Dendrite coarsening and microsegregation in Al-Cu alloys

Solute redistribution and the amount of eutectic are predicted in the solidification structure of a dendritic Al-Cu alloy. The effect of dendrite coarsening on microsegregation during solidification is formulated. Local solidification time and alloy composition are found to change the type of operating dendrite coarsening. While one type of dendrite coarsening operates for a shorter local solidification time and/or lower alloy composition, at longer solidification times and/or higher alloy composition a different type of dendrite coarsening prevails. Local solidification time and alloy composition are the parameters which determine the homogenization and solution treatment, and the structural heterogeneity of the solidified ingot. METIN BASARAN, formerly Associate Professor, Department of Mechanical Engineering, Technical University of Istanbul, Turkey     

Use of a Compaction Simulator System in Tabletting Research

The components and principal operating features of a compaction simulator system are described. Initial experiments with 8 model materials, using single-ended and double-ended compression waveforms are reported. Data obtained at two tablet machine speeds (30 and 150rpm) and at two compressional pressure levels (80 and 400MPa) demonstrate a correlation between total work or average power consumed during the process and the tensile strength of the tablets. Non-linearity of Heckel plots and limited compliance with the Walker equation are also shown.     

Sun-control options in a high-rise office building

The DOE-2 building energy analysis computer program has been used to study the life-cycle cost and annual energy use for a wide range of glazing and sun-control options in a 25-story office building with 50% glazing. Four climates in the U.S. have been analyzed: Miami, Los Angeles, Washington, DC, and Chicago. The impact of daylighting in the perimeter zones for the various sun-control options has also been investigated. Double glazing was found to have little effect on energy use in Miami and Los Angeles, but reduced energy use 11–23% in Washington, DC, and 16–32% in Chicago, Daylighting reduced energy use 10–22% and had a simple payback period of 3.7–8.9 years depending on climate and type of fenestration. Of the alternatives considered, the lowest life-cycle cost and energy use were obtained with daylighting coupled with clear glazing and exterior sun-control blinds.     

Sketched symbol recognition with auto-completion

Sketching is a natural mode of communication that can be used to support communication among humans. Recently there has been a growing interest in sketch recognition technologies for facilitating human–computer interaction in a variety of settings, including design, art, and teaching. Automatic sketch recognition is a challenging problem due to the variability in hand drawings, the variation in the order of strokes, and the similarity of symbol classes. In this paper, we focus on a more difficult task, namely the task of classifying sketched symbols before they are fully completed. There are two main challenges in recognizing partially drawn symbols. The first is deciding when a partial drawing contains sufficient information for recognizing it unambiguously among other visually similar classes in the domain. The second challenge is classifying the partial drawings correctly with this partial information. We describe a sketch auto-completion framework that addresses these challenges by learning visual appearances of partial drawings through semi-supervised clustering, followed by a supervised classification step that determines object classes. Our evaluation results show that, despite the inherent ambiguity in classifying partially drawn symbols, we achieve promising auto-completion accuracies for partial drawings. Furthermore, our results for full symbols match/surpass existing methods on full object recognition accuracies reported in the literature. Finally, our design allows real-time symbol classification, making our system applicable in real world applications.     

ANN- and ANFIS-based multi-staged decision algorithm for the detection and diagnosis of bearing faults

Condition monitoring of roller element bearing defects has been one of the biggest problems in predictive maintenance since bearing failures may give catastrophic results on the machining operations and may cause downtime. Two of the well-established and widely used methods for bearing fault detection and diagnosis are the artificial neural network (ANN) and adaptive neuro-fuzzy inference systems (ANFIS). For this aim, a multi-staged decision algorithm was developed in this study based on ANN and ANFIS models. Both time and frequency domain parameters extracted from the vibration and current signals were used to train the ANN and ANFIS models, which were then used to detect and diagnose the severity of the bearing fault. Experimental data collected from a shaft-bearing mechanism were used to test the performances of the two schemes. The system was operated under four different speeds, for a brand-new bearing and bearings with artificially introduced local defects with various sizes. The experimental results showed that the proposed scheme is an effective means for detecting and diagnosing bearing faults. Furthermore, the results revealed that ANFIS-based scheme was superior to the ANN-based one especially in diagnosing fault severity.

     

Formation and growth of iron nitrides during ion-nitriding

In order to clarify the formation and growth kinetics of iron nitrides, Fe₂N (), Fe_2–3N () and Fe₄N (), on the surface of iron during ion-nitriding, and their contribution to the mechanism of ion-nitriding coarse-grained specimens (2 to 6 mm) were ion-nitrided in pure nitrogen and nitrogen-hydrogen (20%–80%) plasma at temperatures between 500 and 600°C. Reflection electron diffraction (RED) showed immediate formation of the nitrides. Growth of these phases in latter stages of ion-nitriding was studied using optical microscopy and X-ray diffraction. The mechanism of the nitride layer formation is discussed and compared with the existing gas nitriding data. In the case region, Fe₄N () and Fe₁₆N₂ () precipitation was observed to occur under all experimental conditions studied. Case depth is seen to be parabolic with time and nitriding rate increases slightly when nitrogen-hydrogen plasma is used. Discussions are given to explain the difference in the nitriding efficiency under two different plasma compositions.     

Approximate solutions for nonlinear oscillation of a mass attached to a stretched elastic wire

In this paper, the approximate solutions of the mathematical model of a mass attached to a stretched elastic wire are presented. At the beginning of the study, the equation of motion is derived in a detailed way. He’s max–min approach, He’s frequency–amplitude method and the parameter-expansion method are implemented to solve the established model. The numerical results are further compared with the approximate analytical solutions for both a small and large amplitude of oscillations, and a very good agreement is observed. The relative errors are computed to illustrate the strength of agreement between the numerical and approximate analytical results.     

Decision making in equipment selection: an integrated approach with AHP and PROMETHEE

Multi-attribute equipment selection is a very important issue for an effective manufacturing system, since the improper equipment selection might cause many problems affecting productivity, precision, flexibility and quality of the products negatively. On the other hand, selecting the best equipment among many alternatives is a multi-criteria decision making (MCDM) problem. In this study, an integrated approach which employs analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluations (PROMETHEE) together, is proposed for the equipment selection problem. The AHP is used to analyze the structure of the equipment selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain final ranking, and to make a sensitivity analysis by changing the weights. Proposed approach is applied to a problem of selecting milling machines to be purchased in an international company. Company management found the application and results satisfactory and implementable in their equipment selection decisions.     

Buckling of symmetric cross-ply square plates with various boundary conditions

The buckling analysis of cross-ply laminated square plates subjected to three types of in-plane forces and various edge boundary conditions is presented on the basis of a unified five-degree-of-freedom shear deformable plate theory. The employment of the appropriate “shear deformation shape functions” in the theory leads to certain shear deformable plate theories developed previously, also, fulfills the requirement of the continuity conditions among the layers. The governing equations of buckling behaviour of completely simply supported cross-ply laminated plates are solved analytically. For the plates with different combinations of free, clamped and simply supported boundary conditions at their edges, the Ritz method is applied by assuming the displacement components as the double series of simple algebraic polynomials. The numerical results obtained on the basis of various plate theories for uniaxial, biaxial compression and compression–tension types of loading and different length-to-thickness ratios are presented and compared with the ones available in the literature.