Determination of gas dispersion in vapor extraction of heavy oil and bitumen

In this work, a mathematical model is developed and simulated to determine gas dispersion along with solubility during the vapor extraction (Vapex) of live oil from a laboratory scale physical model. The physical model is a rectangular block of homogenous porous medium saturated with heavy oil and bitumen. At a given temperature and pressure, the block is initially exposed on its side to a solvent gas, which diffuses into the medium and gets absorbed. The absorption of gas reduces the viscosity of heavy oil and bitumen causing it to drain under gravity. The low-viscosity “live oil” is produced at the bottom of the porous block. The production of live oil with time is accompanied by the shrinkage of oil in the block as well as its increased exposure to gas from top. These phenomena of Vapex are described by the mathematical model, which is used to calculate live oil production with various values of gas solubility and dispersion. Their optimal values are determined for the vapor extraction of Cold Lake bitumen with butane by matching calculated live oil production with its experimental values published earlier.     

Specimen preparation and image processing and analysis techniques for automated quantification of concrete microcracks and voids

Specimen preparation and image processing/analysis techniques were developed for use in automated quantitative microstructural investigation of concrete, focusing on concrete microcracks and voids. Different specimen preparation techniques were developed for use in fluorescent and scanning electron microscopy (SEM) of concrete; then techniques produce a sharp contrast between microcracks/voids and the body of concrete. The image processing/analysis techniques developed specifically for use with concrete address the following usages: automatic threshold; development of intersecting microcracks/voids and connected voids; distinction of microcracks form voids based on geometric attributes; and noise filtration.     

Comparative study of the electrical properties of diamond films grown by microwave plasma assisted and hot-filament chemical vapor deposition

Schottky diodes were built on different polycrystalline diamond films grown by Microwave Plasma and Hot Filament Chemical Vapor Deposition and their electrical properties were studied. The barrier height increased with the diamond film quality and the corresponding ideality factor decreased. Even though the lower-quality HFCVD film displayed poor rectifying properties, it was found to be much less sensitive to variations in the operating conditions (air vs. vacuum). The activation energies of the films depend on morphological parameters, as preferable grain size or orientation. The bulk conduction also depends on the quality of the deposited films, changing from ohmic to trap-free or shallow trap SCLC and SCLC with an exponential distribution of traps. The hypothesis of using the electrical measurements as an indicator for film quality has been discussed.     

Electrocopolymerization of aniline and ortho-phenylenediamine via facile negative shift of polyaniline redox peaks

Oxidative electropolymerization of aniline (Ani) in phosphoric acid (H₃PO₄) on composite 2B pencil graphite was accomplished using selected inorganic salts as supporting electrolytes. These salts determined the degree of conductivity of polyaniline (PAni) formed. The conductivity was in the order of CaCl₂ > KCl > ZnCl₂ > ZnSO₄ > Ca₃(PO₄)₂. The three pairs of redox peaks in the voltammogram of PAni formed in the presence of 0.06 M Ca₃(PO₄)₂ and 0.2 M ZnSO₄ have shifted 300 mV to the negative potential. The shifting of peaks is strongly influenced by type of anions' presence in the salts. However, the nature of the available cations had no significant effect. The negative shifts of redox peaks were exploited to facilitate the electrocopolymerization of Ani and ortho-phenylenediamine (oPD). The formation of the poly(Ani-co-oPD) was confirmed by the FTIR spectra.     

Optimal estimation of parameters of dynamical systems by neural network collocation method

In this paper we propose a new method to estimate parameters of a dynamical system from observation data on the basis of a neural network collocation method. We construct an object function consisting of squared residuals of dynamical model equations at collocation points and squared deviations of the observations from their corresponding computed values. The neural network is then trained by optimizing the object function.The proposed method is demonstrated by performing several numerical experiments for the optimal estimates of parameters for two different nonlinear systems. Firstly, we consider the weakly and highly nonlinear cases of the Lorenz model and apply the method to estimate the optimum values of parameters for the two cases under various conditions. Then we apply it to estimate the parameters of one-dimensional oscillator with nonlinear damping and restoring terms representing the nonlinear ship roll motion under various conditions. Satisfactory results have been obtained for both the problems.     

Accurate and simple synthesis formulas for coplanar waveguides

Simple and accurate closed‐form formulas obtained by using a differential evolution algorithm are presented for the synthesis of coplanar waveguides (CPW). The results of the synthesis formulas proposed in this article are compared with those of the quasi‐static analysis, the synthesis formulas reported by the other researchers and also the experimental works available in the literature. The accuracy of the proposed synthesis formulas is found to be better than 0.75% for 9256 CPWs samples. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

Reconstruction of reflectance spectra using weighted principal component analysis

The weighted principal component analysis technique is employed for reconstruction of reflectance spectra of surface colors from the related tristimulus values. A dynamic eigenvector subspace based on applying certain weights to reflectance data of Munsell color chips has been formed for each particular sample and the color difference value between the target, and Munsell dataset is chosen as a criterion for determination of weighting factors. Implementation of this method enables one to increase the influence of samples which are closer to target on extracted principal eigenvectors and subsequently diminish the effect of those samples which benefit from higher amount of color difference. The performance of the suggested method is evaluated in spectral reflectance reconstruction of three different collections of colored samples by the use of the first three Munsell bases. The resulting spectra show considerable improvements in terms of root mean square error between the actual and reconstructed reflectance curves as well as CIELAB color difference under illuminant A in comparison to those obtained from the standard PCA method. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 360–371, 2008