Dielectric properties of sol-gel derived Ta2O5 thin films

The dielectric constant and the dielectric loss of tantalum pentoxide (Ta₂O₅) thin films, produced by sol-gel spin-coated process on Corning glass substrates, have been investigated in the frequency range of 20-10⁵ Hz and the temperature range of 183-403 K, using ohmic Al electrodes. The frequency and temperature dependence of relaxation time has also been determined. The capacitance and loss factor were found to decrease with increasing frequency and increase with increasing temperature. The activation energy values were evaluated and a good agreement between the activation energy values obtained from capacitance and dielectric loss factor measurements were observed.     

The effect of niobium on the microstructure of ferritic stainless steel

The effect of different amounts of Nb and of homogenization on the ferritic stainless steels containing 17–18 wt.% Cr was investigated with scanning electron microscopy (SEM), optical microscopy, energy-dispersive spectrometry (EDS), X-ray diffraction (XRD) and differential thermal analysis (DTA). It was observed that M₂₃C₆, NbC and sigma phase formed in these steels. In addition, the formation of Nb₂C was observed in the sample containing 3.0 wt.% Nb. While the amount of Nb increased from 0.5 to 3.0 wt.% Nb, the microhardness of the matrix and the amount of M₂₃C₆ decreased and the toughness of the samples increased. After homogenization, the increase in the toughness of the samples containing 1.5–3.0 wt.%Nb was considerable and impressive.     

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.     

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.

     

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.     

Inverse propagation of uncertainties in finite element model updating through use of fuzzy arithmetic

A fuzzy finite element model updating (FFEMU) method is presented in this study for the damage detection problem. The uncertainty caused by the measurement noise in modal parameters is described by fuzzy numbers. Inverse analysis is formulated as a constrained optimization problem at each α-cut level. Membership functions of each updating parameter which correspond to reduction in bending stiffness of the finite elements is determined by minimizing an objective function using a hybrid version of genetic algorithms (GA) and particle swarm optimization method (PSO) which is very efficient in terms of accuracy and robustness. Practical evaluation of the approximate bounds of the interval modal parameters in FFEMU iterations is addressed. A probabilistic analysis is performed using Monte Carlo simulation (MCS) and the results are compared with presented FFEMU method. It is apparent from numerical simulations that the proposed method is well capable in finding the membership functions of the updating parameters within reasonable accuracy. It is also shown that the results obtained by FFEMU are in good agreement with the MCS results while FFEMU is not as computationally expensive as the MCS method. Nevertheless, the proposed FFEMU do not required derivatives of the objective function like existing methods except in the deterministic case.