Off-line multiresponse optimization of electrochemical surface grinding by a multi-objective programming method

The objective of this study is to optimize electrochemical grinding (ECG) process responses simultaneously by an off-line multiresponse optimization methodology. The responses considered as objectives are side and bottom overcuts, surface finish, spindle load, total metal removal rate, and wheel wear. Materials of 304 Stainless Steel are ground by the ECG process. The process variables optimized for the above objectives include electrolyte type, wheel material, grit size, grit concentration, d.c. voltage, electrolyte flow rate, wheel speed, feed rate, and ripple effect. A simple weighting method transforms the multi-objective problem into a single-objective programming format and then, by parametric variation of the weights, the set of non-dominated optimum solutions are obtained. It is shown in this paper that the multi-objective optimization methodology can be applied for an ECG operation, and that the optimal operating conditions for any given set of weights can be obtained depending upon the objectives.     

Connecting the dots: Understanding the interrelated impacts of type,quality and children's awareness of design features and the mathematics content learning goals in digital math games and related learning outcomes

This study focused on an examination of how type, quality and children's awareness of design features in digital math games, along with an awareness of the mathematics goals of the game, were related to learning outcomes. We conducted a parallel conversion mixed methods study with 45 students in Grades 3 and 4 (ages 9–10). Students participated in clinical interviews using three digital math games. The results suggest a moderated mediation relationship in which the quality of the design features moderated the mediating impact of children's awareness of the game's design features, specifically when the child was aware of the mathematics content learning goal (MCLG) of the game. These findings show how important it is that design features are of high quality in a digital math game, and how this is intertwined with children's awareness of the features and the MCLG. When these variables intertwined in just the right way, the interactions between the children and the digital math game afforded mathematical learning growth.     

Scaling Analysis for the Axial Displacement and Pressure of Flextensional Transducers

We have examined the axial displacement, Δ h , and maximum axial pressure, P _max, of flextensional transducers such as the moonies and the rainbows with both scaling and mechanical analyses. For a constant electric field E across the transducer, Δ h / t ∝ E / t ² where t is the thickness of the rainbow or the thickness of the metal end cap of the moonie and Δ h / t , the relative axial displacement. Thus, for a constant voltage V across the transducer, Δ h / t ∝ V / t ³. As for the maximum pressure, P _max t ² for the rainbows and P _max∝ wt for the moonies where t is the thickness of the rainbow or the thickness of the metal end cap of the moonie and w the thickness of the piezoelectric disk of the moonie. These predictions agree well with the experimental results found in the rainbows and the moonies. Our analysis showed that although the rainbows and the moonies differ in design and processing, the underlying physics for the enhancement in the axial displacement are essentially the same: The nonuniform distribution of d ₃₁ through the thickness of the transducer causes the transducer to arch or flatten with an applied electrical field, which leads to the enhancement in the axial displacement. The only difference is that, for the transducer to arch, the applied field is in the opposite direction to the polarization in the rainbows but in the same direction as the polarization in the moonies.     

Processing of Silicon Carbide-Mullite-Alumina Nanocomposites

Nanocomposite materials in the form of nanometer-sized second-phase particles dispersed in a ceramic matrix have been shown to display enhanced mechanical properties. In spite of this potential, processing methodologies to produce these nanocomposites are not well established. In this paper, we describe a new method for processing SiC-mullite-Al₂O₃ nanocomposites by the reaction sintering of green compacts prepared by colloidal consolidation of a mixture of SiC and Al₂O₃ powders. In this method, the surface of the SiC particles was first oxidized to produce silicon oxide and to reduce the core of the SiC particles to nanometer size. Next, the surface silicon oxide was reacted with alumina to produce mullite. This process results in particles with two kinds of morphologies: nanometer-sized SiC particles that are distributed in the mullite phase and mullite whiskers in the SiC phase. Both particle types are immersed in an Al₂O₃ matrix.     

Consolidation Behavior of Flocculated Alumina Suspensions

The consolidation behavior of flocculated alumina suspensions has been analyzed as a function of the interparticle energy. Consolidation was performed by a centrifugal force field or by gravity, and both the time-dependent and equilibrium density profiles were measured by a gamma-ray absorption technique. The interparicle energy at contact was controlled by adsorbing fatty acids of varying molecular weight at the alumina/decalin interface. We found that strongly attractive interactions result in a particle network which resists consolidation and shows compressible behavior over a large stress range. The most weakly flocculated suspension showed an essentially incompressible, homogeneous density profile after consolidation at different centrifugal speeds. We also found a significant variation in the maximum volume fraction, φ_m, obtained, with φ_m∼ 0.54 for the most strongly flocculated suspension to φ_m∼ 0.63 for the most weakly flocculated suspension. The compresive yield stresses show a behavior which can be fitted to a modified power law. In this paper, we discuss possible correlations between the fitting parameters and physical properties of the flocculated suspensions.     

Mullitization of Diphasic Aluminosilicate Gels

Recent studies have shown that the mullitization of diphasic aluminosilicate matrices comprising transitional alumina and amorphous silica occurs via a nucleation and growth process. Nucleation is preceded by a temperature-dependent incubation period. Following this incubation period, rapid nucleation of mullite occurs, producing about 1.8 × 10¹¹ nuclei/cm³, which remains constant throughout the rest of the transformation. Both incubation and mullite growth are thermally activated processes with apparent activation energies of 987 ± 63 and 1070 ± 200 kJ/mol, respectively. The growth rate of mullite grains under isothermal conditions is time dependent. An interpretation of these results is proposed on the basis of the nucleation and growth concepts of LaMer and Dinegar which supports the concept that the growth rate of mullite grains is controlled by the dissolution of transitional alumina into the amorphous matrix.     

Mullite for Structural, Electronic, and Optical Applications

Mullite (3Al₂O₃·2SiO₂) is becoming increasingly important in electronic, optical, and high-temperature structural applications. This paper reviews the current state of mullite-related research at a fundamental level, within the framework of phase equilibria, crystal structure, synthesis, processing, and properties. Phase equilibria are discussed in terms of the problems associated with the nucleation kinetics of mullite and the large variations observed in the solid-solution range. The incongruent melting behavior of mullite is now widely accepted. Large variations in the solid solubility from 58 to 76 mol% alumina are related to the ordering/disordering of oxygen vacancies and are strongly coupled with the method of synthesis used to form mullite. Similarly, reaction sequences which lead to the formation of mullite upon heating depend on the spatial scale at which the components are mixed. Mixing at the atomic level is useful for low-temperature (<1000°C) synthesis of mullite but not for low-temperature sintering. In contrast, precursors that are segregated are better suited for low-temperature (1250° to 1500°C) densification through viscous deformation. Flexural strength and creep resistance at elevated temperatures are significantly affected by the presence of glassy boundary inclusions; in the absence of glassy inclusions, polycrystalline mullite retains >90% of its room-temperature strength to 1500°C and displays very high creep resistance. Because of its low dielectric constant, mullite has now emerged as a substrate material in high-performance packaging applications. Interest in optical applications mainly centers on its applicability as a window material within the mid-infrared range.     

Signal‐to‐noise ratios for measuring saliency of features extracted by eigenvector methods from ophthalmic arterial Doppler signals

Abstract: Features are used to represent patterns with minimal loss of important information. The feature vector, which is composed of the set of all features used to describe a pattern, is a reduced‐dimensional representation of that pattern. Medical diagnostic accuracies can be improved when the pattern is simplified through representation by important features. By identifying a set of salient features, the noise in a classification model can be reduced, resulting in more accurate classification. In this study, a signal‐to‐noise ratio saliency measure was employed to determine the saliency of input features of recurrent neural networks (RNNs) used in classification of ophthalmic arterial Doppler signals. Eigenvector methods were used to extract features representing the ophthalmic arterial Doppler signals. The RNNs used in the ophthalmic arterial Doppler signal classification were trained for the signal‐to‐noise ratio screening method. The application results of the signal‐to‐noise ratio screening method to the ophthalmic arterial Doppler signals demonstrated that classification accuracies of RNNs with salient input features are higher than those of RNNs with salient and non‐salient input features.     

Feature extraction by autoregressive spectral analysis using maximum likelihood estimation: internal carotid arterial Doppler signals

Abstract: In this study, Doppler signals recorded from the internal carotid artery (ICA) of 97 subjects were processed by personal computer using classical and model-based methods. Fast Fourier transform (classical method) and autoregressive (model-based method) methods were selected for processing the ICA Doppler signals. The parameters in the autoregressive method were found by using maximum likelihood estimation. The Doppler power spectra of the ICA Doppler signals were obtained by using these spectral analysis techniques. The variations in the shape of the Doppler spectra as a function of time were presented in the form of sonograms in order to obtain medical information. These Doppler spectra and sonograms were then used to compare the applied methods in terms of their frequency resolution and the effects in determination of stenosis and occlusion in the ICA. Reliable information on haemodynamic alterations in the ICA can be obtained by evaluation of these sonograms.