Servicio de Información Comunitario sobre Investigación y Desarrollo - CORDIS

FP6

SMB-EUROFLOWS Informe resumido

Project ID: 511097
Financiado con arreglo a: FP6-MOBILITY
País: Cyprus

Final Activity Report Summary - SMB-EUROFLOWS (Application of structure-based modelling to technological and environmental flows of European interest)

One of the most challenging problems to treat computationally in the discipline of Computational fluid dynamics (CFD) is that of turbulent fluid flow. Turbulent flow contains eddies, representing seemingly chaotic zig-zagging or swirling motion. Eddy sizes extend over many orders of magnitude in size and this poses a challenge in predicting the behaviour of turbulent flows. One can attempt to simulate turbulent flow by faithfully representing motion at all scales (an approach referred to by scientists as Direct numerical simulation (DNS)), but then even with the most powerful supercomputers available today, our simulations would be limited to low speeds and geometries that are far too simple for engineering application.

For applications in aerospace engineering, the environment, and other important technology areas, engineers are usually not concerned with the details of the swirling motion, but instead care only about the mean or averaged properties of the flow. For this reason, over the last decades a number of approaches have been developed that allow engineers to predict the mean flow properties of complicated turbulent flows without the need to carry out costly and time consuming computations. One of the most accurate modelling approaches, within the class of models that engineers refer to as one-point Reynolds averaged Navier-Stokes or RANS, is the Structure-based modelling (SBM) methodology. The SBM method was developed in the United States and is one of the most promising schemes for modelling turbulent fluid flow at the RANS level.

The main objective of this project was to further develop and refine the SBM method and to make these refinements available to European groups. Towards this end, a number of large-scale DNS simulations, using some of the fastest super-computers in the Europe and the United States were carried out. The aim of these simulations was to generate new data that could be used to test the SBM approach under conditions that are relevant to a number of technological challenges that have been identified by the CEC as being important for the competitiveness of European technology. Some of the results of these simulations were unexpected and interesting in their own right. For example, in a series of simulations of particle dispersion in Magnetohydrodynamic (MHD) turbulent shear flows, it was found that particles of certain sizes exhibit a very marked preferential concentration, which is directly related to the way the magnetic field modifies the morphology of the turbulent eddies. While preferential concentration is also observed in hydrodynamic flows, it was found that the dimensionality of the particle spatial distribution differs significantly between the MHD case and hydro cases. Further, the differences in spatial distribution were shown to relate to the differences in eddy morphology.

Because the SBM modelling approach accounts for such differences, there is good reason to expect that SBM models can handle preferential particle concentration in both hydrodynamic flows (such as aerosol dispersion in the atmosphere) and in MHD flows (such as impurities in liquid metal and plasma flows). In another exciting result, the SBM approach was shown to perform well in a number of benchmark cases, such as turbulent flow through a rotating channel and through a sudden step expansion. The information that has been gained through this project shows that the SBM approach is quite promising, and has the potential to contribute to European competitiveness in key technological areas. During the life of the project a number of collaborations between the group carrying out this research and a number of other European groups have been developed and this promises that the generated know-how will be used effectively in the future.

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