Novel Constitutive Equation for Predicting Dynamic Recrystallization During Hot Working Considering the Efficiency of Power Dissipation

The efficiency of power dissipation (η) in a dynamic material model has been conventionally used for qualitative predictions to estimate the hot working conditions at which dynamic recrystallization (DRX) is dominant. However, predicting the quantitative value of the DRX fraction (X_DRX) from η remains a challenge. In this paper, a constitutive equation is proposed to quantitatively predict X_DRX using η. The proposed equation for describing X_DRX is derived from the reaction rate equation using the assumption that the DRX rate depends on η. The proposed equation is verified via hot compression tests of equiaxed Ti–6Al–4V ELI alloys (Ti-64) in the (α + β) region. The predicted and experimental X_DRX values are found to be generally consistent with one another, exhibiting an average absolute error of 0.05. Furthermore, the proposed equation provides the same level of prediction accuracy as the conventional Johnson–Mehl–Avrami–Kolmogorov (JMAK) equation. Therefore, the proposed equation can be used to quantitatively predict X_DRX following hot compression tests of equiaxed Ti-64. Moreover, compared with the JMAK equation, the proposed equation is expressed in fewer parameters and constant terms. It is, thus, expected to facilitate the quantitative prediction of X_DRX.

     

Catalysis of gasification of coal-derived cokes and chars

Calcium is the most important in-situ catalyst for gasification of US coal chars in O₂, CO₂ and H₂O. It is a poor catalyst for gasification of chars by H₂. Potassium and sodium added to low-rank coals by ion exchange and high-rank coals by impregnation are excellent catalysts for char gasification in O₂, CO₂ and H₂O. Carbon monoxide inhibits catalysis of the CH₂O reaction by calcium, potassium and sodium; H₂ inhibits catalysis by calcium. Thus injection of synthesis gas into the gasifier will inhibit the CH₂O reaction. Iron is not an important catalyst for the gasification of chars in O₂, CO₂ and H₂O, because it is invariably in the oxidized state. Carbon monoxide disproportionates to deposit carbon from a dry synthesis gas mixture (3 vol H₂ + 1 vol CO) over potassium-, sodium- and iron-loaded lignite char and a raw bituminous coal char, high in pyrite, at 1123 K and 0.1 MPa pressure. The carbon is highly reactive, with the injection of 2.7 kPa H₂O to the synthesis gas resulting in net carbon gasification. The effect of traces of sulphur in the gas stream on catalysis of gasification or carbon-forming reactions by calcium, potassium, or sodium is not well understood at present. Traces of sulphur do, however, inhibit catalysis by iron.     

Some theoretical aspects of the electrophoretic sedimentation of particles

This paper concerns the theoretical interpretation of the results of a previous experimental study of the sedimentation of oxidized fine aluminum and iron particles in waste kerosene under the influence of an electric field. Following the Kynch analysis of the mode of gravity sedimentation, a modified particle volume flux is introduced to compensate for the effect of the electric field strength. It is shown that if the local electric field strength at the settling interface is used as the true driving force for electrophoretic sedimentation, the settling curves can be predicted with reasonable accuracy, provided that electrical heating effects and consequent temperature changes in the system are taken into account.Some theoretical aspects of the effects of dielectric polarization on settling are also discussed and illustrated qualitatively by the experimental data. Finally, some of the factors which might be expected to affect the energy efficiency of a particle separator operating by electrophoretic sedimentation are considered.     

One-step formation of ethyl methyl ketone from 1-butene and water on ultrastable Y-type zeolite catalyst

Proton exchanged ultrastable Y-type zeolite with silica/alumina = 40 showed a pronounced catalytic activity for the formation of ethyl methyl ketone directly from 1-butene and water. The formation rate of ethyl methyl ketone was much higher than those on MoO₃-based catalysts in the oxidation of 1-butene by oxygen. It was suggested that the basic site necessary for the formation of ethyl ketone directly from 1-butene and water would be the pentacoordinated Al.     

Carbon-13 NMR spectroscopic analysis of 24-methyl-Δ5,22-sterols in rape and mustard seed oils

24-Methylcholesta-5,E-22-dien-3β-ol (C₂₈ Δ^5,22-sterol) was separated from the unsaponifiable matters of the following eight seed oils of Brassica species:Brassica campestris (candle I and II and torch),B. napus (tower and midas),B. juncea (brown and oriental mustards), andB. alba (yellow mustard). The configuration at C-24 methyl group of the respective sterols was evaluated by¹³C NMR spectroscopy. All the C₂₈ Δ^5,22-sterols in the Brassica seed oils were found to contain the C-24 epimer of brassicasterol,trans-22-dehydrocampesterol, in the range of ca. 10–30%.     

Predicting viewer-perceived activity/dominance in soccer games with stick-breaking HMM using data from a fixed set of cameras

We attempted to predict activity/dominance for soccer games, where activity is defined as the degree of activity of the game as perceived by the viewer, whereas dominance is the degree at which the viewer perceives a particular team to dominate over the other team. Such activity/dominance information would help a layman viewer understand the game. It would also enable construction of an automatic digest creation system that extracts scenes having high activity/dominance. There are two facets of this study: 1. The main part of the underlying prediction model consists of a Stick-Breaking Hidden Markov Model, where the data automatically estimates the number of states of the Markov process behind the data. 2. The data used in this paper is vector time-series data consisting of player, referee, and ball positions, together with team information, acquired by a set of fixed cameras. The problem was approached with a Bayesian framework where learning and prediction were implemented by three different methods: Markov Chain Monte Carlo, Expectation Maximization, and Variational Bayes. The proposed method was tested using a dataset consisting of 10 professional soccer games and was compared against standard regression methods.     

Studying re-opened bugs in open source software

Bug fixing accounts for a large amount of the software maintenance resources. Generally, bugs are reported, fixed, verified and closed. However, in some cases bugs have to be re-opened. Re-opened bugs increase maintenance costs, degrade the overall user-perceived quality of the software and lead to unnecessary rework by busy practitioners. In this paper, we study and predict re-opened bugs through a case study on three large open source projects—namely Eclipse, Apache and OpenOffice. We structure our study along four dimensions: (1) the work habits dimension (e.g., the weekday on which the bug was initially closed), (2) the bug report dimension (e.g., the component in which the bug was found) (3) the bug fix dimension (e.g., the amount of time it took to perform the initial fix) and (4) the team dimension (e.g., the experience of the bug fixer). We build decision trees using the aforementioned factors that aim to predict re-opened bugs. We perform top node analysis to determine which factors are the most important indicators of whether or not a bug will be re-opened. Our study shows that the comment text and last status of the bug when it is initially closed are the most important factors related to whether or not a bug will be re-opened. Using a combination of these dimensions, we can build explainable prediction models that can achieve a precision between 52.1–78.6 % and a recall in the range of 70.5–94.1 % when predicting whether a bug will be re-opened. We find that the factors that best indicate which bugs might be re-opened vary based on the project. The comment text is the most important factor for the Eclipse and OpenOffice projects, while the last status is the most important one for Apache. These factors should be closely examined in order to reduce maintenance cost due to re-opened bugs.     

Expectation-maximization algorithms for inference in Dirichlet processes mixture

Mixture models are ubiquitous in applied science. In many real-world applications, the number of mixture components needs to be estimated from the data. A popular approach consists of using information criteria to perform model selection. Another approach which has become very popular over the past few years consists of using Dirichlet processes mixture (DPM) models. Both approaches are computationally intensive. The use of information criteria requires computing the maximum likelihood parameter estimates for each candidate model whereas DPM are usually trained using Markov chain Monte Carlo (MCMC) or variational Bayes (VB) methods. We propose here original batch and recursive expectation-maximization algorithms to estimate the parameters of DPM. The performance of our algorithms is demonstrated on several applications including image segmentation and image classification tasks. Our algorithms are computationally much more efficient than MCMC and VB and outperform VB on an example.     

Lithography with UV-LED array for curved surface structure

The technology to fabricate high-aspect ratio and micro curved surface structures is needed for optical device fabrication such as micro lens, light guiding device, and so on. In this study, micro curved surface structures were fabricated by using novel lithography technique with UV-LED array and rotary stage (Hanai et al. in Proceedings of the 22nd sensor symposium, pp 516–519, 2005). Smooth surface structures can be fabricated in this technique, because UV-LED which has wide directivity characteristics makes the difference of the UV dose. In addition, the structures can be formed with high uniformity in large area by only one exposure process, because rotation reduces the unevenness of exposure. This technique can control the shapes of structures by changing exposure time and applying gray scale mask method (Waits et al. in Sensors Actuat A 119:245–253, 2005). We fabricated structures of hemisphere, semi-cylinder, and semi-cone by using this technique. High-aspect ratio structures were obtained and they had smooth curved surface. Then, they were used for micro lens fabrication. By using molding technique, micro lenses of the UV curable resin were fabricated on the silicon wafer.