This report documents the results of a study to address the long range, strategic planning required by NASA's Revolutionary Computational Aerosciences (RCA) program in the area of computational fluid dynamics (CFD), including future software and hardware requirements for High Performance Computing (HPC). Specifically, the "Vision 2030" CFD study is to provide a knowledge-based forecast of the future computational capabilities required for turbulent, transitional, and reacting flow simulations across a broad Mach number regime, and to lay the foundation for the development of a future framework and/or environment where physics-based, accurate predictions of complex turbulent flows, including flow separation, can be accomplished routinely and efficiently in cooperation with other physics-based simulations to enable multi-physics analysis and design. Specific technical requirements from the aerospace industrial and scientific communities were obtained to determine critical capability gaps, anticipated technical challenges, and impediments to achieving the target CFD capability in 2030. A preliminary development plan and roadmap were created to help focus investments in technology development to help achieve the CFD vision in 2030.

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CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences

Giga-voxel-resolution computational morphogenesis is used to optimize the internal structure of a full-scale aeroplane wing, yielding light-weight designs with more similarities to animal bone structures than to current aeroplane wing designs. Computational morphogenesis is used to design the best possible shapes and material distributions for the desired structural properties, such as high strength at minimal weight. In plants and animals, morphogenesis occurs naturally through slow genetic evolution. In engineering, a much faster iterative approach for optimum material distribution has been adopted, called topology optimization. So far, it has been used to calculate only small or simple structures owing to limited resolution. Niels Aage et al. have developed a morphogenesis tool that can be run on a supercomputer and can calculate two orders of magnitude more voxels (the three-dimensional equivalents of pixels) than was previously attainable. This makes it possible to design structures with unprecedented detail, yielding new insights into optimal material distribution. The authors calculate an optimized full aircraft wing structure with remarkable structural detail at several length scales, which displays similarities to naturally occurring bone structures such as those seen in bird beaks. The new tool could inspire surprising design approaches for a range of structures, including wind turbine blades, tower masts and bridges. In the design of industrial products ranging from hearing aids to automobiles and aeroplanes, material is distributed so as to maximize the performance and minimize the cost. Historically, human intuition and insight have driven the evolution of mechanical design, recently assisted by computer-aided design approaches. The computer-aided approach known as topology optimization enables unrestricted design freedom and shows great promise with regard to weight savings, but its applicability has so far been limited to the design of single components or simple structures, owing to the resolution limits of current optimization methods1,2. Here we report a computational morphogenesis tool, implemented on a supercomputer, that produces designs with giga-voxel resolution—more than two orders of magnitude higher than previously reported. Such resolution provides insights into the optimal distribution of material within a structure that were hitherto unachievable owing to the challenges of scaling up existing modelling and optimization frameworks. As an example, we apply the tool to the design of the internal structure of a full-scale aeroplane wing. The optimized full-wing design has unprecedented structural detail at length scales ranging from tens of metres to millimetres and, intriguingly, shows remarkable similarity to naturally occurring bone structures in, for example, bird beaks. We estimate that our optimized design corresponds to a reduction in mass of 2–5 per cent compared to currently used aeroplane wing designs, which translates into a reduction in fuel consumption of about 40–200 tonnes per year per aeroplane. Our morphogenesis process is generally applicable, not only to mechanical design, but also to flow systems3, antennas4, nano-optics5 and micro-systems6,7.

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Giga-voxel computational morphogenesis for structural design

Error estimation and control are critical ingredients for improving the reliability of computational simulations Adjoint-based techniques can be used to both estimate the error in chosen solution outputs and to provide local indicators for adaptive refinement This article reviews recent work on these techniques for computational fluid dynamics applications in aerospace engineering The definition of the adjoint as the sensitivity of an output to residual source perturbations is used to derive both the adjoint equation, in fully discrete and variational formulations, and the adjoint-weighted residual method for error estimation Assumptions and approximations made in the calculations are discussed Presentation of the discrete and variational formulations enables a side-by-side comparison of recent work in output-error estimation using the finite volume method and the finite element method Techniques for adapting meshes using output-error indicators are also reviewed Recent adaptive results from a variety of laminar and Reynolds-averaged Navier-Stokes applications show the power of output-based adaptive methods for improving the robustness of computational fluid dynamics computations However, challenges and areas of additional future research remain, including computable error bounds and robust mesh adaptation mechanics

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Review of Output-Based Error Estimation and Mesh Adaptation in Computational Fluid Dynamics

http://www-personal.umich.edu/~kfid/pubs/Fidkowski_Oliver_Lu_Darmofal_2005.pdf

p-Multigrid solution of high-order discontinuous Galerkin discretizations of the compressible Navier-Stokes equations

This paper presents multipoint high-fidelity aerostructural optimizations of a long-range wide-body transonic transport aircraft configuration. The aerostructural analysis employs Euler computational fluid dynamics with a 2-million-cell mesh and a structural finite-element model with 300,000 degrees of freedom. The coupled adjoint sensitivity method is used to efficiently compute gradients, enabling the use of gradient-based optimization with respect to hundreds of aerodynamic shape and structural sizing variables. The NASA Common Research Model is used as the baseline configuration, together with a wing box structure that was designed for this study. Two design optimization problems are solved: one where takeoff gross weight is minimized, and another where fuel burn is minimized. Each optimization uses a multipoint formulation with five cruise conditions and two maneuver conditions. Each of the optimization problems have 476 design variables, including wing planform, airfoil shape, and structural thickne...

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Multipoint High-Fidelity Aerostructural Optimization of a Transport Aircraft Configuration

The development of a wing/body/nacelle/pylon/horizontal-tail configuration for a common research model is presented, with focus on the aerodynamic design of the wing. Here, a contemporary transonic supercritical wing design is developed with aerodynamic characteristics that are well behaved and of high performance for configurations with and without the nacelle/pylon group. The horizontal tail is robustly designed for dive Mach number conditions and is suitably sized for typical stability and control requirements. The fuselage is representative of a wide/body commercial transport aircraft; it includes a wing-body fairing, as well as a scrubbing seal for the horizontal tail. The nacelle is a single-cowl, high by-pass-ratio, flow-through design with an exit area sized to achieve a natural unforced mass-flow-ratio typical of commercial aircraft engines at cruise. The simplicity of this un-bifurcated nacelle geometry will facilitate grid generation efforts of subsequent CFD validation exercises. Detailed aerodynamic performance data has been generated for this model; however, this information is presented in such a manner as to not bias CFD predictions planned for the fourth AIAA CFD Drag Prediction Workshop, which incorporates this common research model into its blind test cases. The CFD results presented include wing pressure distributions with and without the nacelle/pylon, ML/D trend lines, and drag-divergence curves; the design point for the wing/body configuration is within 1% of its max-ML/D. Plans to test the common research model in the National Transonic Facility and the Ames 11-ft wind tunnels are also discussed.

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Development of a Common Research Model for Applied CFD Validation Studies

The work presented herein has been performed in preparation of the Third AIAA CFD Drag Prediction Workshop to be held June, 2006 at the AIAA 24 th Applied Aerodynamics conference in San Francisco, California. The purpose of this work is to provide a new test case to address a problematic issue related to the inability for the industry-wide state-of-the-art CFD to achieve asymptotic grid convergence for cases with moderate-to-large amounts of flow separation. Two wing-body fairings have been designed for the DLR-F6 model geometry. The first fairing greatly alleviates the side-of-body separation near the wing upper-surface trailing-edge, while the second fairing has completely removed this separation bubble. These geometries will be made available for public release, although only the second fairing will be a subject of study in the next workshop.

A Wing-Body Fairing Design for the DLR-F6 Model: A DPW-III Case Study

Grid Generation Requirements for Accurate Drag Predictions Based on OVERFLOW Calculations

In response to the fourth AIAA CFD Drag Prediction Workshop (DPW-IV), the NASA Common Research Model (CRM) wing-body and wing-body-tail configurations are analyzed using the Reynolds-averaged Navier-Stokes (RANS) flow solvers CFL3D and OVERFLOW. Two families of structured, overset grids are built for DPW-IV. Grid Family 1 (GF1) consists of a coarse (7.2 million), medium (16.9 million), fine (56.5 million), and extra-fine (189.4 million) mesh. Grid Family 2 (GF2) is an extension of the first and includes a superfine (714.2 million) and an ultra-fine (2.4 billion) mesh. The medium grid anchors both families with an established build process for accurate cruise drag prediction studies. This base mesh is coarsened and enhanced to form a set of parametrically equivalent grids that increase in size by a factor of roughly 3.4 from one level to the next denser level. Both CFL3D and OVERFLOW are run on GF1 using a consistent numerical approach. Additional OVERFLOW runs are made to study effects of differencing scheme and turbulence model on GF1 and to obtain results for GF2. All CFD results are post-processed using Richardson extrapolation, and approximate grid-converged values of drag are compared. The medium grid is also used to compute a trimmed drag polar for both codes.

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Mark A. DeHaan

Papers

Development of a Common Research Model for Applied CFD Validation Studies

A Wing-Body Fairing Design for the DLR-F6 Model: A DPW-III Case Study

Grid Generation Requirements for Accurate Drag Predictions Based on OVERFLOW Calculations

Drag Prediction for the NASA CRM Wing-Body-Tail Using CFL3D and OVERFLOW on an Overset Mesh

OVERFLOW Drag Prediction for the DLR-F6 Transport Configuration: A DPW-II Case Study