Natural pozzolans are used as additives in cement to develop more durable and high-performance concrete. Pozzolanic activity index (PAI) is important for assessing the performance of a pozzolan as a binding material and has an important effect on the compressive strength, permeability, and chemical durability of concrete mixtures. However, the determining of the 28 days (short term) and 90 days (long term) PAI of concrete mixtures is a time-consuming process. In this study, to reduce extensive experimental work, it is aimed to predict the short term and long term PAIs as a function of the chemical compositions of various natural pozzolans. For this purpose, the chemical compositions of various natural pozzolans from Central Anatolia were determined with X-ray fluorescence spectroscopy. The mortar samples were prepared with the natural pozzolans and then, the short term and the long term PAIs were calculated based on compressive strength method. The effect of the natural pozzolans' chemical compositions on the short term and the long term PAIs were evaluated and the PAIs were predicted by using multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) model. The prediction model results show that both reactive SiO₂ and SiO₂+Al₂O₃+Fe₂O₃ contents are the most effective parameters on PAI. According to the performance of prediction models determined with metrics such as root mean squared error (RMSE) and coefficient of correlation (R²), ANFIS models are more feasible than the multiple regression model in predicting the 28 days and 90 days pozzolanic activity. Estimation of PAIs based on the chemical component of natural pozzolana with high-performance prediction models is going to make an important contribution to material engineering applications in terms of selection of favorable natural pozzolana and saving time from tedious test processes.

This study investigates experimentally the impact of magnetized water (MW) on the fresh and hardened characteristics of concrete. Five types of MW are produced using magnetic fields of 1.4 and 1.6 Tesla for treating water with 100, 150, and 250 cycles. The concrete properties are assessed using the slump test, compressive strength test, scanning electron microscopy (SEM) analysis, energy dispersive X-ray analysis (EDX), and Fourier transform infrared spectrophotometry (FTIR). Furthermore, the chemical-physical characteristics of tap water (TW) and MW are evaluated. The results showed the magnetic field intensity has a significant impact on the magnetization effect; the best magnetizing conditions were found when TW was exposed successively to magnetic fields of 1.6 T and 1.4 T for 150 cycles. In addition, 150 MW cycles can be used to improve the compressive strength and workability of concrete by 40% and 17%, respectively. pH, total dissolved solids, and electrical conductivity improved by 15%, 17%, and 7%, respectively, when using MW. Additionally, MW can be used to enhance cement hydration chemical processes and made concrete's structure denser.

The influence of material composition such as aggregate types, addition of supplementary cementitious materials as well as exposed temperature levels have significant impacts on concrete residual mechanical strength properties when exposed to elevated temperature. This study is based on data obtained from literature for fly ash blended concrete produced with natural and recycled concrete aggregates to efficiently develop prediction models for estimating its residual compressive strength after exposure to high temperatures. To achieve this, an extensive database that contains different mix proportions of fly ash blended concrete was gathered from published articles. The specific design variables considered were percentage replacement level of Recycled Concrete Aggregate (RCA) in the mix, fly ash content (FA), Water to Binder Ratio (W/B), and exposed Temperature level. Thereafter, a simplified mathematical equation for the prediction of concrete's residual compressive strength using Gene Expression Programming (GEP) was developed. The relative importance of each variable on the model outputs was also determined through global sensitivity analysis. The GEP model performance was validated using different statistical fitness formulas including R², MSE, RMSE, RAE, and MAE in which high R² values above 0.9 are obtained in both the training and validation phase. The low measured errors (e.g., mean square error and mean absolute error are in the range of 0.0160 - 0.0327 and 0.0912 - 0.1281 MPa, respectively) in the developed model also indicate high efficiency and accuracy of the model in predicting the residual compressive strength of fly ash blended concrete exposed to elevated temperatures.

To fully understand shear mechanisms and composite effects of circular concrete-filled steel tube (CFST) columns, systematic numerical investigations were conducted in this paper by improved finite element models. The triaxial plastic-damage constitutive model of the concrete and the interactions between the concrete and steel tube were considered. Afterwards, the critical and upper bound shear span ratios of the circular CFST column under lateral shear loading were determined. The composite effects between the two materials were analyzed by comparing the shear resistance with plain concrete column and hollow steel tube. In addition, a method that predicts the shear bearing capacity of a circular CFST column was proposed. The confining effects on the concrete core and the restraining effects on the steel tube were considered in this method. The proposed formula can predict more accurate results than the methods in different codes and references.

This article investigates the statically analysis regarding the thermal buckling behavior of a nonuniform small-scale nanobeam made of functionally graded material based on classic beam theories along with the nonlocal Eringen elasticity. The material distribution of functionally graded structures is composed of temperature-dependent ceramic and metal phases in axial and thickness directions, called two-dimensional functionally graded (2D-FG). The partial differential (PD) formulations and end conditions are extracted by using to the conservation energy method. The porosity voids are assumed in the nonuniform functionally graded (FG) structure. The thermal loads are in the axial direction of the beam. The extracted nonlocal PD equations are also solved by employing generalized differential quadrature method (GDQM). Last but not least, the information acquired is used to produce miniature sensors, providing a unique perspective on the growth of nanoelectromechanical systems (NEMS).

This paper presents an investigation of variables that cause spurious cracking in numerical modeling of concrete fracture. Spurious cracks appear due to the approximate nature of numerical modeling. They overestimate the dissipated energy, leading to divergent results with mesh refinement. This paper is limited to quasi-static loading regime, homogeneous models, cracking as the only nonlinear mode of deformation and cracking only due to tensile loading. Under these conditions, some variables that can be related to spurious cracking are: mesh alignment, ductility, crack band width, structure size, mesh refinement and load increment size. Case studies illustrate the effect of each variable and convergence analyses demonstrate that, after all, load-increment size is the most important variable. Theoretically, a sufficiently small load increment is able to eliminate or at least alleviate the detrimental influence of the other variables. Such load-increment size might be prohibitively small, rendering the simulation unfeasible. Hence, this paper proposes two alternatives. First, it is proposed an algorithm that automatically find such small load increment size automatically, which not necessarily avoid large computations. Then, it is proposed a double simulation technique, in which the crack is forced to propagate through the localization zone.

Face gear transmission is widely used in aerospace shunt-confluence transmission system. Tooth wear is one of the main factors affecting its bearing transmission performance. Furthermore, the installation errors of face gear are inevitable. In order to study the wear mechanism of face gear tooth surface with installation errors, based on tooth contact analysis numerical method and Archard wear theory, the UMESHMOTION subroutine in ABAQUS is developed.Combining with Arbitrary Lagrangian-Eulerian adaptive mesh technology, the finite element mesh wear model of abraded face gear pair is established.The preprocessing conditions are set to generate the inp files.Then,the inp files for each corner are imported and batch processed in ABAQUS.The loading tooth contact problem at each rotation angle is solved and the load distribution coefficient among gear tooth, tooth root bending stress, tooth surface contact stress and loaded transmission error are obtained. Results show that the tooth root wear is the most serious and the wear at the pitch cone is close to 0.The wear law of tooth surface along tooth width direction is convex parabola and the wear law along tooth height direction is concave parabola.