Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.     

Benchmark simulation Model no 2 in Matlab-simulink: towards plant-wide WWTP control strategy evaluation.

In this paper, implementation of the Benchmark Simulation Model No 2 (BSM2) within Matlab-Simulink is presented. The BSM2 is developed for plant-wide WWTP control strategy evaluation on a long-term basis. It consists of a pre-treatment process, an activated sludge process and sludge treatment processes. Extended evaluation criteria are proposed for plant-wide control strategy assessment. Default open-loop and closed-loop strategies are also proposed to be used as references with which to compare other control strategies. Simulations indicate that the BM2 is an appropriate tool for plant-wide control strategy evaluation.     

Membrane separation of indigenous noroviruses from sewage sludge and treated wastewater.

In this study, feasibility of membrane separation for the removal of indigenous noroviruses (NVs) is evaluated. The indigenous NV gene was never detected from ultrafiltration (UF) permeates of sewage sludge and treated wastewater. Indigenous NV gene was also not detected from permeates of sewage sludge and treated wastewater by microfiltration (MF) with a pore size of 0.1 microm (MF0.1). Even though the pore size of MF (0.1 microm) was much larger than the diameter of virus particle (approximately 30-40nm), more than 4-log10 reduction value (LRV) at maximum was achieved by membrane separation with MF0.1. NV genes were often detected from permeates of sewage sludge and treated wastewater by MF with a pore size of 0.45 microm (MF0.45), although the maximum log10 reduction values were more than 3.59 for sewage sludge and more than 2.90 for treated wastewater. It is important to verify factors determining the removal efficiency of viruses with MF membranes.     

Understanding silica-supported metal catalysts: Pd/silica as a case study

Supported metal catalysts, particularly noble metals supported on SiO₂, have attracted considerable attention due to the importance of the silica–metal interface in heterogeneous catalysis and in electronic device fabrication. Several important issues, e.g., the stability of the metal–oxide interface at working temperatures and pressures, are not well-understood. In this review, the present status of our understanding of the metal–silica interface is reviewed. Recent results of model studies in our laboratories on Pd/SiO₂/Mo(1 1 2) using LEED, AES and STM are reported. In this work, epitaxial, ultrathin, well-ordered SiO₂ films were grown on a Mo(1 1 2) substrate to circumvent complications that frequently arise from the silica–silicon interface present in silica thin films grown on silicon.     

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.     

TEM Studies of High Temperature Corrosion Behaviour of TiAl Intermetallics with Surface Modifications

The oxidation/sulphidation behaviour of a Ti‐46.7Al‐1.9W‐0.5Si alloy with a TiAl₃ diffusion coating was studied in an environment of H₂/H₂S/H₂O at 850^oC. The kinetic results demonstrate that the TiAl₃ coating significantly increased the high temperature corrosion resistance of Ti‐46.7Al‐1.9W‐0.5Si. The SEM, EDX, XRD and TEM analysis reveals that the formation of an Al₂O₃ scale on the surface of the TiAl₃‐coated sample was responsible for the enhancement of the corroison resistance. The Ti‐46.7Al‐1.9W‐0.5Si alloy was also modified by Nb ion implantation. The Nb ion implanted and as received sampels were subjected to cyclic oxidation in an open air at 800^oC. The Nb ion implantation not only increased the oxidation resistance but also substantially improved the adhesion of scale to the substrate.     

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.