Effect of Melt Cleanliness on the Mechanical Properties and Microstructure on AZ91E Mg Alloy Castings

The current study examines various filter configurations, argon bubbling, and degasser addition to improve melt cleanliness of AZ91E permanent mold castings. The unfiltered castings had an average yield strength, ultimate tensile strength, and elongation of 93.3, 153.3 MPa, and 2.2% respectively. Using a fine mesh filter within the well of the mold, the ultimate tensile strength and elongation increased by 9 and 41%, respectively, compared to the unfiltered samples. A combination of a fine filter and argon bubbling resulted in an average increase in ultimate tensile strength and elongation of 29 and 123%, respectively, that matched the performance of the C₂Cl₆-based degassed castings with 95.8, 194.3, and 4.9% for yield strength, ultimate tensile strength, and elongation, respectively. The addition of the C₂Cl₆-based degasser released harmful vapors that can be avoided using the fine filter with argon bubbling. In all cases, the removal of MgO-based inclusions improved mechanical properties.     

The electroremoval of copper from dilute waste solutions using Swiss-roll electrode cell

Copper is usually present in concentrations less than 5 g/L⁻¹ in dilute waste solutions. The low concentrations make these solutions unsuitable for the electro-flow owinning processes via conventional electrolysis cells. Unconventional, two-and three-dimensional electrode cells with relatively large cathodic area are essential for such treatment. Different types of cells are mentioned in the literature. Among these cells, the two-dimensional Swiss-roll cell (SR) is considered in this study. The effects of cathodic current densities, initial copper concentrations, free sulfuric acid concentration, the presence of iron and zinc cations, and the rate of flow of the solution on both the cathodic current efficiency and power consumption were studied. Copper was removed from synthetic and industrial mixtures of Cu/Fe/Zn sulfate solutions to less than 5 ppm with power consumptions of 10.326 kWh/kg⁻¹ and 8.61 kWh/kg⁻¹, respectively. The correlation between the SR cell and packed-column cell on such treatment was also considered.     

A constraint consensus memetic algorithm for solving constrained optimization problems

Constraint handling is an important aspect of evolutionary constrained optimization. Currently, the mechanism used for constraint handling with evolutionary algorithms mainly assists the selection process, but not the actual search process. In this article, first a genetic algorithm is combined with a class of search methods, known as constraint consensus methods, that assist infeasible individuals to move towards the feasible region. This approach is also integrated with a memetic algorithm. The proposed algorithm is tested and analysed by solving two sets of standard benchmark problems, and the results are compared with other state-of-the-art algorithms. The comparisons show that the proposed algorithm outperforms other similar algorithms. The algorithm has also been applied to solve a practical economic load dispatch problem, where it also shows superior performance over other algorithms.     

Maximization of Photonic Bandgaps in Two-Dimensional Superconductor Photonic Crystals

In this paper, we investigate the properties of photonic band structures in two-dimensional superconductor photonic crystals (2D-SCPCs) using the frequency dependent plane wave expansion method. We consider two types of 2D-SCPCs, which are composed of superconductor (dielectric) rods embedded into a dielectric (superconductor) background, named type I (type II) SCPCs. We target maximization of the gap-to-mid-gap ratio by varying many parameters, namely, shape of the rods, the operating temperature, the permittivity of the dielectric material, and the threshold frequency of the superconductor. We show that the type II SCPCs have a higher gap-to-mid-gap ratio than the type I SCPCs. In addition, the PBGs can be tuned efficiently by the operating temperature. Moreover, the photonic band structures can be tailored by changing the dielectric constant of the background (rods) in the type I (type II) SCPCs.     

The texture and anisotropy of hot extruded magnesium alloys fabricated via rapid solidification powder metallurgy

Rapid solidification magnesium alloy powders produced by spinning water atomization process were hot extruded into rectangular bars, from which tensile and compression samples have been cut at 0°, 45° and 90° angles from the extrusion direction to study their anisotropy. Electron back-scattered diffraction analysis has been used to investigate the texture evolution during the extrusion process. Texture parameters like the Schmid factor and the intensity of (0 0 0 1) basal plane in the pole figure have been evaluated and correlated to the mechanical properties. Results have shown that the extruded rods exhibited high strength and relatively less anisotropy compared to other previously reported values for wrought magnesium alloys. Tensile and compression yield stresses have shown very similar values to each other at all loading directions. This limited anisotropy could be linked to both the fine grained and inter-metallic-compound-dispersed microstructure of the extruded alloys. Dynamic recrystallization behavior during hot extrusion has also been investigated in the present study.     

Hierarchical scheduling in an intelligent environmental control system

This paper describes the design and implementation of a hierarchical scheduling subsystem and graphical user interface in an intelligent environmental control system. The hierarchical scheduling system is capable of managing all environmental events occurring in widely different time scales as specified by the user. We employ a knowledge representation scheme called a system entity structure to specify the environmental schedules in a hierarchical fashion. A system entity structure called TAL (Timed Action Language) is developed. TAL organizes a family of all possible long-/mid-/short-term schedules from which a specific schedule can be pruned by the user through graphical interface.Research was done while the author was a member of the Environmental Research Lab, University of Arizona. A Preliminary version of the paper was presented at 2nd International Conference on Industrial & Engineering Applications of AI and Expert System [5].     

Bio-film formation on stainless steels Part 2. The role of seasonal changes, seawater composition and surface roughness

Bio-film formation on type 254 SMO stainless steel in Arabian Gulfwater was followed by measuring the variation of the open circuit potentials of test coupons under a variety of conditions. The time-potential curves exhibited two plateaus corresponding to oxide thickening and later to bio film development. The rate of film formation was found to depend on the ambient seawater temperature, which varied with the season. The reduction of the biological activity of the water through additions of pre-boiled and cooled seawater resulted in the retardation of bio-film formation and in the shift of the final steady-state potential towards less positive values. Similar behaviour was obtained when concentrating seawater by the addition of solid salt. The simultaneous reduction of biological activity and of salt content resulted. The characteristics ofthe formed bio-film depend on the nature ofthe metal surfaces. Smooth surfaces allowed the development of thin clear films while thicker dark films formed on coarse rough surfaces. These were usually associated with the growth of worm-like structures, initiating crevice and pitting corrosion.     

Estimation of solar radiation components incident on Helwan site using neural networks

Field testing carried out for solar energy applications is costly, time consuming and depends heavily on prevailing weather conditions. Adequate security and weather protection must be provided at the test site. Measurements may also suffer from delays that can be caused by system failures and bad weather. To overcome these problems the need for accurate model becomes evermore important. To achieve such prediction task, an artificial neural network, ANN, model is regarded as a cost-effective technique superior to traditional statistical methods. In this paper, Levenberg optimization function is adopted to predict insolation data in different spectral bands for Helwan (Egypt) monitoring station. The predicted values were then compared with the actual values and presented in terms of usual statistics. The results hint that, the ANN model predicted infrared, ultraviolet, and global insolation with a good accuracy of approximately 95%, 93% and 96%, respectively. In addition, ANN model was tested to predict the same components for Aswan over an 11 month period. The predicted values of the ANN model compared to the actual values for Aswan produced an accuracy of 95%, 91% and 92%, respectively. Data for Aswan were not included as a part of ANN training set. Hence, these results demonstrate the generalization capability of this approach over unseen data and its ability to produce accurate estimates.     

Packing scheme for mean-filtering of an 8 bit image

Filtering is one of the most well known low-level image processing procedures. In most filtering procedures, the potential capability of an ALU in a processor is not fully used. The authors propose a packed mean filtering scheme. The scheme packs several pixels into a unit and processes them simultaneously. Experiments are held under three distinct machines to evaluate the performance of the scheme. The result shows that the scheme enhances processing speed in all three environments