The automotive industry has recently seen a paradigmatic shift from design processes based on physical prototypes to a computationally aided product development process (PDP) based on virtual prototypes. To maintain the competitiveness of European car manufacturers, a significant reduction of lead development time is required. The main potential for improvement lies in further exploitation of virtual development and especially in further automation of these virtual processes through optimal design techniques.
Optimal design techniques are mature and are being used in structural mechanics in the automotive industry, as well as in computational fluid dynamics (CFD) in the aeronautical industry. However, this potential has not yet been realised for CFD in the automotive industry. To integrate these methods into workflows within the routine PDP, the project will make advances with adjoint sensitivity methods, mesh-based and CAD-based shape optimisation, high-Reynolds number topology optimisation. Complete CFD optimisation workflows, i.e. chains of optimisation techniques adapted to the automotive processes for the early as well as later stages of development will be integrated into the PDP. Aspects of process stability, data management, storage, numerical efficiency will be addressed in conjunction with an analysis of current PDP practices.
The aim of the FLOWHEAD project was to develop fast gradient-based optimisation methods using adjoint sensitivities for automotive flow design. This was done by:
- developing and enhancing a range of adjoint solvers, including commercially licensed solvers, open source solvers and research codes;
- developing automated shape parametrisation methods to deliver sensitivities for the complete design chain and
- developing topology optimisation methods for industrial applications to integrate the optimisation tools into the design workbench and the product development process.
The current practices of organising the PDP were analysed, the areas of potential for optimisation workflows identified and where necessary alterations of the PDP were made. Key use cases within the design process defined by the two car manufacturers in the project were demonstrated and the resulting reduction in lead time was validated. European SMEs play a leading role in developing the software tools for the PDP and in supporting the car manufacturers in implementing these tools in their PDPs. Three SMEs with a track record of working with the automotive industry are partners in the project.
Development of fast gradient-based optimisation methods. The project has resulted in adjoint-based optimisation methods, for shape and topology optimisation of fluid flow, with application to the automotive industry. The project focused on:
- development of continuous and discrete adjoint flow solvers for industrial application;
- CAD-based, morphing-based and node-based parametrisations;
- industrial application of topology optimisation for fluids;
- robust design and
- industrial application and the integration into the product development process.
In the aeronautical industry, computational fluid dynamics ('CFD') is often used in the design process phase in contrast to the automotive industry. The FLOWHEAD project brings the potential of computational fluid dynamics to the automotive industry.
Implementation of a robust discrete adjoint is not easy. The project has focussed on adjoint-based techniques for transient problems. As the adjoint proceeds backwards in time (from the end to the start of the flow simulation), the main difficulty encountered for large-scale applications is the massive amount of data storage required. Techniques to alleviate this problem, have been studied. The need for Algorithmic Differentiation of numerical algorithms has become apparent. The project discussed interpretations of Algorithmic Differentiation principles when applied to numerical algorithms. The project also studied an alternative solution approach based on algebraic multigrid. Unlike the geometric multigrid, algebraic multigrid does not explicitly rely on the geometry of the grid. It is therefore a very attractive approach for problems dealing with unstructured grids. The suggested solution technique to a range of problems, from subsonic Euler equations to transonic Reynolds-averaged Navier–Stokes equations, have been demonstrated.
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