Phase equilibria (LLE and VLE) of refining operations for enzymatic biodiesel production via quantum mechanical COSMO‐RS method

Phase equilibria, both liquid–liquid equilibria (LLE) and vapor‐liquid equilibria (VLE), are equally important in the refining operations of biodiesel production. Equilibrium distributions of components at the down‐processing of enzymatic ethanolysis reaction were investigated through quantum mechanical COnductor‐like Screening MOdel‐Real Solvent method with implemented vapor pressure equations. Due to the composite nature of fatty acid ethyl ester (FAEE) components as the biodiesel fuel, multicomponent predictive phase equilibria approach was applied for a model reaction system of refined soybean oil with 30% molar excess amount of ethanol. Simulation results for the LLE at 303 K were in significant agreement with reported experimental data. Minimum boiling azeotropes were found for FAEE‐glycerol binaries at isothermal (at 423 and 473K) and isobaric (at reduced pressures) VLE simulations. Similar results were also found at the VLE of glycerol purification operations for multicomponent real case simulations. The feasibilities of simple and rigorous unit operations were also pointed up in this study. © 2012 American Institute of Chemical Engineers AIChE J, 2012     

Comparative Evaluation of Intestinal Nitric Oxide in Embryonic Zebrafish Exposed to Metal Oxide Nanoparticles

Nanoparticle (NP) exposure may induce oxidative stress through generation of reactive oxygen and nitrogen species, which can lead to cellular and tissue damage. The digestive system is one of the initial organs affected by NP exposure. Here, it is demonstrated that exposure to metal oxide NPs induces differential changes in zebrafish intestinal NO concentrations. Intestinal NO concentrations are quantified electrochemically with a carbon fiber microelectrode inserted in the intestine of live embryos. Specificity of the electrochemical signals is demonstrated by NO‐specific pharmacological manipulations and the results are correlated with the 4,5‐diaminofluorescein‐diacetate (DAF‐FM‐DA). NPs are demonstrated to either induce or reduce physiological NO levels depending on their redox reactivity, type and dose. NO level is altered following exposure of zebrafish embryos to CuO and CeO₂ NPs at various stages and concentrations. CuO NPs increase NO concentration, suggesting an intestinal oxidative damage. In contrast, low CeO₂ NP concentration exposure significantly reduces NO levels, suggesting NO scavenging activity. However, high concentration exposure results in increased NO. Alterations in NO concentration suggest changes in intestinal physiology and oxidative stress, which will ultimately correspond to NPs toxicity. This work also demonstrates the use of electrochemistry to monitor in vivo changes of NO within zebrafish organs.     

Recent advances in modelling of metal machining processes

During the last few decades, there has been significant progress in developing industry-driven predictive models for machining operations. This paper presents the state-of-the-art in predictive performance models for machining, and identifies the strengths and weaknesses of current models. This includes a critical assessment of the relevant modelling techniques and their applicability and/or limitations for the prediction of the complex machining operations performed in industry. This paper includes contributions from academia and industry, and is expected to serve as a comprehensive report of recent progress, as well as a roadmap for future directions. Process models often target the prediction of fundamental variables such as stresses, strains, strain-rates, temperatures etc. However, to be useful to industry, these variables must be correlated to performance measures: product quality (accuracy, dimensional tolerances, finish, etc.), surface and subsurface integrity, tool-wear, chip-form/breakability, burr formation, machine stability, etc. The adoption of machining models by industry critically depends on the capability of a model to make this link and predict machining performance. Therefore, this paper would identify and discuss several key research topics closely associated with predictive model development for machining operations, primarily targeting industry applications.     

A study on cutting errors in the tooth profiles of the spur gears manufactured in CNC milling machine

In this study, the cutting errors in the tooth profile of the spur gears which are manufactured by end mill according to radial cutting method in three-axis CNC milling machine are investigated. According to this method, a mathematical approach in order to investigate the cutting errors of the tooth profile is presented. Then, mathematical expressions determining the error quantity in the tooth profile curve are derived by using this approach, and a programme is developed in the MATLAB. Parameters such as module (m), tooth number (N), pressure angle (?) and cutting angle (α _m ) in the programme are changed, and the cutting errors of the involute tooth profile according to the obtained results are interpreted graphically. As a result, it is seen that the cutting errors in the involute curve increase according to increments of m, N, ? and α _m .     

The Effects of Na2SiO3 Concentration on the Properties of Plasma Electrolytic Oxidation Coatings on 6060 Aluminum Alloy

In this study, 6060 aluminum alloy was coated by plasma electrolytic oxidation (PEO) process. The effect of sodium silicate concentration (A solution-7.5?g/L??B solution-15?g/L) on various morphological properties and corrosion resistance of the surface was investigated. The correlation between the microwave sintering of 6060 aluminum alloy coated by PEO and non-microwave sintering of 6060 aluminum alloy properties are discussed. Detailed estimation of the quality of the coated metal surface was performed by additional testing of chemical compositions by EDS, crystalline structure of the films was examined using x-ray diffraction (XRD) and scanning electron microscope (SEM). The results showed that the oxidation layer was of typical morphology for the PEO process. The porosity amount of 6060 aluminum sample coated with 15?g/L was obtained higher than that of 7.5?g/L. In addition to, the porosity of all coated samples was decreased with increasing microwave sintering time. The corrosion resistance of coated samples with microwave sintering process was better than non-microwave sintering of 6060 aluminum alloy.     

Modified material constitutive models for serrated chip formation simulations and experimental validation in machining of titanium alloy Ti–6Al–4V

Titanium alloys present superior properties such as high strength-to-weight ratio and resistance to corrosion but, possess poor machinability. In this study, influence of material constitutive models and elastic–viscoplastic finite element formulation on serrated chip formation for modeling of machining Ti–6Al–4V titanium alloy is investigated. Temperature-dependent flow softening based modified material models are proposed where flow softening phenomenon, strain hardening and thermal softening effects and their interactions are coupled. Orthogonal cutting experiments have been conducted with uncoated carbide (WC/Co) and TiAlN coated carbide cutting tools. Temperature-dependent flow softening parameters are validated on a set of experimental data by using measured cutting forces and chip morphology. Finite Element simulations are validated with experimental results at two different rake angles, three different undeformed chip thickness values and two different cutting speeds. The results reveal that material flow stress and finite element formulation greatly affects not only chip formation mechanism but also forces and temperatures predicted. Chip formation process for adiabatic shearing in machining Ti–6Al–4V alloy is successfully simulated using finite element models without implementing damage models.     

Complex-exponential representation of time-domain response of a one-mode resonator

Time-domain response of a one-mode resonator is investigated by using a complex-exponential representation of the time-domain impulse response. The transient response of a resonator has calculated for a short incident pulse which has rectangular form and the radio frequency filling. The convolution integral has been analytically carried out and two solutions for the time histories of the transient response of the resonator have been found. They are the early-time and late-time portions of the signal. The behaviour of amplitude and frequency of the transient response of the electrodynamical structure under consideration is studied.     

Antimicrobial resistance of bacterial flora associated with bovine products in South Africa.

The administration of subtherapeutic doses of antibiotics to livestock introduces selective pressures that may lead to the emergence and dissemination of resistant bacteria. This study determined the antibiotic-resistance spectra of the microbial flora found on freshly slaughtered and retail beef and in unpasteurized and pasteurized packaged milk. Staphylococci, Enterobacteriaeae, and isolates from total aerobic plate counts were tested for resistance to vancomycin, streptomycin, methicillin, tetracycline, and gentamicin using the disc diffusion susceptibility test and resistance to penicillin was determined by using oxacillin. A larger proportion of resistance to most antibiotics, except for vancomycin, was displayed by isolates from abattoir samples. The incidence of multiple antibiotic resistance (MAR) pathogenic bacteria is also higher in the abattoir. Resistance genes lost because of lack of selective pressure or resistant flora being replaced by more sensitive flora during processing is the reason for the lower incidence of MAR pathogenic bacteria among retail samples. These resistant bacteria can be transferred to humans through the consumption of rare or raw beef and unpasteurized milk, thus rendering the resultant food-related infections difficult to treat. The present findings clearly demonstrate that antibiotic-resistant bacteria in beef and milk pose a serious problem in South Africa.     

Symbolic Regression Based Extreme Learning Machine Models for System Identification

Neural Processing Letters - Reproducible machine learning models with less number of parameters and fast optimization are preferred in embedded system design for the applications of artificial...