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Metallic foams or sponges are materials with a cell structure suitable for many industrial applications, such as reformers, heat catalytic converters, etc. The success of these materials is due to the combination of various characteristics such as mechanical strength, low density, high specific surface, good thermal exchange properties, low flow resistance and sound absorption. Different materials and manufacturing processes produce different type of structure and properties for various applications. In this work a genetic algorithm has been developed and applied to support the design of catalytic devices. In particular, two substrates were considered, namely the traditional honeycomb and an alternative open-cell foam type. CFD simulations of pressure losses and literature based correlations for the heat and mass transfer were used to support the genetic algorithm in finding the best compromise between flow resistance and pollutant abatement.

Nowadays, an automotive DI Diesel engine is demanded to provide an adequate power output together with limit-complying NOx and soot emissions so that the development of a specific combustion concept is the result of a trade-off between conflicting objectives. In other words, the development of a low-emission DI diesel combustion concept could be mathematically represented as a multi-objective optimization problem. In recent years, genetic algorithm and CFD simulations were successfully applied to this kind of problem. However, combining GA optimization with actual CFD-3D combustion simulations can be too onerous since a large number of simulations is usually required, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes.

The preparation of the air-fuel mixture represents one of the most critical tasks in the definition of a clean and efficient SI engine. Therefore it becomes necessary to consolidate the numerical methods which are able to describe such a complex physical process. Within this context, the authors developed a CFD methodology into an open-source code to investigate the air-fuel mixture formation process in PFI engines. Attention is focused on moving mesh algorithms, Lagrangian spray modeling and spray-wall interaction modeling. Since moving grids are involved and the mesh quality during motion strongly influences the computed in-cylinder flow-field, a FEM-based automatic mesh motion solver combined with topological changes was adopted to preserve the grid quality in presence of high boundary deformations like the interaction between the piston bowl and the valves during the valve-overlap period.

In this paper three-dimensional Large Eddy Simulations (i.e., LES) by using a PLIC-VOF method have been adopted to investigate the atomization process of round liquid jets issuing from automotive multi-hole injector-like nozzles. LES method is used to compute directly the effect of the large flow structure, being the smallest one modelled. A mesh having a cell size of 4 μm was used in order to derive a statistics of the detached liquid structures, i.e. droplets and ligaments. The latter have been identified by using an algorithm coded by authors. Cavitation modeling has not been included in the present computations. Two different mean injection nozzle flow velocities of 50 m/s and 270 m/s, corresponding to two mean nozzle flow Reynolds numbers of 1600 and 8700, respectively, have been considered in the calculations as representative of laminar and turbulent nozzle flow conditions.