Case base reduction using solution-space metrics

In this paper we propose a case base reduction technique which uses a metric defined on the solution space. The technique utilises the Generalised Shepard Nearest Neighbour (GSNN) algorithm to estimate nominal or real valued solutions in case bases with solution space metrics. An overview of GSNN and a generalised reduction technique, which subsumes some existing decremental methods, such as the Shrink algorithm, are presented. The reduction technique is given for case bases in terms of a measure of the importance of each case to the predictive power of the case base. A trial test is performed on two case bases of different kinds, with several metrics proposed in the solution space. The tests show that GSNN can out-perform standard nearest neighbour methods on this set. Further test results show that a caseremoval order proposed based on a GSNN error function can produce a sparse case base with good predictive power.

Computational modelling of bubbles, droplets and particles in metals reduction and refining

The CFD modelling of metals reduction processes particularly always seems to involve the interaction of liquid metals, a gas (often air) top space, liquid droplets in the top space and injection of both solid particles and gaseous bubbles into the bath. These phases all interact and exhange mass, momentum and energy. Often it is the extent to which these multi-phase phemomena can be effectively captured within the CFD model which determines whether or not a tool of genuine use to the target industry sector can constructed. In this paper we discuss these issues in the context of two problems - one involving the injection of sparging gases into a steel continuous caster and the other based on the development of a novel process for aluminium electrolysis.

Electronic packaging and reduction in modelling time using domain decomposition

The domain decomposition method is directed to electronic packaging simulation in this article. The objective is to address the entire simulation process chain, to alleviate user interactions where they are heavy to mechanization by component approach to streamline the model simulation process.

Nonlinear MHD stability of aluminium reduction cells

An industrial electrolysis cell used to produce primary aluminium is sensitive to waves at the interface of liquid aluminium and electrolyte. The interface waves are similar to stratified sea layers [1], but the penetrating electric current and the associated magnetic field are intricately involved in the oscillation process, and the observed wave frequencies are shifted from the purely hydrodynamic ones [2]. The interface stability problem is of great practical importance because the electrolytic aluminium production is a major electrical energy consumer, and it is related to environmental pollution rate. The stability analysis was started in [3] and a short summary of the main developments is given in [2]. Important aspects of the multiple mode interaction have been introduced in [4], and a widely used linear friction law first applied in [5]. In [6] a systematic perturbation expansion is developed for the fluid dynamics and electric current problems permitting reduction of the three-dimensional problem to a two dimensional one. The procedure is more generally known as “shallow water approximation” which can be extended for the case of weakly non-linear and dispersive waves. The Boussinesq formulation permits to generalise the problem for non-unidirectionally propagating waves accounting for side walls and for a two fluid layer interface [1]. Attempts to extend the electrolytic cell wave modelling to the weakly nonlinear case have started in [7] where the basic equations are derived, including the nonlinearity and linear dispersion terms. An alternative approach for the nonlinear numerical simulation for an electrolysis cell wave evolution is attempted in [8 and references there], yet, omitting the dispersion terms and without a proper account for the dissipation, the model can predict unstable waves growth only. The present paper contains a generalisation of the previous non linear wave equations [7] by accounting for the turbulent horizontal circulation flows in the two fluid layers. The inclusion of the turbulence model is essential in order to explain the small amplitude self-sustained oscillations of the liquid metal surface observed in real cells, known as “MHD noise”. The fluid dynamic model is coupled to the extended electromagnetic simulation including not only the fluid layers, but the whole bus bar circuit and the ferromagnetic effects [9].

Computational modelling of bubbles, droplets and particles in metals reduction and refining

A multi-phase framework is typically required for the CFD modelling of metals reduction processes. Such processes typically involve the interaction of liquid metals, a gas (often air) top space, liquid droplets in the top space and injection of both solid particles and gaseous bubbles into the bath. The exchange of mass, momentum and energy between the phases is fundamental to these processes. Multi-phase algorithms are complex and can be unreliable in terms of either or both convergence behaviour or in the extent to which the physics is captured. In this contribution, we discuss these multi-phase flow issues and describe an example of each of the main “single phase” approaches to modelling this class of problems (i.e., Eulerian–Lagrangian and Eulerian–Eulerian). Their utility is illustrated in the context of two problems – one involving the injection of sparging gases into a steel continuous slab caster and the other based on the development of a novel process for aluminium electrolysis. In the steel caster, the coupling of the Lagrangian tracking of the gas phase with the continuum enables the simulation of the transient motion of the metal–flux interface. The model of the electrolysis process employs a novel method for the calculation of slip velocities of oxygen bubbles, resulting from the dissolution of alumina, which allows the efficiency of the process to be predicted.

Scalable and efficient graph colouring in 3 dimensions using emergence engineering principles

This paper describes ways in which emergence engineering principles can be applied to the development of distributed applications. A distributed solution to the graph-colouring problem is used as a vehicle to illustrate some novel techniques. Each node acts autonomously to colour itself based only on its local view of its neighbourhood, and following a simple set of carefully tuned rules. Randomness breaks symmetry and thus enhances stability. The algorithm has been developed to enable self-configuration in wireless sensor networks, and to reflect real-world configurations the algorithm operates with 3 dimensional topologies (reflecting the propagation of radio waves and the placement of sensors in buildings, bridge structures etc.). The algorithm’s performance is evaluated and results presented. It is shown to be simultaneously highly stable and scalable whilst achieving low convergence times. The use of eavesdropping gives rise to low interaction complexity and high efficiency in terms of the communication overheads.

Aqueous solution of anionic surfactants mixed with soils show a synergistic reduction in surface tension

Water retention and transport in soils is dependent upon the surface tension of the aqueous phase. Surfactants present in aqueous solution reduce the surface tension of aqueous phase. In soil–water systems, this can result in water drainage and reductions in field capacity and hydraulic conductivity. In this investigation, the surface tension of surfactant solutions mixed with soil—in a constant fixed ratio—was measured as a function of surfactant concentration. Two anionic surfactants were used: sodium dodecyl sulphate and sodium bis (2-ethylhexyl) sulfosuccinate. Two soils were also used—a clay soil and a sandy soil. The key observation made by this investigation was that the addition of soil to the surfactant solution provided a further component of surface tension reduction. Neither soil sample reduced the surface tension of water when surfactant was absent from the aqueous phase, though both soils released soil organic matter at low surfactant concentrations as shown by measurement of the chemical oxygen demand of the supernatant solutions. Furthermore, both surfactants were shown to be weakly adsorbed by soil as shown by the use of a methylene blue assay. It is therefore proposed that the additional reduction in surface tension arises from synergistic interactions between the surfactants and dissolved soil organic matter.

A study on the cost sharing model for supply lead time reduction with component commonality

This paper studies a two-level supply chain consisting of components supplier and product assembly manufacturer, while the manufacturer shares the investment on shortening supply lead time. The objective of this research is to investigate the benefits of cost sharing strategy and adopting component commonality. The result of numerical analysis demonstrates that using component commonality can help reduce the total cost, especially when the manufacture shares a higher fraction of the cost of investment in shortening supply lead time.

Microwave mediated reduction of heterocycle and fluorine containing nitroaromatics with Mo(CO)(6) and DBU

Heterocycle containing nitroaromatics were reduced by Mo(CO)(6) and DBU in EtOH under microwave irradiation within 15 min. Under the same conditions, 4-fluoronitrobenzene was reduced to 4-fluoroaniline, whereas 2-chloro-1-fluoro-4-nitrobenzene afforded a mixture of 3-chloro-4-fluoroaniline and 3-chloro-4-ethoxyaniline. The extent of the competing SNAr/reduction process could be influenced by the nature of the solvent, with t-BuOH the inert solvent of choice. The latter was used as solvent for SNAr/reductions of 2-chloro-1-fluoro-4-nitrobenzene with S-nucleophiles to yield 3-chloro-4-mercaptoanilines. Crown Copyright (c) 2008 Published by Elsevier Ltd. All rights reserved.