Investigation of Lu effect on YBa2Cu3O7−δ superconducting compounds

This study reports the effect of Lu addition on the microstructural and superconducting properties of YBa₂Lu_xCu₃O_7?δ (Y123) superconducting samples with x = 0, 0.1, 0.3, 0.5 and 0.7 by means of X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM), electron dispersive X-ray (EDX), electrical resistivity and transport critical current density (J_c) measurements. The samples prepared by the liquid ammonium nitrate and derivatives are exposed to various annealing time (20, 40 and 60 h) and temperature (950, 960 and 970 °C), and the best ambient for the sample fabrication is determined to be 970 °C for 20 h. Zero resistivity transition temperatures (T_c), critical current densities (J_c), variation of transition temperatures, hole-carrier concentration, grain size, lattice parameter, surface morphology, element distribution, crystallinity and resistivity (at room temperature) values of the bulk superconducting samples prepared at 970 °C for 20 h are compared with each other. T_c and J_c values of the samples are inferred from the dc resistivity and the critical current measurements, respectively. The results show that the T_c value of the pure sample is about 90.6 K while the sample doped with 0.1 wt% Lu has the maximum T_c value (92.5 K). However, beyond x = 0.1, the T_c value is observed to decrease toward to 83.5 K with increment in the Lu addition. Similarly, the J_c values measured are found to reduce from 142 to 76 A/cm² with the addition. Moreover, XRD measurements show that both pure and Lu-doped samples exhibit the polycrystalline superconducting phase with the changing intensity of diffraction lines and contain Y123 and Y211 phase, confirming the incorporation of Lu atoms into the crystalline structure of the samples studied. At the same time, comparing of the XRD patterns of samples, the intensity ratio of the characteristic (110) and (013) peaks on the sample doped with 0.1 wt% Lu is more than that on the other samples prepared. Additionally, SEM images display that the sample doped with 0.1 wt% Lu obtains the best crystallinity, grain connectivity and largest grain size whereas the worst surface morphology is observed for the maximum doped sample (x = 0.7). Further, EDX results demonstrate that the Lu atoms doped are successfully introduced into the microstructure of the Y123 samples studied and the maximum Cu element level is observed for the sample doped with 0.1 wt%, explaining that why this sample obtains the best superconducting properties compared to others. According to all the results obtained, it is concluded that the 0.1 wt% Lu addition into the Y123 system improves the microstructural and superconducting properties of the samples studied.     

Antimicrobial Activity of Ozone against Pathogenic Oral Microorganisms on Different Denture Base Resins

ABSTRACT

The present study aimed to evaluate the antimicrobial effect of gaseous ozone against specific oral pathogens on denture base resins. 1080 round samples were prepared (10mm-diameter, 2mm-thickness). Candida albicans, Streptococcus mutans, Streptococcus gordonii, and Aggregatibacter actinomycetemcomitans, polyamide-Deflex, heat-cured polymethyl-methacrylate (PMMA)-QC-20, and cold-cured-PMMA-Meliodent. The doses and durations: 25, 50 and 100µg/ml, 5, 10, 20, 30 minutes. For Cell viability (CV) MTT was used. 100µg/ml was most effective dose for C. albicans, S .gordonii, and A. actinomycetemcomitans were in heat-cured-PMMA and polyamide for S.mutans. For polyamide, lowest CV was 43% in S.mutans and A.actinomycetemcomitans. CV of heat-cure and cold-cure PMMA were 31% and 32% in S.gordonii, respectively. CV was similar for all resins and durations in S.mutans and A.actinomycetemcomitans and for polyamide for C.albicans and for heat-cure PMMA for S.gordonii. 30-min ozone application killed 80% of all microorganisms in all resins except for C.albicans in polyamide (65% cell death) and cold-cure PMMA (57% cell death). Optimal dose/duration combination was 100 µg/ml-10 min. Gaseous ozone can be considered as an effective cleansing agent for denture base resins.     

Power generation expansion planning with adaptive simulated annealing genetic algorithm

In this paper, an adaptive simulated annealing genetic algorithm is proposed to solve generation expansion planning of Turkey's power system. Least‐cost planning is a challenging optimization problem due to its large‐scale, long‐term, nonlinear, and discrete nature of power generation unit size. Genetic algorithms have been successfully applied during the past decade, but they show some limitations in large‐scale problems. In this study, simulated annealing is used instead of mutation operator to improve the genetic algorithm. The improved algorithm is applied to the power generation system with seven types of generating units and a 20‐year planning horizon. The planning horizon is divided into four equal periods. The new algorithm provides approximately 6.6 billion US$ (3.2%) cheaper solution than GA and also shows faster convergence. Copyright © 2006 John Wiley & Sons, Ltd.     

Smart shop floor scheduling using knowledge based simulation

In this paper, the need for knowledge-based simulation technique in shop floor scheduling are addressed. A prototype integrated system in Feed Mill manufacturing utilizing an integrated approach of Artificial Intelligence (AI) and simulation is discussed. The system is designed to support the production planner in scheduling and controlling the shop floor on real-time and on-line basis. System overview with the emphasis on knowledge-based simulation module is described.     

Interface crack problems in graded orthotropic media: Analytical and computational approaches

Interface crack problems in graded orthotropic media are considered using analytical and computational techniques. In the analytical formulation an interface crack between a graded orthotropic coating and a homogeneous orthotropic substrate is considered. The principal axes of orthotropy are assumed to be parallel and perpendicular to the crack plane. Mechanical properties of the medium are assumed to be continuous with discontinuous derivatives at the interface. The problem is formulated in terms of the averaged constants of plane orthotropic elasticity and reduced to a pair of singular integral equations which are solved numerically to compute the mixed mode stress intensity factors and the energy release rate. In the second part of the study, enriched finite elements are formulated and implemented for graded orthotropic materials. Comparisons of the finite element and analytical results show that enriched finite element technique is capable of producing highly accurate results for crack problems in graded orthotropic media. Finally, periodic interface cracking and the four point bending test for graded orthotropic solids are modeled using enriched finite elements and the results are briefly discussed.     

A surface mesh deformation method near component intersections for high-fidelity design optimization

Aerodynamic shape optimization based on computational fluid dynamics (CFD) requires three steps: updating the geometry based on the design variables, updating the CFD surface mesh for the new geometry, and updating the CFD volume mesh based on the new surface mesh. While there are many tools available for the first and third steps, the methods available for the second step are insufficient for geometries that have intersecting components. For these geometries, the CFD surface mesh needs to be updated near component intersections to conform to the component geometries and the updated intersection curves. To address this need, we introduce a method that can deform the CFD surface mesh nodes near component intersections. The method can handle arbitrary design changes for each intersecting component as long as the geometric topology is unchanged. Furthermore, the method is suitable for gradient-based optimization because it smoothly deforms every CFD surface node without introducing topological changes in the CFD surface mesh. In this paper, we detail each step of the proposed method and visualize the range of design changes that can be achieved with this approach. Finally, we use the proposed method in an aerodynamic shape optimization problem to optimize the wing-body intersection of the DLR-F6 configuration. These results demonstrate the effectiveness of the proposed method in a high-fidelity design optimization framework. The method applies to both structured and unstructured CFD meshes and makes it possible to use computer-aided design and conceptual design geometry tools within high-fidelity design optimization.

     

Effect of styrene‐butadiene‐styrene addition on polystyrene/high‐density polyethylene blends

In order to prepare an ideal mixture, the physical and chemical properties of the constituent polymers must be known in detail. Thus, selection of the polymers that will constitute the mixture and a thorough study of the mixing methods and the economic factors become important. A rigid plastic is toughened by dispersing a small amount of rubbery material (generally 5–20%) in the rigid plastic matrix. Such a mixture of plastics is characterized by its impact resistance. Among thermoplastics toughened in this way are polystyrene (PS), poly(vinyl chloride), poly(methyl methacrylate), polypropylene, polycarbonate, and nylons, and recently thermoset resins such as epoxies, unsaturated polyester resins, and polyamids. In this study PS and high‐density polyethylene polymers were mixed in various ratios. In order to increase the compatibility of the mixtures, 5, 7.5, and 10% SBS copolymer was also added. The mixing operation was conducted by using a twin‐screw extruder. The morphology and the compatibility of the mixtures were examined by using SEM and DSC techniques. Furthermore, the elastic modulus, yield and tensile strengths, percent elongation, Izod impact resistance, hardness, and melt flow index values of the polymer alloys of various ratios were determined. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 83: 2967–2975, 2002; DOI 10.1002/app.2325     

Surface-free energy analysis of hydrolyzed ethylene-vinyl acetate copolymers

Ethylene-vinyl acetate (E-VA) copolymers containing 12, 28, and 40 wt% of vinyl acetate, ethylene-vinyl acetate-vinyl alcohol terpolymers obtained by partial hydrolysis of (E-VA) copolymers and ethylene-vinyl alcohol (E-VOH) copolymers obtained by complete hydrolysis of (E-VA) copolymers were investigated by one-liquid contact-angle method. The polar force component of surface-free energy (γ) of copolymers drastically increased by the substitution of the acetate groups with hydroxyl groups. The dispersion force component (γ) of copolymers increased only slightly with the hydrolysis degree and deviated largely from the additivity law in regards of the surface area functions. The surface-free energy analysis of the cross-linked ethylene-vinyl alcohol and surface-hydrolyzed ethylene-vinyl acetate copolymers was also carried out.     

Fault detection on robot manipulators using artificial neural networks

Nowadays, gas welding applications on vehicle’s parts with robot manipulators have increased in automobile industry. Therefore, the speed of end-effectors of robot manipulator is affected on each joint during the welding process with complex trajectory. For that reason, it is necessary to analyze the noise and vibration of robot’s joints for predicting faults. This paper presents an experimental investigation on a robot manipulator, using neural network for analyzing the vibration condition on joints. Firstly, robot manipulator’s joints are tested with prescribed of trajectory end-effectors for the different joints speeds. Furthermore, noise and vibration of each joint are measured. And then, the related parameters are tested with neural network predictor to predict servicing period. In order to find robust and adaptive neural network structure, two types of neural predictors are employed in this investigation. The results of two approaches improved that an RBNN type can be employed to predict the vibrations on industrial robots.     

Detecting emotional state of a child in a conversational computer game

The automatic recognition of user’s communicative style within a spoken dialog system framework, including the affective aspects, has received increased attention in the past few years. For dialog systems, it is important to know not only what was said but also how something was communicated, so that the system can engage the user in a richer and more natural interaction. This paper addresses the problem of automatically detecting “frustration”, “politeness”, and “neutral” attitudes from a child’s speech communication cues, elicited in spontaneous dialog interactions with computer characters. Several information sources such as acoustic, lexical, and contextual features, as well as, their combinations are used for this purpose. The study is based on a Wizard-of-Oz dialog corpus of 103 children, 7–14 years of age, playing a voice activated computer game. Three-way classification experiments, as well as, pairwise classification between polite vs. others and frustrated vs. others were performed. Experimental results show that lexical information has more discriminative power than acoustic and contextual cues for detection of politeness, whereas context and acoustic features perform best for frustration detection. Furthermore, the fusion of acoustic, lexical and contextual information provided significantly better classification results. Results also showed that classification performance varies with age and gender. Specifically, for the “politeness” detection task, higher classification accuracy was achieved for females and 10–11 years-olds, compared to males and other age groups, respectively.