Continuous development of numerical methods over the last decades together with increasing available computer power has made Computational Fluid Dynamics (CFD) a key technology in modern aircraft development. The results obtained over the last decades give rise to the vision that future aircraft design may almost entirely rely on numerical simulations. This shift in paradigm will not only dramatically change the engineering process in itself, but also the requirements on the simulation data. In particular, safe estimates of the errors and uncertainties of the simulation results will have to be provided, similar to error bars in experimental data from the windtunnel.
In order to meet such future needs, the collaborative research project MUNA – Management and Minimisation of Errors and Uncertainties in Numerical Aerodynamics – has been initiated within the 4th German Aeronautics Research Program (Luftfahrtforschungsprogramm). Following the predecessor projects MEGAFLOW and MEGADESIGN, altogether 12 partners from industry (Airbus, Cas – sidian, Eurocopter), research organisations (DLR, Institute of Aerodynamics and Flow Technology) and universities (RWTH Aachen: Institute of Aerodynamics and Institute of Computational Analysis of Technical Systems; TU Berlin: Institute of Fluid Mechanics and Technical Acoustics; TU Braunschweig: Institute of Fluid Mechanics, Institute of Aircraft Design and Lightweight Structures and Institute of Scientific Computing; University Stuttgart: Institute of Aerodynamics and Gas – dynamics; University Trier: Department of Mathematics) have been developing and applying methods, addressing errors and uncertainties of various kind, typically encountered in CFD simulations. For this purpose, the DLR TAU code was provided as major simulation tool.
In a first step the partners jointly collected possible sources of errors and uncertainties, where the computational grid, turbulence modeling, the numerical accuracy and geometrical issues in the context of coupled multidisciplinary simulations have been identified as important. Consequently, the research activities of the first project phase have been concentrating on the respective areas, which is also reflected by the organisation of the book.
In the second phase of the project, stochastic uncertainties, also called aleatory, have been addressed. Therefore the final part of the book is devoted to various activities towards efficiently computing statistical output quantities due to uncertainties in the input parameters, including methods for the robust design under geometrical uncertainties.
The results of the project have been presented to the public during two Workshops held on March 23th and 24th 2010 and on October 25th 2012. The current book documents the results achieved by the partners.
The editor is indebted to all co-workers of the project, in particular to the members of the steering committee, Holger Barnewitz (Airbus), Willy Fritz (Cassidian) and Prof. Dr. Frank Thiele (TU Berlin), for their contributions and inevitable support in making MUNA a success. Furthermore the editor wants to thank the general editor of the Springer series “Notes on Numerical Fluid Mechanics and Multidisciplinary Design”, Prof. Dr. W. Schroder, and the staff of the Springer-Verlag for the opportunity to publish the technical results of the MUNA project.
Finally the funding of the partner activities by the German Ministry of Economics within the 4th German Aeronautics Research Program is gratefully acknowledged.
Braunschweig Bernhard Eisfeld
E. Mazlum and R. Radespiel
Abstract. For the numerical simulation of complex aircraft configurations discretisation errors around wings and tailplanes as well as in their wakes are a key source of computational uncertainties. Both simplifications and uncertainties in the geometry description as well as improper numerical grids have an influence on the prediction of lift and drag coefficients, whereas the error magins are not well known. For this reason, the Institute of Fluid Mechanics systematically analysed and quantified grid induced uncertainties in the frame of the projekt MUNA. Based on this, strategies and tools have been developed for error detection and improvement of improperly discretised grid regions. For the detection of dicrestization errors, a method based on the artificial dissipation of central schemes has been developed. Furthermore, two methods have been developed for local grid improvement which follow two different grid manipulation strategies. These strategies are the local deformation of grids and the local refinement of hexahedra. The developed methods and tools have been verified on different test cases.