Gasification kinetics of oil sands coke

Kinetics of steam gasification of delayed and fluid cokes derived from Athabasca bitumen have been studied in 6.35 cm diameter stirred and fixed bed reactors. Experiments were carried out at atmospheric pressure and at temperatures between 800°C and 930°C. The coke particle size ranged from 0.1 to 3.5 mm, and the steam partial pressure was varied from 15.2 to 60.6 kPa. Scanning electron microscopy, surface area analysis, and mercury porosimetry were employed to relate physical structure changes in the solids to experimental kinetic data. Several kinetic models for gasification were tested with the experimental gasification data. Rate expressions are presented for carbon conversion and for the release of sulphur.     

Authentification and identification — Taking the user into account

Username/Password is still the prevailing authentication mechanism for internet based services — but it is not secure! We show how new authentication and identification mechanisms focused on usability and security can change this.     

Living carbocationic polymerization

Summary Living carbocationic polymerization of styrene (St) has been achieved by the use of the 1(p-methylphenyl)ethyl acetate (pMePhEtOAc)·BCl₃ complex in CH₃Cl solvent at –30°C using both the IMA and AMI techniques. The living nature of the polymerizations has been demonstrated by linear M_n versus W_PSt (weight of polystyrene) plots passing through the origin and horizontal N (moles of PSt) versus W_PSt plots starting at N=I_o (the number of moles of initiator used). The molecular weight distribution MWD of the PSts is broad (M_w/M_n=~5–6) due to slow initiation and/or slow exchange between dormant and active species relative to propagation. The structure of the ester initiator strongly affects the rate and outcome of living polymerization, e.g., cumyl acetate (CumOAc), cumyl propionate (CumOPr), and 2,4,6-trimethylphenylethyl acetate (TMePhEtOAc), do not lead to truly living St polymerizations. The findings with the latter esters is explained in terms of a two path process comprising a slow living polymerization and a faster conventional cationic chain reaction. With phenylethyl acetate (PhEtOAc) living polymerization is achieved, however, initiation (cation generation) is slow. Forced termination by pyridine or methanol, or heating to ambient temperature leads to-CH₂CH(C₆H₅)Cl end groups.     

Living carbocationic polymerization

Conventional cationic polymerization can be converted into living carbocationic polymerization (LC^⊕Pzn) by the introduction of common anion into the charge. Thus the conventional polymerization of isobutylene (IB) induced by the 2-chloro-2,4,4-trimethylpentane (TMPCl)/TiCl₄ combination yields LC^⊕Pzn of IB upon the addition of tetrabutyl ammonium chloride (n-Bu₄NCl), most likely due to then-Bu₄NCl+TiCl₄ ?n-Bu₄N^⊕+TiCl ₅ ^⊕ equilibrium. A kinetic model has been developed and tested which corroborates these propositions. By this model we have gained for the first time quantitative insight into the quasiliving equilibrium.     

Application of Fuzzy Moving Sliding Surface Approach for Container Cranes

International Journal of Control, Automation and Systems - In this paper, we consider the fuzzy moving sliding surface anti-sway control problem for container cranes. We first introduce the dynamic...     

Satellite-Based Water Quality Mapping from Sequential Simulation with Parameter Outlier Removal

The satellite-based regression model provides the data model that identifies water quality for inland and coastal waters. However, the satellite regression usually depends on the selection of observation, satellite data, and model type. A resampling simulation technique, such as sequential simulation using geographically weighted regression (GWR simulation), can be applied in generating multiple realizations for water quality estimation to reduce the sampling effect and consider spatial heterogeneity. Traditional models often result in considerable underestimation in extreme observations. The GWR simulation provides the best goodness of fit and spatial varying relationship between observed water quality and remote sensing considering parameter outlier and noise removal for parameter stability. This simulation model can increase the sampling diversity from various observations and reduce the neighboring effects of observations using outlier and noise removal. The model that handles spatial uncertainty and heterogeneity is a novel tool for inferring the characteristics of water quality from a series of sample subsets.

     

Micro cam system driven by electrostatic comb-drive actuators based on SOI-MEMS technology

Microsystem Technologies - This paper reports a design and fabrication process of a micro cam system (MCS) with a flat-faced translating follower. The cam rim with cover diameter of 2.4 mm...     

High quality voice conversion using prosodic and high-resolution spectral features

Voice conversion methods have advanced rapidly over the last decade. Studies have shown that speaker characteristics are captured by spectral feature as well as various prosodic features. Most existing conversion methods focus on the spectral feature as it directly represents the timbre characteristics, while some conversion methods have focused only on the prosodic feature represented by the fundamental frequency. In this paper, a comprehensive framework using deep neural networks to convert both timbre and prosodic features is proposed. The timbre feature is represented by a high-resolution spectral feature. The prosodic features include F0, intensity and duration. It is well known that DNN is useful as a tool to model high-dimensional features. In this work, we show that DNN initialized by our proposed autoencoder pretraining yields good quality DNN conversion models. This pretraining is tailor-made for voice conversion and leverages on autoencoder to capture the generic spectral shape of source speech. Additionally, our framework uses segmental DNN models to capture the evolution of the prosodic features over time. To reconstruct the converted speech, the spectral feature produced by the DNN model is combined with the three prosodic features produced by the DNN segmental models. Our experimental results show that the application of both prosodic and high-resolution spectral features leads to quality converted speech as measured by objective evaluation and subjective listening tests.