Multiphysics modeling and its application to the casting process

A modeling strategy is presented to solve the governing equations of fluid flow, temperature (with solidification), and stress in an integrated manner. These equations are discretized using finite volume methods on unstructured grids, which provide the capability to represent complex domains. Both the cell-centered and vertex-based forms of the finite volume discretization procedure are explained, and the overall integrated solution procedure using these techniques with suitable solvers is detailed. Two industrial processes, based on the casting of metals, are used to demonstrate the capabilities of the resultant modeling framework. This manufacturing process requires a high degree of coupling between the governing physical equations to accurately predict potential defects. Comparisons between model predictions and experimental observations are given.

A computational model for defect prediction in shape castings based on the interaction of free surface flow, heat transfer, and solidification phenomena

High-integrity castings require sophisticated design and manufacturing procedures to ensure they are essentially macrodefect free. Unfortunately, an important class of such defects—macroporosity, misruns, and pipe shrinkage—are all functions of the interactions of free surface flow, heat transfer, and solidication in complex geometries. Because these defects arise as an interaction of the preceding continuum phenomena, genuinely predictive models of these defects must represent these interactions explicitly. This work describes an attempt to model the formation of macrodefects explicitly as a function of the interacting continuum phenomena in arbitrarily complex three-dimensional geometries. The computational approach exploits a compatible set of finite volume procedures extended to unstructured meshes. The implementation of the model is described together with its testing and a measure of validation. The model demonstrates the potential to predict reliably shrinkage macroporosity, misruns, and pipe shrinkage directly as a result of interactions among free-surface fluid flow, heat transfer, and solidification.

Model sensitivity and uncertainty analysis using roadside air quality measurements

Most of the air quality modelling work has been so far oriented towards deterministic simulations of ambient pollutant concentrations. This traditional approach, which is based on the use of one selected model and one data set of discrete input values, does not reflect the uncertainties due to errors in model formulation and input data. Given the complexities of urban environments and the inherent limitations of mathematical modelling, it is unlikely that a single model based on routinely available meteorological and emission data will give satisfactory short-term predictions. In this study, different methods involving the use of more than one dispersion model, in association with different emission simulation methodologies and meteorological data sets, were explored for predicting best CO and benzene estimates, and related confidence bounds. The different approaches were tested using experimental data obtained during intensive monitoring campaigns in busy street canyons in Paris, France. Three relative simple dispersion models (STREET, OSPM and AEOLIUS) that are likely to be used for regulatory purposes were selected for this application. A sensitivity analysis was conducted in order to identify internal model parameters that might significantly affect results. Finally, a probabilistic methodology for assessing urban air quality was proposed.

The application of free-surface techniques to metal forming processes

In this paper the use of free-surface techniques, within the framework of a finite volume methodology, are investigated for the simulation of metal forming processes. In such processes, for example extrusion and forging, a workpiece is subjected to large scale deformation to create the product's shape. The use of Eulerian free-surface techniques to predict this final shape offers the advantage, over the traditionally used Lagrangian finite element method, of not requiring remmeshing. Two free-surface techniques to predict this final shape offers the advantage, over the traditionally used Lagrangian finite element method, of not requiring remesingh. Two free-surface techniques are compared by modelling a typical example of this type of process - non-Newtonian extrusion of an aluminium workpiece through a conical die.

Computational modelling of metal extrusion and forging processes

The computational modelling of extrusion and forging processes is now well established. There are two main approaches: Lagrangian and Eulerian. The first has considerable complexities associated with remeshing, especially when the code is parallelised. The second approach means that the mould has to be assumed to be entirely rigid and this may not be the case. In this paper, a novel approach is described which utilises finite volume methods on unstructured meshes. This approach involves the solution of free surface non-Newtonian fluid flow equations in an Eulerian context to track the behaviour of the workpiece and its extrusion/forging, and the solution of the solid mechanics equations in the Lagrangian context to predict the deformation/stress behaviour of the die. Test cases for modelling extrusion and forging problems using this approach will be presented.

Two fluid approach to high speed impact interaction amongst solid structures

The issues surrounding collision of projectiles with structures has gained a high profile since the events of 11th September 2001. In such collision problems, the projectile penetrates the stucture so that tracking the interface between one material and another becomes very complex, especially if the projectile is essentially a vessel containing a fluid, e.g. fuel load. The subsequent combustion, heat transfer and melting and re-solidification process in the structure render this a very challenging computational modelling problem. The conventional approaches to the analysis of collision processes involves a Lagrangian-Lagrangian contact driven methodology. This approach suffers from a number of disadvantages in its implementation, most of which are associated with the challenges of the contact analysis component of the calculations. This paper describes a 'two fluid' approach to high speed impact between solid structures, where the objective is to overcome the problems of penetration and re-meshing. The work has been carried out using the finite volume, unstructured mesh multi-physics code PHYSICA+, where the three dimensional fluid flow, free surface, heat transfer, combustion, melting and re-solidification algorithms are approximated using cell-centred finite volume, unstructured mesh techniques on a collocated mesh. The basic procedure is illustrated for two cases of Newtonian and non-Newtonian flow to test various of its component capabilities in the analysis of problems of industrial interest.

Forward and inverse transport of particulate matter and gaseous pollutants affecting the region bordering the English Channel

The ATTMA "Aerosol Transport in the Trans-Manche Atmosphere" project investigates the transportation and dispersion of air pollutants across the English Channel, in collaboration with local authorities and other Universities in Southern England and Northern France. The research is concerned with both forward and inverse (receptor based) tracking. Two alternative dispersion simulation methods are used: (a) Lagrangian Particle Dispersion (LPD) models, (b) Eulerian Finite Volume type models. This paper is concerned with part (a), the simulations based on LPD models. Two widely applied LPD models are used and compared. Since in many observed episodes the source of pollution is traced outside the region of interest, long range, trans-continental transport is also investigated.

Modelling high particulate matter and ozone episodes in the Trans-Manche region

There is concern in the Cross-Channel region of Nord-Pas-de-Calais (France) and Kent (Great Britain), regarding the extent of atmospheric pollution detected in the area from emitted gaseous (VOC, NOx, S02)and particulate substances. In particular, the air quality of the Cross-Channel or "Trans-Manche" region is highly affected by the heavily industrial area of Dunkerque, in addition to transportation sources linked to cross-channel traffic in Kent and Calais, posing threats to the environment and human health. In the framework of the cross-border EU Interreg IIIA activity, the joint Anglo-French project, ATTMA, has been commissioned to study Aerosol Transport in the Trans-Manche Atmosphere. Using ground monitoring data from UK and French networks and with the assistance of satellite images the project aims to determine dispersion patterns. and identify sources responsible for the pollutants. The findings of this study will increase awareness and have a bearing on future air quality policy in the region. Public interest is evident by the presence of local authorities on both sides of the English Channel as collaborators. The research is based on pollution transport simulations using (a) Lagrangian Particle Dispersion (LPD) models, (b) an Eulerian Receptor Based model. This paper is concerned with part (a), the LPD Models. Lagrangian Particle Dispersion (LPD) models are often used to numerically simulate the dispersion of a passive tracer in the planetary boundary layer by calculating the Lagrangian trajectories of thousands of notional particles. In this contribution, the project investigated the use of two widely used particle dispersion models: the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the model FLEXPART. In both models forward tracking and inverse (or·. receptor-based) modes are possible. Certain distinct pollution episodes have been selected from the monitor database EXPER/PF and from UK monitoring stations, and their likely trajectory predicted using prevailing weather data. Global meteorological datasets were downloaded from the ECMWF MARS archive. Part of the difficulty in identifying pollution sources arises from the fact that much of the pollution outside the monitoring area. For example heightened particulate concentrations are to originate from sand storms in the Sahara, or volcanic activity in Iceland or the Caribbean work identifies such long range influences. The output of the simulations shows that there are notable differences between the formulations of and Hysplit, although both models used the same meteorological data and source input, suggesting that the identification of the primary emissions during air pollution episodes may be rather uncertain.

Exploring adaptation & self-adaptation in autonomic computing systems

This panel paper sets out to discuss what self-adaptation means, and to explore the extent to which current autonomic systems exhibit truly self-adaptive behaviour. Many of the currently cited examples are clearly adaptive, but debate remains as to what extent they are simply following prescribed adaptation rules within preset bounds, and to what extent they have the ability to truly learn new behaviour. Is there a standard test that can be applied to differentiate? Is adaptive behaviour sufficient anyway? Other autonomic computing issues are also discussed.

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.

Airborne transport of Saharan dust to the Mediterranean and to the Atlantic

The Sahara desert is a significant source of particulate pollution not only to the Mediterranean region, but also to the Atlantic and beyond. In this paper, PM 10 exceedences recorded in the UK and the island of Crete are studied and their source investigated, using Lagrangian Particle Dispersion (LPD) methods. Forward and inverse simulations identify Saharan dust storms as the primary source of these episodes. The methodology used allows comparison between this primary source and other possible candidates, for example large forest fires or volcanic eruptions. Two LPD models are used in the simulations, namely the open source code FLEXPART and the proprietary code HYSPLIT. Driven by the same meteorological fields (the ECMWF MARS archive and the PSU/NCAR Mesoscale model, known as MM5) the codes produce similar, but not identical predictions. This inter-model comparison enables a critical assessment of the physical modelling assumptions employed in each code, plus the influence of boundary conditions and solution grid density. The outputs, in the form of particle concentrations evolving in time, are compared against satellite images and receptor data from multiple ground-based sites. Quantitative comparisons are good, especially in predicting the time of arrival of the dust plume in a particular location.

Dynamic model for metal cleanness evaluation by melting in a cold crucible

Melting of metallic samples in a cold crucible causes inclusions to concentrate on the surface owing to the action of the electromagnetic force in the skin layer. This process is dynamic, involving the melting stage, then quasi-stationary particle separation, and finally the solidification in the cold crucible. The proposed modeling technique is based on the pseudospectral solution method for coupled turbulent fluid flow, thermal and electromagnetic fields within the time varying fluid volume contained by the free surface, and partially the solid crucible wall. The model uses two methods for particle tracking: (1) a direct Lagrangian particle path computation and (2) a drifting concentration model. Lagrangian tracking is implemented for arbitrary unsteady flow. A specific numerical time integration scheme is implemented using implicit advancement that permits relatively large time-steps in the Lagrangian model. The drifting concentration model is based on a local equilibrium drift velocity assumption. Both methods are compared and demonstrated to give qualitatively similar results for stationary flow situations. The particular results presented are obtained for iron alloys. Small size particles of the order of 1 μm are shown to be less prone to separation by electromagnetic field action. In contrast, larger particles, 10 to 100 μm, are easily “trapped” by the electromagnetic field and stay on the sample surface at predetermined locations depending on their size and properties. The model allows optimization for melting power, geometry, and solidification rate.

Modelling metal powder production by the gas atomisation process

Metal powder in the range of 10-100 microns is widely employed in the production of Raney nickel type catalysts for hydrogenation reactions and hydrogen fuel cell manufacture. In this presentation we examine the modelling of powder production in a gas atomisation vessel using CFD techniques. In a fully coupled Lagrangian-Eulerian two phase scheme, liquid meal particles are tracked through the vessel following atomisation of a liquid nickel-aluminium stream. There is full momentum, heat and turbulence transport between particles and surrounding argon gas and the model predicts the position of solidification depending on particle size and undercooled condition. Maps of collision probability of particles at different stages of solidification are computed, to predict the creation of satellite defects, or to initiate solidification of undercooled droplets. The model is used to support experimental work conducted under the ESA/EU project IMPRESS.

Role of light and photophysiological properties on phytoplankton succession during the spring bloom in the north-western Mediterranean Sea

This study aimed to determine the role of light on the succession of the phytoplankton community during the spring bloom in the northwestern Mediterranean Sea. To this end, three successive Lagrangian experiments were carried out between March and April 2003. The three experiments correspond to distinct phases of the bloom development (pre-bloom, bloom peak and post-bloom, respectively) and therefore to different trophic conditions. Phytoplankton (sampled on a daily scale) was grouped in size-based classes (pico and nano+micro) each of them were characterised in terms of chemotaxonomic composition, primary production and photophysiological properties. The phytoplankton community evolved with time changing in both size-class dominance and specie/group dominance within each size class. The bloom peak was characterised by highly dynamic condition (i.e. vertical mixing) and by the dominance of both small (pico) and large (nano and micro) diatoms, as a result of their capacity to photoacclimate to changing light regimes (‘physiological plasticity’). Concluding, we suggest that the physiological adaptation to light is the main factor driving the succession of the phytoplankton community during the first phases of the bloom (until the onset of thermal stratification) in the western Mediterranean Sea.

Marine plankton phenology and life history in a changing climate: current research and future directions

Increasing availability and extent of biological ocean time series (from both in situ and satellite data) have helped reveal significant phenological variability of marine plankton. The extent to which the range of this variability is modified as a result of climate change is of obvious importance. Here we summarize recent research results on phenology of both phytoplankton and zooplankton. We suggest directions to better quantify and monitor future plankton phenology shifts, including (i) examining the main mode of expected future changes (ecological shifts in timing and spatial distribution to accommodate fixed environmental niches vs. evolutionary adaptation of timing controls to maintain fixed biogeography and seasonality), (ii) broader understanding of phenology at the species and community level (e.g. for zooplankton beyond Calanus and for phytoplankton beyond chlorophyll), (iii) improving and diversifying statistical metrics for indexing timing and trophic synchrony and (iv) improved consideration of spatio-temporal scales and the Lagrangian nature of plankton assemblages to separate time from space changes.