Multi-physics-multi-scale simulation and optimisation: the next generation

FEA and CFD analysis is becoming ever more complex with an emerging demand for simulation software technologies that can address ranges of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and length scales. Computation modelling of such problems requires software technologies that enable the representation of these complex suites of 'physical' interactions. This functionality requires the structuring of simulation modules for specific physical phemonmena so that the coupling can be effectiely represented. These 'multi-physics' and 'multi-scale' computations are very compute intensive and so the simulation software must operate effectively in parallel if it is to be used in this context. Of course the objective of 'multi-physics' and 'multi-scale' simulation is the optimal design of engineered systems so optimistation is an important feature of such classes of simulation. In this presentation, a multi-disciplinary approach to simulation based optimisation is described with some key examples of application to challenging engineering problems.

Computational modelling of multi-physics and multi-scale processes in parallel

This paper provides an overview of the developing needs for simulation software technologies for the computational modelling of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and space scales. Computational modelling of such problems requires software tech1nologies that enable the mathematical description of the interacting physical phenomena together with the solution of the resulting suites of equations in a numerically consistent and compatible manner. This functionality requires the structuring of simulation modules for specific physical phenomena so that the coupling can be effectively represented. These multi-physics and multi-scale computations are very compute intensive and the simulation software must operate effectively in parallel if it is to be used in this context. An approach to these classes of multi-disciplinary simulation in parallel is described, with some key examples of application to2 challenging engineering problems.

Reaching across organisational, sectoral and geographical boundaries: exploring the learning potential of an EU cross-border project

Research This paper outlines some of the key findings from an evaluation of the project and demonstrates that EC funded projects such as this, which seek to promote cross border collaboration and understanding (i.e. across organisational, sectoral and geographical boundaries) offer considerable learning potential – not least about variances in health politics across different communities. However, for this learning to be realised a comprehensive system of knowledge management needs to be an integral part of project planning alongside a system for sustaining embryonic professional networks. The concept of managing relationships was also a key part of the projects success. Executing a project funded by the EU demands the development of complex organisational skills to negotiate all the administrative challenges en route to successful completion and this project in particular relied for its success on the development of social relationships of trust and mutual respect across national, professional and social boundaries. Context A three–year European Commission funded project designed to exchange a wide range of staff (professional semiprofessional and voluntary staff in health and social care) project led by the University of Greenwich (UK) and the Université Catholique de Lille, France was completed this year (February 2008). The project was complex because it involved working in different national contexts, was multi-disciplinary, and demanded the negotiation of multiple boundaries. Theories A mixed method evaluation including written reports gathered immediately after each exchange visit and a post hoc series of individual interviews and focus groups was conducted in order to gain qualitative information (from the participants perspective) on their experiences and to identify any learning gained. Results Analysis of the data provided evidence of learning on a number of levels; personally, inter and intra professionally and organisationally as well as across sectors and also from a project management perspective. The learning crystallised around the extent of the differences noted by the participants between the UK and the French health and social care systems despite geographical proximity, common membership of the EU and many shared challenges in health and social care. The extent of these differences, noted at every level from policy to practice proved a rich source for reflection on organisational philosophies, ways of working, distribution of resources, professional roles and autonomy and professional registration and mobility - in short on health politics at ‘macro’ and ‘micro’ levels.