Maya crude hydrodemetallization and hydrodesulfurization catalysts: An effect of TiO2 incorporation in Al2O3

Hydrotreating of Maya heavy crude oil over high specific surface area CoMo/TiO₂–Al₂O₃ oxide supported catalysts was studied in an integral reactor close to industrial practice. Activity studies were carried out with Maya crude hydrodesulfurization (HDS), hydrodemetallization (HDM), hydrodenitrogenation (HDN), and hydrodeasphaltenization (HDAs) reactions. The effect of support composition, the method of TiO₂ incorporation, and the catalyst deactivation are examined. Supported catalysts are characterized by BET specific surface area (SSA), pore volume (PV), pore size distribution (PSD), and atomic absorption. It has been found that sulfided catalysts showed a wide range of activity variation with TiO₂ incorporation into the alumina, which confirmed that molybdenum sulfided active phases strongly depend on the nature of support. The pore diameter and nature of the active site for HDS, HDM, HDN, and HDAs account for the influence of the large reactant molecules restricted diffusion into the pore, and/or the decrease in the number of active sites due to the MoS₂ phases buried with time-on-stream. The textural properties and hysteresis loop area of supported and spent catalysts indicated that catalysts were deactivated at the pore mouth due to the metal and carbon depositions. The atomic absorption results agreed well regarding the textural properties of spent catalysts. Thus, incorporation of TiO₂ with γ-Al₂O₃ alters the nature of active metal interaction with support, which may facilitate the dispersion of active phases on the support surface. Therefore, the TiO₂ counterpart plays a promoting role to HDS activity due to the favorable morphology of MoS₂ phases and metal support interaction.     

Sorption/diffusion of aqueous mixtures of 1,4‐dioxane/tetrahydrofuran through blend membranes of poly(vinyl alcohol) and sodium alginate: Their compatibility and pervaporation separation studies

Blend membranes of poly(vinyl alcohol) (PVA) and sodium alginate (NaAlg) were prepared by solution casting and crosslinked with glutaraldehyde (GA). Polymer blend compatibility was studied in water by measuring solution viscosity at 30°C. From the viscosity data, interaction parameters were determined to find the blend compatibility. Thickness of the membranes ranged between 35 and 40 μm. Circular disc‐shaped samples were cut from the thin membranes to perform gravimetric sorption experiments in water + 1,4‐dioxane and water + tetrahydrofuran mixtures at 30°C. Diffusion coefficients were calculated using Fick's equation. Concentration profiles of liquids were computed by solving Fick's equation under suitable boundary conditions. Diffusion coefficients show a dependence on the composition of the blends as well as composition of binary mixtures. A correlation was attempted between concentration profiles and diffusion coefficients of the transporting liquids. Degree of swelling and sorption coefficients were calculated from the gravimetric sorption data. Sorption kinetics was studied using an empirical equation to understand the nature of sorption–diffusion anomalies. Membrane selectivity for water + 1,4‐dioxane and water + tetrahydrofuran mixtures were calculated from the pervaporation experiments. A correlation between sorption and membrane selectivity was attempted. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 178–188, 2005     

Characteristics and compositions ofCarissa spinarum,Leucaena leucocephala andPhysalis minima seeds and oils

The seeds and extracted oils ofCarissa spinarum (Apocynaceae), (I),Leucaena leucocephala (Leguminosae) (II) andPhysalis minima (Solanaceae) (III) were analyzed for characteristics and compositions. The seeds of I, II and III contained 22.4, 6.4 and 40.0% oil and 10.1, 27.6 and 17.9% protein, respectively. The oils of I, II and III had, respectively, iodine values 70.1, 113.5 and 122.5; saponification values 186, 188 and 189; unsaponifiable matter 5.2, 2.5 and 0.8%, and the following fatty acid compositions (area %): palmitic 12.6, 14.2, 10.5; stearic 7.6, 6.1, 8.6; oleic 72.7, 20.1, 17.3; linoleic 5.2, 53.8, 61.4; linolenic 0.9, 1.8, 0.0, and arachidic 1.0, 2.3, 0.0. II contained 1.7% lignoceric acid. III contained small amounts of hexadecenoic (0.1%), epoxy (0.6%) and hydroxy (1.5%) fatty acids.     

A compact asymmetric slot dual band antenna fed by CPW for PCS and UWB applications

A compact slot antenna with an overall dimension of 30 × 30 × 1.6 mm³ is proposed for dual band applications. The radiating element is a hexagonal shape patch which protrudes from a Co‐Planar Waveguide (CPW) feed into a step shape slot. The slot is basically rectangular in shape and is extended by inserting rectangular cuts of different sizes on the ground plane around it. The ultrawide impedance bandwidth is achieved using asymmetric feed line along with extended rectangular cuts around the slot. For realizing the second band for personal communication system applications (near 1.9 GHz), a metallic stub of quarter wave length is attached at the top of the slot. The measured impedance bandwidth (for S₁₁ < ?10 dB) is 110 MHz (1.86–1.97 GHz) for the first band and 9 GHz (3.0–12.0 GHz) for the second band. The antenna is further characterized by omnidirectional radiation patterns in the H‐plane, dumb‐bell shape radiation patterns in the E‐plane and a peak gain of 3–5 dBi over the ultrawideband. All the measured results are found to be in good agreement with the simulated results. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:243–254, 2015.     

A New Method for Getting Rational Approximation for Fractional Order Differintegrals

In this paper a new algorithm is presented to calculate the poles and zeros to approximate a fractional order (FO) differintegral (s^±α,α∈(0,1)) by a rational function on a finite frequency band ω∈(ω_l,ω_h). The constant phase property of the FO differintegral is the basis for development of the algorithm. Interlacing of real poles and zeros is used to achieve the constant phase. The calculations are done using the asymptotic Bode phase plot. A brief investigation is made to get a good approximation for the Bode phase plot. Two design parameters are introduced to keep the average phase close to the desired phase angle and to keep the error within the allowed bounds. A study is done to empirically understand the relationship between the error and the design parameters. The results thus obtained help in the further calculations. The algorithm is computationally simple and inexpensive, and gives a fairly good approximation of fractance frequency response on the specified frequency band.     

Design of Barrages with Genetic Algorithm Based Embedded Simulation Optimization Approach

Barrages are hydraulic structures constructed across rivers to divert flow into irrigation canals or power generation channels. The most of these structures are founded on permeable foundation. The optimum cost of these structures is nonlinear function of factors that cause the seepage forces under the structure. There is, however, no procedure to ascertain the basic barrage parameters such as depth of sheet piles or cutoffs and the length and thickness of floor in a cost–effective manner. In this paper, a nonlinear optimization formulation (NLOF), which consists of an objective function of minimizing total cost, is solved using genetic algorithm (GA). The mathematical model that represents the subsurface flow is embedded in the NLOF. The applicability of the approach has been illustrated with a typical example of barrage profile. The results obtained in this study shows drastic cost savings when the proposed NLOF is solved using GA than that of using classical optimization technique and conventional method. A parametric analysis has also been performed to study the effect of varying soil and hydrological conditions on design parameters and on over all cost.     

Agile Spectrum Imaging: Programmable Wavelength Modulation for Cameras and Projectors

We advocate the use of quickly‐adjustable, computer‐controlled color spectra in photography, lighting and displays. We present an optical relay system that allows mechanical or electronic color spectrum control and use it to modify a conventional camera and projector. We use a diffraction grating to disperse the rays into different colors, and introduce a mask (or LCD/DMD) in the optical path to modulate the spectrum. We analyze the trade‐offs and limitations of this design, and demonstrate its use in a camera, projector and light source. We propose applications such as adaptive color primaries, metamer detection, scene contrast enhancement, photographing fluorescent objects, and high dynamic range photography using spectrum modulation.     

Mathematical model for quality cost optimization

Quality engineering uses robust design in order to improve quality by reducing the effects of variability. Variability of the product can be reduced by two stages. One is parameter design which is adjustable to the nominal value so that output is less sensitive to the cause of variability. Other one is tolerance design which is to reduce the tolerance in order to control variability. All costs incurred in a product life cycle can be divided into two categories—manufacturing cost before the sale to the customer and quality loss after the shipment of the product to the customer. It is very important to find the optimum tolerances for each of the characteristics. A balance between manufacturing cost and quality loss should be arrived at in the tolerance design for quality improvement and cost reduction. For the case of Nominal-The-Best, a mathematical model is developed in order to determine the optimum product tolerance and minimize the total cost which includes the manufacturing cost and the quality loss. Since the process capability index (C_pm) shows the balance of quality responsibility between the design and the manufacturing engineers, this is taken as the basis in developing the functional relationship between the variability of the product and the tolerance. Based on these relationships, the total cost of model can be expressed as a function of product tolerance from which the optimal tolerance limits can be found out. Finally, using this model a tolerance design approach that increases the quality and reduces the cost can be achieved in the early stages of the product process design stage itself.