Mass Transfer in a Flat Gas/Liquid Interface using non‐Newtonian Media

Gas/liquid mass transfer has been investigated using a stirred vessel gas/liquid contactor using non‐Newtonian media and carbon dioxide as absorbent and gas phase, respectively. The volumetric mass transfer coefficients at different operational variables have been determined. Non‐Newtonian media (liquid phase) were prepared as aqueous solutions of sodium carboxymethyl cellulose salt. The influence of the rheological properties, polymer concentration, stirring rate, and gas flow rate on mass transfer was studied for these liquid phases. Kinematic viscosity and density experimental data were used to calculate the average molecular weight corresponding to the polymer employed. The Ostwald model has been used to fit the rheological behavior of aqueous solutions of the polymer employed as absorbent phase. Reasonably good agreement was found between the predictions of the proposed models and the experimental data of mass transfer coefficients.     

Switched-Current Filters Revisited: Square-Root Domain Sampled-Data Filters

In this brief, the well-known switched-current (SI) filtering technique is revisited using the concept of the square-root domain (SRD) filtering. It is proved that SI filters are a subclass of the SRD filters, where sampled-data signal processing is performed. This is achieved by considering typical lossless and lossy SRD sampled-data integrator configurations, using a set of complementary SRD operators which are based on the quadratic I-V relationship of MOS transistor operated in the saturation. Circuit examples are given, where linear-domain integrator and third-order filter configurations were derived using appropriate SRD sampled-data building blocks     

Kinetic Characteristics of Amino Acid Salt Crystallization in Methanol‐Water System

Nucleation and growth mechanisms and kinetics of crystals of an amino acid salt were investigated in a methanol‐water system by measuring and evaluating the induction time as a function of the supersaturation ratio and temperature in batch salting out crystallization experiments. Discrimination between the possible crystallization mechanisms, and estimation of the kinetic parameters were carried out using nonlinear parameter identification. The results concerning the growth mechanism obtained were checked additionally by measuring the induction time as a function of number density of seed crystals.     

Microscale Patterning of Mesoscopic PZN-PT Single Crystal Films by Crystal ion Slicing and Laser-Induced Etching

Advances in the fabrication of solid-solution single crystal relaxor ferroelectrics have made it possible to produce highly efficient piezoelectric crystals, and have attracted renewed interest in the use of these crystals for a new generation of piezoelectric transducers, actuators and sensors. Of particular interest is their incorporation into micro-electromechanical systems (MEMS). In this paper we report on the laser-induced wet chemical etching of lead zinc niobate-lead titanate (PZN-PT) in hydrochloric acid (HCl). Argon-ion laser radiation at power levels up to 4 W is focused to a spot diameter of about 15μm and results in the chemical etching of grooves at patterning speeds up to 5μm/sec. Crystal ion slicing, an ion-implant-based film separation technique, is used in combination with laser etching to form 5 to 10μm-thick patterned and freestanding films for incorporation into micro-electromechanical devices.     

Valorisation of waste fractions from autohydrolysis of selected lignocellulosic materials

Non‐isothermal processing of lignocellulosic materials in aqueous media (autohydrolysis reaction) under mild conditions leads to solutions containing valuable chemicals (oligosaccharides, sugars and acetic acid) and other, undesired, compounds (belonging to the extractive and acid‐soluble lignin fractions) which have to be removed in further purification treatments. Liquors obtained by non‐isothermal autohydrolysis of Eucalyptus globulus wood and corncobs under a variety of operational conditions were extracted with ethyl acetate in order to remove non‐saccharide components, and the suitability of the fraction dissolved in the organic phase was assayed for possible utilisation as an antioxidant. The yield and antioxidant activity of ethyl acetate extracts (measured by the α,α‐diphenyl‐β‐picrylhydrazyl (DPPH) radical scavenging capacity) showed a strong dependence on the autohydrolysis conditions. The antioxidant activity of extracts obtained under selected operational conditions compared well with synthetic antioxidants. © 2003 Society of Chemical Industry     

Synthesis of Rice Processing Plants. I. Development of Simplified Models

This article, the first of three articles on the synthesis of rice processing plants, focuses on the development of simplified mathematical models necessary for use in optimizing rice processing plants. The second concentrates on the optimal synthesis of a rice plant and the third on the sensitivity of the optimization to uncertainty in model parameters. Existing models for rice processing unit operations are not suitable for flowsheet optimization and new models need to be developed to overcome numerical difficulties that occur in optimization applications, specifically in mixed integer nonlinear programming (MINLP) applications. Simplified models of the drying, cooling, and tempering units are developed. In addition head rice yield models, used as a quality indicator, energy consumption, and economic models were also developed. Naturally, the new models exhibit some mismatch with respect to the existing models from which they were developed. However, a sensitivity analysis, presented in Part III, has shown that the optimal flowsheet structure was not sensitive to a lack of fit between the simplified and complex models. The simplified models were found adequate to be appropriate for use at the synthesis stage.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.