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.     

Studies on high density polyethylene (HDPE) functionalized by ultraviolet irradiation and its application

The structure and properties of high density polyethylene (HDPE) functionalized by ultraviolet irradiation at different light intensities in air were studied by electron analysis, FTIR spectroscopy, contact angle with water, differential scanning calorimetry and mechanical properties measurement. The results show that oxygen‐containing groups such as C?O, C—O and C(?O)O were introduced onto the molecular chain of HDPE following irradiation, and the rate and efficiency of HDPE functionalization increased with enhancement of irradiation intensity. After irradiation, the melting temperature, contact angle with water and notched impact strength of HDPE decreased, the degree of crystallinity increased, and their variation amplitude increased with irradiation intensity. Compared with HDPE, the yield strength of HDPE irradiated at lower light intensity (32 W m^?2 and 45 W m^?2) increases monotonically with irradiation time, and the yield strength of HDPE irradiated at higher light intensity (78 W m^?2) increases up to 48 h and then decreased with further increase in irradiation time. The irradiated HDPE behaved as a compatibilizer in HDPE/polycarbonate (PC) blends, and the interface bonding between HDPE and PC was ameliorated. After adding 20 wt% HDPE irradiated at 78 W m^?2 irradiation intensity for 24 h to HDPE/PC blends, the tensile yield strength and notched Izod impact strength of the blend were increased from 26.3 MPa and 51 J m^?1 to 30.2 MPa and 158 J m^?1, respectively. Copyright © 2003 Society of Chemical Industry     

An introduction of the condition class space with continuous value discretization and rough set theory

The granularity of an information system has an incumbent effect on the efficacy of the analysis from many machine learning algorithms. An information system contains a universe of objects characterized and categorized by condition and decision attributes. To manage the concomitant granularity, a level of continuous value discretization (CVD) is often undertaken. In the case of the rough set theory (RST) methodology for object classification, the granularity contributes to the grouping of objects into condition classes with the same condition attribute values. This article exposits the effect of a level of CVD on the subsequent condition classes constructed, with the introduction of the condition class space—the domain within which the condition classes exist. This domain elucidates the association of the condition classes to the related decision outcomes—reflecting the inexactness incumbent when a level of CVD is undertaken. A series of measures is defined that quantify this association. Throughout this study and without loss of generality, the findings are made through the RST methodology. This further offers a novel exposition of the relationship between all the condition attributes and the RST‐related reducts (subsets of condition attributes). © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 173–191, 2006.     

Fault detection for control of wastewater treatment plants.

Interest in real-time model-based control is increasing as more and more facilities are being asked to meet stricter effluent requirements while at the same time minimizing costs. It has been identified that biological process models and automated process control technologies are being used at wastewater treatments plants throughout the world and that great potential for optimising biotreatment may exist with the integration of these two technology areas. According to our experience, wastewater treatment plants are indeed looking for ways to successfully integrate their modelling knowledge into their process control structure; however, there are practical aspects of this integration that must be addressed if the benefits of this integration are to be realised. This paper discusses the practical aspects of monitoring, filtering and analysing real sensor data with an aim to produce a reliable real-time data stream that might be used within a model-based control structure. Several real case study examples are briefly discussed in this paper.     

Comparison of total and faecal coliforms as faecal indicator in eutrophicated surface water.

The aim of this study was to evaluate the use of total coliforms (TC) and faecal coliforms (FC) using a membrane filtration method for precise monitoring of faecal pollution in Korean surface water. The samples were collected in Korea from both main rivers and their tributaries. Presumptive TC * FC were enumerated. The ratios of presumptive FC to TC were not constant, but varied widely, and TC were difficult to enumerate because of overgrowth by background colonies. For FC this was not the case. Seven hundred and three purified strains of presumptive TC * FC and their background colonies were biotyped using API 20E. Among 272 presumptive TC, non-faecal related species, Aeromonas hydrophila dominated (34.6%) and E. coli accounted for only 5.1%. In contrast, E. coli made up 89% of the 209 presumptive FC. Furthermore, of 164 background colonies on Endo Agar LES, 54.9% was A. hydrophila, while background colonies on m-FC Agar were few (58 strains), and despite their atypical colony appearance, most of them were biotyped as enteric bacteria. These results reveal that the detection of FC rather than TC using m-FC Agar is more appropriate for faecal pollution monitoring in eutrophicated surface water located in a temperate region.     

Recovery of gold cyanide using inherently conducting polymers

Removal of gold from basic solutions containing [Au(CN)₂]^? has been demonstrated using the inherently conducting polymer polypyrrole. Polymers containing sulfonated aromatic dopants have been found to display a significant ability to remove gold from such solutions. Experiments performed in solutions containing both gold and copper cyanide complexes indicate that the recovery process is not highly selective. However, the polypyrroles used display significantly faster rates of gold recovery than activated carbon. © 2003 Society of Chemical Industry     

Monte Carlo simulation of gas phase polymerization of 1,3‐butadiene. Part II: Kinetics optimization and confirmation

Studies on the deactivations and initiations of gas phase polymerizations of 1,3‐butadiene have been achieved by Monte Carlo simulation. Initiation and deactivation control the reaction before and after the peak of the polymerization rate, respectively. The influence of polymerization temperature has been studied. Monte Carlo modeling of polymerization kinetics and mechanism was confirmed by the agreement of experimental data and simulation results of polymerizations run with a temporary evacuation of monomer. The balance of catalysts and active chains is established by both initiation and chain transfer reactions with cocatalyst, which causes a ‘pseudo‐stability’ stage. © 2003 Society of Chemical Industry     

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.