Application of CFD in vacuum dezincing process

Most lead bullion is refined by pyrometallurgical methods - this involves a serics of processes that remove the antimony (softening) silver (Parkes process), zinc (vacuum dezincing) and if need be, bismuth (Betterton-Kroll process). The first step, softening, removes the antimony, arsenic and tin by air oxidation in a furnace or by the Harris process. Next, in the Parkes process, zinc is added to the melt to remove the silver and gold. Insoluble zinc, silver and gold compounds are skimmed off from the melt surface. Excess zinc added during desilvering is removed from lead bullion using one of ghree methods: * Vacuum dezincing; * Chlorine dezincing; or * Harris dezincing. The present study concentrates on the Vacuum dezincing process for lead refining. The main aims of the research are to develop mathematical model(s), using Computational Fluid Dyanmics (CFD) a Surface Averaged Model (SAM), to predict the process behaviour under various operating conditions, thus providing detailed information of the process - insight into its reaction to changes of key operating parameters. Finally, the model will be used to optimise the process in terms of initial feed concentration, temperature, vacuum height cooling rate, etc.

Pneumatic contactless microfeeder design refinement through CFD simulation

A new contactless pneumatic microfeeder based on distributed manipulation is proposed. By cooperation of dynamically programmable microactuators, the part to be conveyed floats over an air cushion and is moved to the desired location with the desired orientation. CFD simulations are used to test the validity of the proposed concept and refine the design of the microactuators

SMARTFIRE: an intelligent CFD-based fire model

This paper describes a project aimed at making Computational Fluid Dynamics (CFD) based fire simulation accessible to members of the fire safety engineering community. Over the past few years, the practise of CFD based fire simulation has begun the transition from the confines of the research laboratory to the desk of the fire safety engineer. To a certain extent, this move has been driven by the demands of performance based building codes. However, while CFD modelling has many benefits over other forms of fire simulation, it requires a great deal of expertise on the user’s part to obtain reasonable simulation results. The project described in this paper, SMARTFIRE, aims to relieve some of this dependence on expertise so that users are less concerned with the details of CFD analysis and can concentrate on results. This aim is achieved by the use of an expert system component as part of the software suite which takes some of the expertise burden away from the user. SMARTFIRE also makes use of the latest developments in CFD technology in order to make the CFD analysis more efficient. This paper describes design considerations of the SMARTFIRE software, emphasising its open architecture, CFD engine and knowledge based systems.

SMARTFIRE: an intelligent CFD based fire model

This paper describes a project aimed at making Computational Fluid Dynamics (CFD)- based fire simulation accessible to members of the fire safety engineering community. Over the past few years, the practice of CFD-based fire simulation has begun the transition from the confines of the research laboratory to the desk of the fire safety engineer. To a certain extent, this move has been driven by the demands of performance based building codes. However, while CFD modeling has many benefits over other forms of fire simulation, it requires a great deal of expertise on the user’s part to obtain reasonable simulation results. The project described in this paper, SMARTFIRE, aims to relieve some of this dependence on expertise so that users are less concerned with the details of CFD analysis and can concentrate on results. This aim is achieved by the use of an expert system component as part of the software suite which takes some of the expertise burden away from the user. SMARTFIRE also makes use of the latest developments in CFD technology in order to make the CFD analysis more efficient. This paper describes design considerations of the SMARTFIRE software, emphasizing its open architecture, CFD engine and knowledge-based systems.

The development of a CFD based simulator for water mist suppression systems: the development of the fire submodel

The FIRE Detection and Suppression Simulation (FIREDASS) project was concerned with the development of water misting systems as a possible replacement for halon based fire suppression systems currently used in aircraft cargo holds and ship engine rooms. As part of this program of work, a computational model was developed to assist engineers optimize the design of water mist suppression systems. The model is based on Computational Fluid Dynamics (CFD) and comprised of the following components: fire model; mist model; two-phase radiation model; suppression model; detector/activation model. In this paper the FIREDASS software package is described and the theory behind the fire and radiation sub-models is detailed. The fire model uses prescribed release rates for heat and gaseous combustion products to represent the fire load. Typical release rates have been determined through experimentation. The radiation model is a six-flux model coupled to the gas (and mist) phase. As part of the FIREDASS project, a detailed series of fire experiments were conducted in order to validate the fire model. Model predictions are compared with data from these experiments and good agreement is found.

Modelling induction skull melting design modifications

Induction Skull Melting (ISM) is a technique for heating, melting, mixing and, possibly, evaporating reactive liquid metals at high temperatures with a minimum contact at solid walls. The presented numerical modelling involves the complete time dependent process analysis based on the coupled electromagnetic, temperature and turbulent velocity fields during the melting and liquid shape changes. The simulation model is validated against measurements of liquid metal height, temperature and heat losses in a commercial size ISM furnace. The observed typical limiting temperature plateau for increasing input electrical power is explained by the turbulent convective heat losses. Various methods to increase the superheat within the liquid melt, the process energy efficiency and stability are proposed.

Turbulence modelling and its impact on CFD predictions for cooling of electronic components

This paper will discuss Computational Fluid Dynamics (CFD) results from an investigation into the accuracy of several turbulence models to predict air cooling for electronic packages and systems. Also new transitional turbulence models will be proposed with emphasis on hybrid techniques that use the k-ε model at an appropriate distance away from the wall and suitable models, with wall functions, near wall regions. A major proportion of heat emitted from electronic packages can be extracted by air cooling. This flow of air throughout an electronic system and the heat extracted is highly dependent on the nature of turbulence present in the flow. The use of CFD for such investigations is fast becoming a powerful and almost essential tool for the design, development and optimization of engineering applications. However turbulence models remain a key issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the turbulence model employed together with the wall functions implemented. In order to resolve the abrupt fluctuations experienced by the turbulent energy and other parameters located at near wall regions and shear layers a particularly fine computational mesh is necessary which inevitably increases the computer storage and run-time requirements. The PHYSICA Finite Volume code was used for this investigation. With the exception of the k-ε and k-ω models which are available as standard within PHYSICA, all other turbulence models mentioned were implemented via the source code by the authors. The LVEL, LVEL CAP, Wolfshtein, k-ε, k-ω, SST and kε/kl models are described and compared with experimental data.

Modelling induction skull melting design modifications

Induction Skull Melting (ISM) is used for heating, melting, mixing and, possibly, evaporating reactive liquid metals at high temperatures when a minimum contact at solid walls is required. The numerical model presented here involves the complete time dependent process analysis based on the coupled electromagnetic, temperature and turbulent velocity fields during the melting and liquid shape changes. The simulation is validated against measurements of liquid metal height, temperature and heat losses in a commercial size ISM furnace. The often observed limiting temperature plateau for ever increasing electrical power input is explained by the turbulent convective heat losses. Various methods to increase the superheat within the liquid melt, the process energy efficiency and stability are proposed.