The numerical simulation of enclosure fires using a Cfd fire field model coupled with a pyrolysis based solid fuel combustion submodel—a first approximation

In this paper, we present some early work concerned with the development of a simple solid fuel combustion model incorporated within a Computational Fluid Dynamics (CFD) framework. The model is intended for use in engineering applications of fire field modeling and represents an extension of this technique to situations involving the combustion of solid cellulosic fuels. A simple solid fuel combustion model consisting of a thermal pyrolysis model, a six flux radiation model and an eddy-dissipation model for gaseous combustion have been developed and implemented within the CFD code CFDS-FLOW3D. The model is briefly described and demonstrated through two applications involving fire spread in a compartment with a plywood lined ceiling. The two scenarios considered involve a fire in an open and closed compartment. The model is shown to be able to qualitatively predict behaviors similar to "flashover"—in the case of the open room—and "backdraft"— in the case of the initially closed room.

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 Jama legal narrative part I: The JAMA Model and narrative interpretation patterns

For the purposes of starting to tackle, within artificial intelligence (AI), the narrative aspects of legal narratives in a criminal evidence perspective, traditional AI models of narrative understanding can arguably supplement extant models of legal narratives from the scholarly literature of law, jury studies, or the semiotics of law. Not only: the literary (or cinematic) models prominent in a given culture impinge, with their poetic conventions, on the way members of the culture make sense of the world. This shows glaringly in the sample narrative from the Continent-the Jama murder, the inquiry, and the public outcry-we analyse in this paper. Apparently in the same racist crime category as the case of Stephen Lawrence's murder (in Greenwich on 22 April 1993) with the ensuing still current controversy in the UK, the Jama case (some 20 years ago) stood apart because of a very unusual element: the eyewitnesses identifying the suspects were a group of football referees and linesmen eating together at a restaurant, and seeing the sleeping man as he was set ablaze in a public park nearby. Professional background as witnesses-cum-factfinders in a mass sport, and public perceptions of their required characteristics, couldn't but feature prominently in the public perception of the case, even more so as the suspects were released by the magistrate conducting the inquiry. There are sides to this case that involve different expected effects in an inquisitorial criminal procedure system from the Continent, where an investigating magistrate leads the inquiry and prepares the prosecution case, as opposed to trial by jury under the Anglo-American adversarial system. In the JAMA prototype, we tried to approach the given case from the coign of vantage of narrative models from AI.

Utilising computational fluid dynamics (CFD) for the modelling of granular material in large-scale engineering processes

In this paper, the framework is described for the modelling of granular material by employing Computational Fluid Dynamics (CFD). This is achieved through the use and implementation in the continuum theory of constitutive relations, which are derived in a granular dynamics framework and parametrise particle interactions that occur at the micro-scale level. The simulation of a process often met in bulk solids handling industrial plants involving granular matter, (i.e. filling of a flat-bottomed bin with a binary material mixture through pneumatic conveying-emptying of the bin in core flow mode-pneumatic conveying of the material coming out of a the bin) is presented. The results of the presented simulation demonstrate the capability of the numerical model to represent successfully key granular processes (i.e. segregation/degradation), the prediction of which is of great importance in the process engineering industry.

A model to predict the life of pneumatic conveyor bends

A new approach to the prediction of bend lifetime in pneumatic conveyors, subject to erosive wear is described. Mathematical modelling is exploited. Commercial Computational Fluid Dynamics (CFD) software is used for the prediction of air flow and particle tracks, and custom code for the modelling of bend erosion and lifetime prediction. The custom code uses a toroidal geometry, and employs a range of empirical data rather than trying to fit classical erosion models to a particular circumstance. The data used was obtained relatively quickly and easily from a gas-blast erosion tester. A full-scale pneumatic conveying rig was used to validate a sample of the bend lifetime predictions, and the results suggest accuracy of within ±65%, using calibration methods. Finally, the work is distilled into user-friendly interactive software that will make erosion lifetime predictions for a wide range of bends under varying conveying conditions. This could be a valuable tool for the pneumatic conveyor design or maintenance engineer.

Computational modelling of particle degradation in dilute phase pneumatic conveyors

The aim of this paper is to develop a mathematical model with the ability to predict particle degradation during dilute phase pneumatic conveying. A numerical procedure, based on a matrix representation of degradation processes, is presented to determine the particle impact degradation propensity from a small number of particle single impact tests carried out in a new designed laboratory scale degradation tester. A complete model of particle degradation during dilute phase pneumatic conveying is then described, where the calculation of degradation propensity is coupled with a flow model of the solids and gas phases in the pipeline. Numerical results are presented for degradation of granulated sugar in an industrial scale pneumatic conveyor.

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.

Computational modelling of freeze layers in smelting processes

The use of computational modelling in examining process engineering issues is very powerful. It has been used in the development of the HIsmelt process from its concept. It is desirable to further water-cool the HIsmelt vessel to reduce downtime for replacing refractory. Water-cooled elements close to a metal bath run the risk of failure. This generally occurs when a process perturbation causes the freeze and refractory layers to come away from the water-cooled element, which is then exposed to liquid metal. The element fails as they are unable to remove all the heat. Modelling of the water-cooled element involves modelling the heat transfer, fluid flow, stress and solidification for a localised section of the reaction vessel. The complex interaction between the liquid slag and the refractory applied to the outside of thewater-cooled element is also being examined to model the wear of this layer. The model is being constructed in Physica, a CFD code developed at the University of Greenwich. Modelling of this system has commenced with modelling solidification test cases. These test cases have been used to validate the CFD code’s capability to model the solidification in this system. A model to track the penetration of slag into refractory has also been developed and tested.

Computational modeling techniques for reliability of electronic components on printed circuit boards

This paper describes modeling technology and its use in providing data governing the assembly and subsequent reliability of electronic chip components on printed circuit boards (PCBs). Products, such as mobile phones, camcorders, intelligent displays, etc., are changing at a tremendous rate where newer technologies are being applied to satisfy the demands for smaller products with increased functionality. At ever decreasing dimensions, and increasing number of input/output connections, the design of these components, in terms of dimensions and materials used, is playing a key role in determining the reliability of the final assembly. Multiphysics modeling techniques are being adopted to predict a range of interacting physics-based phenomena associated with the manufacturing process. For example, heat transfer, solidification, marangoni fluid flow, void movement, and thermal-stress. The modeling techniques used are based on finite volume methods that are conservative and take advantage of being able to represent the physical domain using an unstructured mesh. These techniques are also used to provide data on thermal induced fatigue which is then mapped into product lifetime predictions.

Mathematical modelling of the behaviour of granular material in a computational fluid dynamics framework using micro-mechanical models

In this paper, a Computational Fluid Dynamics framework is presented for the modelling of key processes which involve granular material (i.e. segregation, degradation, caking). Appropriate physical models and sophisticated algorithms have been developed for the correct representation of the different material components in a granular mixture. The various processes, which arise from the micromechanical properties of the different mixture species can be obtained and parametrised in a DEM / experimental framework, thus enabling the continuum theory to correctly account for the micromechanical properties of a granular system. The present study establishes the link between the micromechanics and continuum theory and demonstrates the model capabilities in simulations of processes which are of great importance to the process engineering industry and involve granular materials in complex geometries.

A new computational approach to microwave heating of two-phase porous materials

Computational results for the microwave heating of a porous material are presented in this paper. Combined finite difference time domain and finite volume methods were used to solve equations that describe the electromagnetic field and heat and mass transfer in porous media. The coupling between the two schemes is through a change in dielectric properties which were assumed to be dependent on both temperature and moisture content. The model was able to reflect the evolution of both temperature and moisture fields as well as energy penetration as the moisture in the porous medium evaporates. Moisture movement results from internal pressure gradients produced by the internal heating and phase change.

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.

Analysis and modeling of heaping behavior of granular mixtures within a computational mechanics framework

This paper presents a continuum model of the flow of granular material during filling of a silo, using a viscoplastic constitutive relation based on the Drucker-Prager plasticity yield function. The performed simulations demonstrate the ability of the model to realistically represent complex features of granular flows during filling processes, such as heap formation and non-zero inclination angle of the bulk material-air interface. In addition, micro-mechanical parametrizations which account for particle size segregation are incorporated into the model. It is found that numerical predictions of segregation phenomena during filling of a binary granular mixture agree well with experimental results. Further numerical tests indicate the capability of the model to cope successfully with complex operations involving granular mixtures.