Twisted Multi Channel Angular Pressing (TMCAP) as a Novel Severe Plastic Deformation Method

Metals and Materials International - The Twist Multi Channel Angular Pressing (TMCAP) process is presented for the first time to investigate the mechanical properties of AL1050 numerically and...     

High-strength and highly-uniform composite produced by anodizing and accumulative roll bonding processes

The anodizing and accumulative roll bonding (ARB) processes are used in this paper as a new, effective alternative for manufacturing high-strength and highly-uniform aluminum/alumina composites. Four different thicknesses of alumina layers are grown on the substrate using an anodizing process and the microstructural evolution and mechanical properties of the resulting aluminum/alumina composite are investigated. Microscopic investigations of the composite show a uniform distribution of alumina particles in the matrix. It is found that alumina layers produced by the anodizing process neck, fracture, and depart as the number of accumulative roll bonding passes increases. During ARB, it is observed that as strain increases with the number of passes, the strength and elongation of the produced composites correspondingly increase. Also, by increasing alumina quantity, tensile strength improves so that the tensile strength of the Al/3.55 vol.% Al₂O₃ composite becomes ∼3.5 times greater than that of the annealed aluminum used as raw material.     

Effect of drainage channel dimensions on the performance of wave-plate mist eliminators

We investigated the effects of drainage channel dimensions on droplet removal efficiency and pressure drop of the gas droplet flow in a wave-plate mist eliminator. Droplet dispersion in turbulent gas flows is numerically simulated using eddy interaction model (EIM) and Eulerian-Lagrangian method. Reynolds stress transport model (RSTM) with enhanced wall treatment and shear stress transport (SST) k-ω model are used for simulating the turbulent airflow. Comparison between the numerical simulations and available experimental data shows that eddy lifetime constant (C _L ) can affect the results significantly, and by selecting suitable values of the eddy lifetime constant, both turbulence models give reasonable predictions of droplet removal efficiency. Simulations of gas droplet flow in the eliminators with various drainage channel dimensions show that the drainage channel length (L _DC ) has a greater effect on droplet removal efficiency than the drainage channel width (W _DC ).     

Bending load capacity of carbon fiber reinforced concrete beams as a function of fiber performance index (FPI)

Over the past several decades, textile reinforced concrete (TRC) materials have been developed due to their superior mechanical properties, corrosion resistance, lightweight application, and high load-bearing capacity. In this study, the effect of three main factors on bending load capacity of carbon fiber reinforced concrete (CFRC) beams is investigated; the number of reinforcements (carbon-fiber rovings), penetration of the cement within the fibers, and the post-cracking factor. The second and third factors are defined as the fiber performance index (FPI) for evaluating bending load capacity of CFRC beams. The best FPI for a different number of reinforcements was estimated using empirical values of bending load capacity of CFRC beams. The results were indicative of the efficiency and accuracy of the proposed FPI for a wide range of roving numbers, namely 2–24 with 800 tex as the titer. The post-cracking factor was suggested as 2.67 for TRCs and CFRCs materials, which are reinforced by rovings. In order to improve the FPI, the roving was impregnated partially with epoxy, which increased the maximum load capacity and displacement of the beams up to 26.68 and 23.24%, respectively. In addition, the impacts of roving numbers, the first factor, on the failure mode, load-bearing capacity, ductility, and toughness of the CFRC beams were investigated.     

Flexural design of textile-reinforced concrete (TRC) using warp-knitted fabric with improving fiber performance index (FPI)

Bending capacity of textile-reinforced concrete (TRC) is often limited by low penetration of the concrete into inner filaments of fabric rovings. To improve this limitation, we used warp-knitted fabric with different rovings as weft inserted then introduce a fibers performance index (FPI) as sign of the textile reinforcing efficiency. On the base of equilibrium condition models and comparing with experimental data, the FPI is simulated. The influence of different number of rovings and also different layers, on the maximum load, displacement, toughness, and failure modes is discussed. Furthermore, the FPI was improved by partially impregnated fabrics with spotted epoxy. This technique considerably increased FPI from 0.21 for the fabric without epoxy to 0.5 and improved bending properties of TRC.     

Optimal placement and sizing of PV systems and electric parking lots considering reactive power capability and load variation

Power systems should operate in reliable, stable, and efficient conditions. Addition of new generation units or loads to the power systems may change their performance. Therefore, appropriate decisions should be made to manage these elements to improve the power system performance. In this study, optimal placement and sizing of photovoltaic systems and electric parking lots (EPLs) are studied considering the reactive power capability of the inverters and load variation in a 24-h period. For the EPL, a proper charge/discharge scheme (CDS) is initially proposed to flatten the daily load profile; then the EPL with the associated CDS is considered to find its optimal location. Voltage profile, energy losses, bus, and line voltage stability are considered as the objectives of the problem. Genetic algorithm and backward–forward power flow method are utilised to solve the problem considering the IEEE 33-bus system. The results show that all objectives are improved utilising the proposed method.     

Failure mode and interface chemistry of localized coatings on brass

The behaviour of partly coated aluminium brass has been examined under accelerated laboratory and under natural conditions. Acrylic (Incralac) coatings are found to have a good life and to provide a long-term protection of brass surfaces. Analysis of failed interfaces by photoelectron spectroscopy showed that acidic conditions developed beneath the coating and contributed to a partial weakening of the bond strength. Eventually the crevice conditions drift back towards neutral and there is little further loss of strength.     

Exact solution for thermoelastoplastic behavior of thick-walled functionally graded sphere under combined pressure and temperature gradient loading

Considering the combined uniform pressure and thermal loading condition, a closed form analytical thermoelastoplastic solution for thick-walled spheres made of functionally graded materials (FGMs) is presented in this article. Taking into account three different scenarios for the onset of yielding, the formulas to determine stress field in both elastic and plastic zones of FG sphere are generated and the radius of the plastic zone is obtained for combined loading. It is shown that the effective stress in the sphere subjected to combined loading decreases significantly when the FG materials are used. Moreover, the FG sphere is simulated entirely using ABAQUS/Explicit software. Based on the good agreement between the results from present theoretical analysis and those from finite element simulation, the accuracy of the present analysis is verified.     

A particle swarm–BFGS algorithm for nonlinear programming problems

This article proposes a hybrid optimization algorithm based on a modified BFGS and particle swarm optimization to solve medium scale nonlinear programs. The hybrid algorithm integrates the modified BFGS into particle swarm optimization to solve augmented Lagrangian penalty function. In doing so, the algorithm launches into a global search over the solution space while keeping a detailed exploration into the neighborhoods. To shed light on the merit of the algorithm, we provide a test bed consisting of 30 test problems to compare our algorithm against two of its variations along with two state-of-the-art nonlinear optimization algorithms. The numerical experiments illustrate that the proposed algorithm makes an effective use of hybrid framework when dealing with nonlinear equality constraints although its convergence cannot be guaranteed.     

Settlement prediction of the rock-socketed piles through a new technique based on gene expression programming

The settlement design of bored piles socketed into rock has received considerable attention. Although many design methods of pile settlement are recommended in the literature, proposing new/practical technique(s) with higher performance prediction is of advantage. A new model based on gene expression programming (GEP) is presented in this paper for predicting the settlement of the rock-socketed pile. To do this, 96 piles socketed in different types of rock (mostly granite) as part of the Klang Valley Mass Rapid Transit project, Malaysia, were studied. In order to propose a predictive model with higher performance prediction, a series of GEP analyses were conducted using the most important factors on pile settlement, i.e. ratio of length in soil layer to length in rock layer, ratio of total length to diameter, uniaxial compressive strength, standard penetration test and ultimate bearing capacity. For comparison purpose, using the same dataset, linear multiple regression (LMR) technique was also performed. After developing the equations, their prediction performances were checked through several performance indices. The results demonstrated the feasibility of GEP-based predictive model of settlement. Coefficients of determination (CoD) values of 0.872 and 0.861 for training and testing datasets of GEP equation, respectively, show superiority of this model in predicting pile settlement while these values were obtained as 0.835 and 0.751 for the LMR model. Moreover, root mean square error (RMSE) values of (1.293 and 1.656 for training and testing) and (1.737 and 1.767 for training and testing) were achieved for the developed GEP and LMR models, respectively.