Statistical analysis has found useful application in the design of experiments (DOE) especially optimization of concrete ingredients however, to be able to apply the concept properly using computer aided applications there has to be an upper and lower limits of responses fed to the system. In this study, the production of high-performance steel fiber concrete (HPSFC) at five different fiber addition levels by volume with two aspect ratios of 60 and 83 were studied under two curing methods completely dry cured (DC) and moist cured (MC) conditions. In other words, this study was carried out for those limits based on material properties available in North Cyprus. Specimens utilized were cubes 100 mm size casted and cured for 28 days and tested for compressive strength. Minitab 18 statistical software was utilized for the analysis of results at a 5 per cent level of significance. Experimentally, it was observed that, there was fluctuation in compressive strength results for the two aspect ratios and curing regimes. On the other hand P-value hypothesis evaluation of the response showed that at the stated level of significance, there was a statistically significant difference between dry and moist curing conditions. Upper and lower limit values were proposed for the response to be utilized in DOE for future studies based on these material properties. It was also suggested that for a narrow confidence interval and accuracy of the system, future study should increase the sample size.

The possibility of earthquakes in vulnerable regions indicates that efficient technique is required for seismic protection of buildings. During the recent decades, the concept is moving towards the insertion of base isolation on seismic prone buildings. So, investigation of structural behavior is a burning topic for buildings to be isolated in base level by bearing device. This study deals with the incorporation of base isolation system and focuses the changes of structural responses for different types of Lead Rubber Bearing (LRB) isolators. A number of sixteen model buildings have been simulated selecting twelve types of bearing systems as well as conventional fixed-base (FB) scheme. The superstructures of the high-rise buildings are represented by finite element assemblage adopting multi-degree of freedoms. Static and dynamic analyses are carried out for FB and base isolated (BI) buildings. The dynamic analysis in finite element package has been performed by the nonlinear time history analysis (THA) based on the site-specific seismic excitation and compared employing eminent earthquakes. The influence of the model type and the alteration in superstructure behavior of the isolated buildings have been duly assessed. The results of the 3D multistory structures show that the lateral forces, displacement, inertia and story accelerations of the superstructure of the seismic prone buildings are significantly reduced due to bearing insertion. The nonlinear dynamic analysis shows 12 to 40% lessening in base shear when LRB is incorporated leading to substantial allowance of horizontal displacement. It is revealed that the LRB isolators might be potential options to diminish the respective floor accelerations, inertia, displacements and base shear whatever the condition coincides. The isolators with lower force intercept but higher isolation period is found to be better for decreasing base shear, floor acceleration and inertia force leading to reduction of structural and non-structural damage. However, LRB with lower isolator period seems to be more effective in dropping displacement at bearing interface aimed at reducing horizontal shift of building structure.

This paper investigates the potential of a hybrid model which combines the least squares support vector machine (LSSVM) and an improved particle swarm optimization (IMPSO) techniques for prediction of concrete compressive strength. A modified PSO algorithm is employed in determining the optimal values of LSSVM parameters to improve the forecasting accuracy. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed IMPSO-LSSVM model. Further, predictions from five models (the IMPSO-LSSVM, PSO-LSSVM, genetic algorithm (GA) based LSSVM, back propagation (BP) neural network, and a statistical model) were compared with the experimental data. The results show that the proposed IMPSO-LSSVM model is a feasible and efficient tool for predicting the concrete compressive strength with high accuracy.

Time dependent strain due to creep is a significant factor in structural design. Multi-gene genetic programming (MGGP) and artificial neural network (ANN) are used to develop two models for prediction of creep compliance in concrete. The first model was developed by MGGP technique and the second model by hybridized MGGP-ANN. In the MGGP-ANN, the ANN is working in parallel with MGGP to predict errors in MGGP model. A total of 187 experimental data sets that contain 4242 data points are filtered from the NU-ITI database. These data are used in developing the MGGP and MGGP-ANN models. These models contain six input variables which are: average compressive strength at 28 days, relative humidity, volume to surface ratio, cement type, age at start of loading and age at the creep measurement. Practical equation based on MGGP was developed. A parametric study carried out with a group of hypothetical data generated among the range of data used to check the generalization ability of MGGP and MGGP-ANN models. To confirm validity of MGGP and MGGP-ANN models; two creep prediction code models (ACI209 and CEB), two empirical models (B3 and GL 2000) are used to compare their results with NU-ITI database.

As a nondestructive testing method, the Schmidt rebound hammer is widely used for structural health monitoring. During application, a Schmidt hammer hits the surface of a concrete mass. According to the principle of rebound, concrete strength depends on the hardness of the concrete energy surface. Study aims to identify the main variables affecting the results of Schmidt rebound hammer reading and consequently the results of structural health monitoring of concrete structures using adaptive neuro-fuzzy inference system (ANFIS). The ANFIS process for variable selection was applied for this purpose. This procedure comprises some methods that determine a subsection of the entire set of detailed factors, which present analytical capability. ANFIS was applied to complete a flexible search. Afterward, this method was applied to conclude how the five main factors (namely, age, silica fume, fine aggregate, coarse aggregate, and water) used in designing concrete mixture influence the Schmidt rebound hammer reading and consequently the structural health monitoring accuracy. Results show that water is considered the most significant parameter of the Schmidt rebound hammer reading. The details of this study are discussed thoroughly.

The slag through sieve #4 replaced the natural fine aggregate in different proportions (0-50%) to make ready-mixed soil and slag (RMSAS). The fresh properties studied, and the concrete specimens were produced to test the hardened properties at different ages. Results showed that the workability of RMSAS decreases when the replacement increases. The unit weight increases with the replacement. The setting time extends when the replacement decreases and shortens when the replacement increases. The compressive strength, ultrasonic pulse velocity and hammer rebound value increase with the replacement. However, the high-replacement results decrease because of the expansion factor at late age. Resistivity is close and less than $20k{\Omega}-cm$. After the industrial of steelmaking by-products are processed properly, they can be used in civil engineering, not only as a substitute for natural resources and to reduce costs, but also to provide environmental protection.

Making a transverse opening in concrete beams in order to accommodate utility services through the member instead of below or above of that, sometimes may be necessary. It is obvious that inclusions of an opening in a beam decreases its flexural and shear strengths. Fabricated steel bars are usually used to increase the capacity of the opening section, but details of reinforcements around the opening are dense and complex resulting in laborious pouring and setup process. The goal of this study was to investigate the possibility of using steel fibers in concrete mixture instead of complex reinforcement detailing order to strengthen opening section. Nonlinear finite element method was employed to investigate the behavior of steel fiber reinforced concrete beams. The numerical models were validated by comparison with experimental measurements tested by other investigators and then used to study the influence of fiber length, fiber aspect ratio and fiber content on the shear performance of SFRC slender beams with opening. Finally, it was concluded that the predicted shear strength enhancement is considerably influenced by use of steel fibers in concrete mixture but the effect of fiber length and fiber aspect ratio wasn't significant.

This paper measures the mechanical response of precast pavement joints under moving axle loads using the finite-element method, and the models were validated with results of field tests. In order to increase the ability to use the non-linear FE analysis for design and assessment of precast pavement subjected to moving axle load, this paper investigated the effects of different load transfer between the slabs using the ABAQUS finite-element package to solve the nonlinear explicit model equations. The assembly of the panels using dowels and groove-tongue keys has been studied to assess the efficiency of keyway joint system. Concrete damage plasticity model was used to calculate the effects of permanent damages related to the failure mechanisms. With aggregate interlock as the only load transferring system, Load transfer efficiency (LTE) is not acceptable when the axle load reaches to slab joints. The Finite-element modelling (FEM) results showed that keyway joints significantly reduced tensile stresses developed at the mid-slab. Increasing the thickness of the tongue the LTE was improved but with increasing the height of the tongue the LTE was decreased. Stresses are transferred to the adjacent slab efficiently when dowels are embedded within the model. When the axle load approaches joints, tensile damage occurs sooner than compressive damage, but the damage rate remains constant, then compressive damage increases significantly and become the major form of distress under the dowels.

In this study alkali activation of Electric Arc Furnace Slag (EAFS) is studied with a comprehensive test program. Three different silicate moduli (1-1,5-2), three different sodium concentrations (4%-6%-8%) for each silicate module, two different curing conditions (45%-98% relative humidity) for each sodium concentration, two different curing temperatures ($400^{\circ}C-800^{\circ}C$) for each relative humidity condition and two different curing time (6h-12h) for each curing temperature variables are selected and their effects on compressive strength was evaluated then regression equations using multiple linear regressions methods are fitted. And then to select the best regression models confirm with using the variables, the regression models compared between itself. An Artificial Neural Network (ANN) models that use silicate moduli, sodium concentration, relative humidity, curing temperature and curing time variables, are formed. After the investigation of these ANN models' results, ANN and multiple linear regressions based models are compared with each other. After that, an explicit formula is developed with values of the ANN model. As a result of this study, the fluctuations of data set of the compressive strength were very well reflected using both of the methods, multiple linear regression with quadratic terms and ANN.

In this study, nonlinear vibration and stability of a polymeric pipe reinforced by single-walled carbon naotubes (SWCNTs) conveying fluid-nanoparticles mixture flow is investigated. The Characteristics of the equivalent composite are determined using Mori-Tanaka model considering agglomeration effects. The surrounding elastic medium is simulated by orthotropic visco-Pasternak medium. Employing nonlinear strains-displacements, stress-strain energy method the governing equations were derived using Hamilton's principal. Differential quadrature method (DQM) is used for obtaining the frequency and critical fluid velocity. The influence of volume percent of SWCNTs, agglomeration, geometrical parameters of pipe, viscoelastic foundation and fluid velocity are shown on the frequency and critical fluid velocity of pipe. Results showed the increasing volume percent of SWCNTs leads to higher frequency and critical fluid velocity.

Today, buildings are exposed to the effects such as explosion and impact loads. Usually, explosion and impact loads that act on the buildings such as nuclear power plants, airports, defense industry and military facilities, can occur occasionally on the normal buildings because of some reasons like drop weight impacts, natural gas system explosions, and terrorist attacks. Therefore, it has become important to examine the behavior of reinforced concrete (RC) structures under impact loading. Development of computational mechanics has facilitated the modeling of such load conditions. In this study, three kinds of RC walls that have different geometric forms (square, ellipse, and circle) and used in guardhouses with same usage area were modeled with Abaqus finite element software. The three configurations were subjected to the same impact energy to determine the geometric form that gives the best behavior under the impact loading. As a result of the analyses, the transverse impact forces and failure modes of RC walls under impact loading were obtained. Circular formed (CF) reinforced concrete wall which has same impact resistance in each direction had more advantages. Nonetheless, in the case of the impact loading occurring in the major axis direction of the ellipse (EF-1), the elliptical formed reinforced concrete wall has higher impact resistance.

A nonlinear finite element modeling approach is developed to assess the behavior of a dowel bar embedded on a single concrete block substrate, subjected to monotonic loading. In this approach, a discrete representation of the steel reinforcing bar is considered, using beam finite elements with nonlinear material behavior. The bar is connected to the concrete embedment through nonlinear Winkler spring elements. This modeling approach can only be used if a new constitutive model is developed for the spring elements, to simulate the deformability and strength of the concrete substrate. To define this constitutive model, an extensive literature review was conducted, as well as 3 experimental tests, in order to select the experimental data which can be used in the calibration of the model. Based on this data, an empirical model was established to predict the global dowel response, for a wide range of bar diameters and concrete strengths. This empirical model provided the information needed for calibration of the nonlinear Winkler spring model, valid for dowel displacements up to 4 mm. This new constitutive model is composed by 5 stages, in order to reproduce the concrete substrate response.