By Z. J. Wang
This publication comprises vital contributions by way of world-renowned specialists on adaptive high-order tools in computational fluid dynamics (CFD). It covers numerous normal, and nonetheless intensively researched equipment, together with the discontinuous Galerkin, residual distribution, finite quantity, differential quadrature, spectral quantity, spectral distinction, PNPM, and correction approach through reconstruction tools. the main target is purposes in aerospace engineering, however the booklet also needs to be beneficial in lots of different engineering disciplines together with mechanical, chemical and electric engineering. considering the fact that a lot of those tools are nonetheless evolving, the e-book could be a great reference for researchers and graduate scholars to achieve an knowing of the state-of-the-art and final demanding situations in high-order CFD equipment.
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Additional info for Adaptive High-Order Methods in Computational Fluid Dynamics
December 1, 2010 16:28 World Scientific Review Volume - 9in x 6in 28 01˙Chapter-1 F. Bassi et al. 8 1 Fig. 18. DLR F6: skin friction coefficient of P3 solution (◦ 1012360 DOFs) compared with TAU (—— 5102446 DOFs) and CFL3D (– – – 2256896 DOFs, – · – 7689088 DOFs, – ·· – 26224640 DOFs). 4. Final Remarks In this chapter we have presented and demonstrated several well-tried features of the DG code MIGALE, that has been developed over the years for the numerical solution of the coupled RANS and k-ω turbulence model equations.
Couaillier, H. van der Ven, and K. , ADIGMA - A European Initiative on the Development of Adaptive Higher-Order Variational Methods for Aerospace Applications. vol. 113, Notes on Numerical Fluid Mechanics and Multidisciplinary Design, (Springer Berlin / Heidelberg, 2010). ISBN 978-3-642-03706-1. 17. V. Schmitt and F. Charpin. Pressure distributions on the ONERA-M6-wing at transonic Mach numbers. Advisory Report 138, AGARD, (1979). 18. Third AIAA Computational Fluid Dynamics Drag Prediction Workshop.
V. Schmitt and F. Charpin. Pressure distributions on the ONERA-M6-wing at transonic Mach numbers. Advisory Report 138, AGARD, (1979). 18. Third AIAA Computational Fluid Dynamics Drag Prediction Workshop. gov/tsab/cfdlarc/aiaa-dpw/Workshop3/ (June, 2006). 19. E. Lee-Rausch, N. Frink, D. Mavriplis, R. Rausch, and W. Milholen, Transonic drag prediction on a DLR-F6 transport configuration using unstructured grid solvers, Computers & Fluids. 38, 511–532, (2009). 20. J. Chu and J. Luckring. Experimental surface pressure data obtained on 65◦ delta wing across Reynolds number and Mach number ranges.