An artificial neural network approach on parametric optimization of laser micro-machining of die-steel

In the present research, laser micro machining (LMM) of tungsten-molybdenum general purpose high speed steel (Rex M2) has been studied. Selection of optimum machining parameter combinations for obtaining higher depth of groove and smaller height of recast layer is a challenging task in LMM due to the presence of a large number of process variables. There is no perfect combination of parameters which can simultaneously result in both the highest depth of groove and lowest height of recast layer. This paper presents an attempt to develop a strategy for predicting the optimum machining parameter setting for the generation of the maximum depth of groove with minimum height of recast layer. A feed forward back-propagation neural network has been developed to model the machining process. The model, after proper training, is capable of predicting the response parameters as a function of four different control parameters. Experimental results demonstrate that the machining model is suitable and the optimization strategy satisfies practical requirements. The developed model has been found to be quite unique, powerful and flexible.     

Study of thermal effects and self-heating phenomena in planar power SOI MOS transistors

Heat removal problems, thermal effects, and self-heating phenomena occurring during operation of planar power SOI MOS transistors are considered. Using device-technological simulating methods, the transistor characteristics and safe operation range were studied. It was shown that limitations of the safe operation range are mostly associated with structure self-heating rather than with the parasitic bipolar transistor.     

CFD Prediction of Flow and Homogenization in a Stirred Vessel: Part I Vessel with One and Two Impellers

A simulation of flow field and tracer homogenization was performed using the commercial CFD software FLUENT 6.1. The aim is to investigate the potential of CFD software to predict concentration distribution of added tracer in cylindrical vessels. The calculated results – dimensionless velocity profiles, power and pumping numbers, dimensionless concentration curves, and mixing times – were compared with experiments in stirred vessels. In Part I, the study was performed for vessels agitated by one or two impellers on a centric shaft. Two different impellers were used – a 6‐bladed 45° pitched blade turbine and a standard Rushton turbine. The standard k‐? turbulence model and multiple reference frames method were used for the simulations. The influence of the grid type was also investigated; three types of grid – a structured, unstructured and a special user‐defined grid – were studied.     

Preparation and characterization of chitosan‐based dispersions

Complexation of chitosan in aqueous solutions by low molecular weight electrolytes is one of the simplest methods for the preparation of aqueous chitosan dispersions. In this work, the influence of storage time, sulfate concentration, method of preparation and surfactant content on some properties of the resultant chitosan dispersions (turbidity, viscosity and zeta potential) was analyzed. Turbidimetry was adequate to monitor the formation of particles, while viscometry was suitable to monitor changes in the dispersing phase. An analysis of the properties of these systems, mainly in terms of particle–particle and macromolecule–macromolecule interactions was carried out. Copyright © 2004 Society of Chemical Industry     

Evaluation of ProKappa

ProKappa is an expert system tool kit developed by IntelliCorp in C using X-Windows for graphical interface. The SUN 3 or 4 version costs $9995/£7000 and $2595/£1800 for the interactive C environment.
This review covers ProKappa version 1.1, installed on a colour SUN SPARC Station 1 with the minimum recommended values of 12 Mb of memory and 30 Mb of swap space.
IntelliCorp can be contacted in the USA at 1975 El Camino Real West, Mountain View, CA 94040-2216 (+1 (415) 965-5500) and in the UK at 10 Jewry Street, Winchester, Hampshire SO23 8RZ (+44 (0)962 735348).     

A fine-grain architecture for relational database aggregationoperations

The design and simulation of a bit-sliced processor for relational database aggregation functions, are discussed. The processor, which addresses an important, computationally expensive problem in database computers, takes two tuples as input (one bit at a time) and returns two bits as output every clock cycle. A larger aggregation unit uses a number of identical slice processors, connected according to odd-even network topology, to achieve improved performance on a parallel pipelined processor. The data processing time is completely overlapped with the input and output of data to and from the unit. The design is independent of the tuple size, and since a bit-serial computation is used, the system requires limited interconnection