction, is an effective binding material for the concrete. This paper presents an up-to-date review regarding the important engineering properties of geopolymer formed by FA and slag binders; the findings demonstrate that this type of geopolymer could be an adequate alternative to ordinary Portland cement (OPC). Due to the significant positive mechanical properties of slag-FA geopolymer cements and their positive effects on the environment, it represents a material that could potentially be used in the construction industry.

The stability and safety of concrete plug structure of diversion tunnel is crucial for the impoundment of upstream reservoir in hydropower projects. The ongoing Wudongde hydropower plant in China plans to adopt straight column plugs and curved column plugs to replace the traditional expanded wedge-shaped plugs. The performance of the proposed new plug structures under high water head is then a critical issue and attracts the attentions of engineers. This paper firstly studied the joint bearing mechanism of plug and surrounding rock mass and found that the quality and mechanical properties of the interfaces among plug concrete, shotcrete, and surrounding rock mass play a key role in the performance of plug structures. By performing geophysical and mechanical experiments, the contact state and the mechanical parameters of the interfaces were analyzed in detail and provide numerical analysis with rational input parameters. The safety evaluation is carried out through numerical calculation of plug stability under both construction and operation period. The results indicate that the allowable water head acting on columnar plugs is 3.1 to 7.4 times of the designed water head. So the stability of the new plug structure meets the design code requirement. Based on above findings, it is concluded that for the studied project, it is feasible to adopt columnar plugs to replace the traditional expanded wedge-shaped plugs. It is hoped that this study can provide reference for other projects with similar engineering background and problems.

In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, surrogate approaches, such as artificial neural network models, have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the predicted values with the corresponding experimental ones, as well as with available formulas from previous research studies or code provisions highlight the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, for the first time, the (quantitative) values of weights for the proposed neural network model, are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.