Nonlinear control of the doubly-fed induction generator in wind power systems

This paper describes the models of a wind power system, such as the turbine, generator, power electronics converters and controllers, with the aim to control the generation of wind power in order to maximize the generated power with the lowest possible impact in the grid voltage and frequency during normal operation and under the occurrence of faults. The presented work considers a wind power system equipped with the doubly-fed induction generator and a vector-controlled converter connected between the rotor and the grid. The paper presents comparative results between proportional-integral controllers and neural networks based controllers, showing that better dynamic characteristics can be obtained using neural networks based controllers.     

Analysis of the particle swarm algorithm in the optimization of a three-phase slurry catalytic reactor

The Particle Swarm Optimization (PSO) method was employed to optimize an industrial chemical process characterized by being difficult to be optimized by conventional deterministic methods. The chemical process is a three phase catalytic slurry reactor (tubular geometry) in which the reaction of the hydrogenation of o-cresol producing 2-methyl-cyclohexanol is carried out. The optimization problem was formulated considering as input variables the operating conditions of the reactor and as objective function the maximization of productivity, subject to the environmental constraint of conversion. The process was represented by a multivariable non-linear rigorous mathematical model and in order to solve the optimization problem, the performance of the PSO algorithm was evaluated considering four sets of parameters values suggested by the literature. PSO demonstrated to be efficient and robust to solve the constrained optimization problem, independently of the values of the PSO parameters. The solution of the rigorous mathematical model of the reactor was associated with a high computational burden, and although the PSO algorithm presented high rate of convergence, the attempt to make possible the optimization in a timeframe suitable to real time applications failed because the algorithm lost robustness (fraction of the number of runs the algorithm reached the optimization goal) when run with a reduced number of function evaluations. Therefore, if this type of application is desired, simplified mathematical models with fast and simple numerical methods must be preferred.     

Optimisation of a continuous flash fermentation for butanol production using the response surface methodology

Factorial design and response surface techniques were used in combination with mathematical modelling and computational simulation to optimise an innovative industrial bioprocess, the production of biobutanol employing the flash fermentation technology. A parametric analysis performed by means of a full factorial design at two levels determined the influence of operating variables on butanol yield and productivity. A second set of simulations were carried out based on the central composite rotatable design. This procedure generated simplified statistical models that describe butanol yield and productivity as functions of the significant operating variables. From these models, response surfaces were obtained and used to optimise the process. For a range of substrate concentration from 130 to 180 g/l, the optimum operating ranges ensure butanol productivity between 7.0 and 8.0 g/l h, butanol yield between 19 and 22%, substrate conversion above 90% and final butanol concentration around 25 g/l.     

Phosphated crosslinked pectin as a potential excipient for specific drug delivery: preparation and physicochemical characterization

Pectin was chemically modified with different amounts of trisodium trimetaphosphate (STMP) in aqueous solution (pH = 12), thereby giving a material with reduced water solubility. The physiochemical characterization of this new material was carried out through Fourier transform infrared and thermogravimetric analyses. Phosphated pectin (Pect‐STMP) together with prebiotic (oligosaccharide) were incorporated into an aqueous dispersion of polymethacrylate (Eudragit^® RS 30 D) in order to obtain free films using a casting process (50 °C) on a Teflon plate. The free films were evaluated using water vapour transmission, average swelling index in simulated gastric fluid (SGF) and simulated intestinal fluid, scanning electron microscopy and a diffusion study with theophylline in buffer solution with and without pectinolytic enzyme. The results suggest that the new material can be used in the coating process for oral solid‐reservoir systems, to prevent the premature release of drugs in SGF (pH = 1.2). Furthermore, the presence of both Pect‐STMP and oligosaccharide favours the specific degradation of the pellicle by the action of the enzymes produced by colonic microflora. The material obtained in this work has the potential to be applied in devices for drug delivery in the colon, making possible modified release of drugs. Nevertheless, subsequent colon‐specific experiments in vivo need to be carried out in order to confirm the possible application of this new material. Copyright © 2009 Society of Chemical Industry     

Distribution and bioavailability of copper in farm effluent

Effluent and sludge samples from a number of dairy and piggery units in the North Island of New Zealand were collected and analysed for free ionic-copper (Cu(2+)) and organically-complexed Cu. The bioavailability of sludge-Cu was examined using microbial respiration and plant growth experiments. Microbial respiration was measured at various levels of Cu (0-1000 mg kg(-1)), added as copper sulfate (CuSO(4)) and sludge-Cu, using a Gilson differential respirometer. A glass house experiment was conducted to examine the transformation of Cu in soils and its subsequent uptake by ryegrass pasture. Three Cu sources were used that included fast-release CuSO(4), slow-release copper oxide (CuO) and Cu-enriched sludge. The pasture samples were analysed for Cu concentration. The transformation of Cu in the soil was monitored by analysing the soil samples for various fractions of Cu. The effluent and sludge samples collected from farms which regularly used Cu to treat lameness in dairy cattle and as a growth promoter in swine contained higher concentration of Cu. The total Cu concentration ranged from approximately 0.1 to 1.55 mg l(-1) and from 0.5 to 10.5 mg l(-1) in the piggery and diary effluent, respectively. The corresponding values for the sludge samples were 3.0-526 and 25-105 mg kg(-1). Most of the Cu in both the effluent and solid sludge material was organically complexed. The respiration measurements indicated that sludge-Cu was less toxic to soil microbial activity than CuSO(4). The results from the glass house experiment indicated that increasing the level of Cu applied through fertilisers and sludge increased Cu concentration in plants. At the same rate of application, plants took up less Cu from sludge and CuO than from CuSO(4). There was, however, a greater translocation of Cu from root to shoot at the highest rate of Cu through sludge application. The Cu fractionation study indicated that there was greater accumulation of organic bound Cu in the sludge-treated soil than the fertiliser-treated soil.     

Numerical investigation of several physical and geometric parameters in the natural convection into trapezoidal cavities

Natural convection in trapezoidal cavities, especially those with two internal baffles in conjunction with an insulated floor, inclined top surface, and isothermal left-heated and isothermal right-cooled vertical walls, has been investigated numerically using the Element based Finite Volume Method (EbFVM). In numerical simulations, the effect of three inclination angles of the upper surface as well as the effect of the Rayleigh number (Ra), the Prandtl number (Pr), and the baffle’s height (H_b) on the stream functions, temperature profiles, and local and average Nusselt numbers has been investigated. A parametric study was performed for a wide range of Ra numbers (10³ ? Ra ? 10⁶) H_b heights (H_b = H¹/3, 2H¹/3, and H¹), Pr numbers (Pr = 0.7, 10 and 130), and top angle (θ) ranges from 10 to 20. A correlation for the average Nusselt number in terms of Pr and Ra numbers, and the inclination of the upper surface of the cavity is proposed for each baffle height investigated.     

Role of Draw Rate and Molecular Weight when Electrospun Nanofibers are Post-Drawn with Residual Solvent

The postdrawing process is poorly understood for polymer nanofibers due to the difficulty of manipulating nanofiber structures. Here, an angled track system facilitates postdrawing of individual nanofibers with control of parameters including molecular weight, draw rate, draw ratio, and solvent evaporation time. In this study, the effects of molecular weight, draw rate, and relative residual solvent content on final nanofiber properties are investigated. Molecular weight is first investigated to clarify any influence polymer chain length can have on drawing in facilitating or hindering chain extensibility. Polyacrylonitrile nanofibers with 50 and 150 kDa molecular weights behave similarly with postdrawing resulting in reduced diameters and enhanced mechanics. Since solvent quantity during drawing is a time sensitive component it is meaningful to assess the impact of draw rate on the chemical and structural makeup of postdrawn fibers. Chemical bond vibrations and chain orientation are sensitive to draw rate when polycaprolactone nanofibers are dried for 3 minutes prior to postdrawing, but this dependency to draw rate is not observed when fibers are postdrawn immediately upon collection. These findings demonstrate that the amount of retained solvent at collection is relevant to this postprocessing approach, and highlights the dynamics of solvent evaporation during postdrawing.     

A Smart Deep Convolutional Neural Network for Real-Time Surface Inspection

A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of the proposed model are: small size and low computational burden. The model is 10 to 20 times smaller when compared to other networks designed for the same task, and more than 700 times smaller than general networks. Also, the number of floating-point operations for a prediction is about 50 times lower than the ones used for similar tasks. Despite its small size, the proposed model achieved near-perfect accuracy on a public dataset of 1800 images of six types of steel rolling defects.