Effective adjoint approaches for computational fluid dynamics

Machine Learning in Aerodynamic Shape Optimization

This article examines the increasingly crucial role played by Computational Fluid Dynamics (CFD) in the analysis, design, certification, and support of aerospace products. The status of CFD is described, and we identify opportunities for CFD to have a more substantial impact. The challenges facing CFD are also discussed, primarily in terms of numerical solution, computing power, and physical modelling. We believe the community must find a balance between enthusiasm and rigor. Besides becoming faster and more affordable by exploiting higher computing power, CFD needs to become more reliable, more reproducible across users, and better understood and integrated with other disciplines and engineering processes. Uncertainty quantification is universally considered as a major goal, but will be slow to take hold. The prospects are good for steady problems with Reynolds-Averaged Navier-Stokes (RANS) turbulence modelling to be solved accurately and without user intervention within a decade – even for very complex geometries, provided technologies, such as solution adaptation are matured for large three-dimensional problems. On the other hand, current projections for supercomputers show a future rate of growth only half of the rate enjoyed from the 1990s to 2013; true exaflop performance is not close. This will delay pure Large-Eddy Simulation (LES) for aerospace applications with their high Reynolds numbers, but hybrid RANS-LES approaches have great potential. Our expectations for a breakthrough in turbulence, whether within traditional modelling or LES, are low and as a result off-design flow physics including separation will continue to pose a substantial challenge, as will laminar-turbulent transition. We also advocate for much improved user interfaces, providing instant access to rich numerical and physical information as well as warnings over solution quality, and thus naturally training the user.

/pdf/on-the-role-and-challenges-of-cfd-in-the-aerospace-industry-303nxmuogb.pdf

On the role and challenges of CFD in the aerospace industry

Since its introduction, the NASA Common Research Model has proved a useful aerodynamic benchmark for predicting computational-fluid-dynamics-based drag and aerodynamic design optimization. The mode...

https://arc.aiaa.org/doi/pdf/10.2514/1.J056603

Benchmark Aerostructural Models for the Study of Transonic Aircraft Wings

Robust aerodynamic shape optimization—From a circle to an airfoil

Three model problems associated with aerodynamic drag minimizations are studied. These test cases have been proposed by the aerodynamic design optimization discussion group, and they include an inviscid NACA0012 nonlifting airfoil, a viscous RAE2822 lifting airfoil, and a viscous lifting wing based on the NASA Common Research Model. Various optimization methods are used, including MDOPT, TRANAIR, SYN83, and SYN107. The resulting designed and associated baseline geometries are cross analyzed by several computational fluid dynamics codes, including OVERFLOW, TRANAIR, GGNS, and FLO82. Pathological issues are unveiled in both of the simple airfoil model problems. Designed geometries for the inviscid symmetric test case exhibit strong tendencies to permit nonsymmetric flow solutions. Designed airfoils for the viscous lifting case also support nonunique solutions and hysteresis loops at or near the design point in Reynolds-averaged Navier–Stokes and integral boundary-layer method simulations. These results prov...

Study Based on the AIAA Aerodynamic Design Optimization Discussion Group Test Cases

Aerodynamic Cruise Design of a Joined Wing SensorCraft

In recent decades, overland supersonic flight has become an important topic of research for the aerospace industry. A major goal of this technology is to develop civil transport aircraft which can fly faster than the speed of sound, but without producing a loud, startling sonic boom characteristic of older supersonic aircraft. These low-boom aircraft can be designed and analyzed using a combination of numerical modeling techniques, including computational fluid dynamics and wave propagation solvers; however, care must be taken to desensitize the loudness of such aircraft from sources of uncertainty, such as the freestream Mach number and angle of attack. In this work, several gradient-enhanced robust design strategies are presented to address these challenges, including classical multi-point design and a use of the recently-developed Spatially Accurate Polynomial Chaos method. These approaches are applied to the design of a development version of the NASA X-59 QueSST aircraft. All but one attempted optimization strategy improved the robustness of sonic boom performance, while maintaining the same quiet performance as the baseline model. Although designs based on Spatially Accurate Polynomial Chaos were found to increase robustness, they were also the most computationally expensive in terms of flow solutions required. 

Robust Design of Sonic Boom Performance using Spatially Accurate Polynomial Chaos

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Study Based on the AIAA Aerodynamic Design Optimization Discussion Group Test Cases

Aerodynamic Cruise Design of a Joined Wing SensorCraft

Robust Design of Sonic Boom Performance using Spatially Accurate Polynomial Chaos