Distributed-Flap Layout Trade Study on a Highly Flexible Common Research Model
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Engineering topics
Publications and source records attributed to Anderson, George R..
No abstract available
The results of a layout trade study of a full-span, trailing-edge flap system for the NASACommon Research Model (CRM) are presented. Previously developed analysis and design tools areused to determine the potential performance benefits of several flap layouts on a highlyflexible version of the aircraft wing. The wing is first re-twisted for optimal aerodynamicperformance at the design cruise condition while addressing aeroelastic effects. Several flaplayouts are then installed on the new baseline wing. The deflection of each segment on allflap layouts is then optimized for aerodynamic performance at an overspeed flight conditionto ascertain the effectiveness of each flap system. The results indicate that employing two-segmentflaps greatly improves overspeed performance as compared to using no or justsingle-segment flaps. The study also showed that additional segments offer only incrementalimprovements in performance. The results also show that using only four spanwise flaps canproduce meaningful performance gains. Overall, the trade study results suggest a simpledistributed flap system (four spanwise flaps with two segments each) can reduce the drag ofthe Common Research Model by 13 counts at a Mach number that is 3.5 percent higher than thedesign cruise point.
Simulation results are presented for all test cases prescribed in the Second AIAA Sonic Boom Prediction Workshop. For each of the four nearfield test cases, we compute pressure signatures at specified distances and off-track angles, using an inviscid, embedded-boundary Cartesian-mesh flow solver with output-based mesh adaptation. The cases range in complexity from an axisymmetric body to a full low-boom aircraft configuration with a powered nacelle. For efficiency, boom carpets are decomposed into sets of independent meshes and computed in parallel. This also facilitates the use of more effective meshing strategies - each off-track angle is computed on a mesh with good azimuthal alignment, higher aspect ratio cells, and more tailored adaptation. The nearfield signatures generally exhibit good convergence with mesh refinement. We introduce a local error estimation procedure to highlight regions of the signatures most sensitive to mesh refinement. Results are also presented for the two propagation test cases, which investigate the effects of atmospheric profiles on ground noise. Propagation is handled with an augmented Burgers' equation method (NASA's sBOOM), and ground noise metrics are computed with LCASB.
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This work assesses the potential aerodynamic performance benefits of a variable-camber, continuous-trailing-edge flap system on a generic transport aircraft at off-design conditions. A process to optimize transport wings while addressing static aeroelastic effects is presented. To establish a proper baseline, a transport wing is first aerodynamically optimized at a mid-cruise flight condition using an inviscid, aeroelastic analysis tool. The optimized wing is then analyzed at off-design cruise conditions. The optimization is repeated at these off-design conditions to determine how much performance is lost by the wing optimized solely for the mid-cruise condition. The full-span flap system is then adapted to improve performance of the mid-cruise-optimized wing at these off-design conditions. The measured improvement is quantified by a comparison with wings designed specifically for the off-design conditions. To evaluate the effects of aeroelasticity on the effectiveness of the flap system, this entire process is performed on both a conventionally stiff wing and a modern, more flexible wing. The results indicate that the flap system allows for recovery of near-optimal performance throughout cruise. The flap system is found to be advantageous even for modern wings with increased flexibility.
Results are presented for four optimization benchmark problems posed by the AIAA Aerodynamic Design Optimization Discussion Group. The benchmarks are intended to exercise optimization frameworks on representative airfoil and wing design problems. All problems involve drag minimization subject to geometric and aerodynamic constraints. Our design approach involves two forms of adaptation. First, the shape parameterization is gradually and automatically enriched from an initially coarse search space. Second, adjoint solutions are used to drive adaptive mesh refinement to control discretization error. The error threshold is tailored so that the nest meshes, with the greatest accuracy, are used only when nearing the optimum. On the inviscid airfoil design problem, while reducing the drag by a factor of 10, we show how the combination of progressive parameterization and tiered discretization error control can dramatically accelerate the optimization. On the viscous airfoil design problem, we use inviscid analysis-driven optimization to reduce the total drag by a factor of two. Next, we improve the span efficiency factor of a wing by performing twist optimization. Finally, we optimize the Common Research Model wing, managing to hold drag roughly fixed, while targeting an initially-violated pitching moment constraint. Our approach aims to introduce greater complexity and accuracy only when necessary to improve the design, and also support a greater degree of automation.
We present an approach to aerodynamic optimization in which the shape control is adaptively parameterized. Starting from a coarse set of design variables, a sequence of higher-dimensional nested search spaces is automatically generated. Refinement can be either uniform or adaptive, in which case only the most important shape control is added. The relative importance of candidate design variables is determined by comparing objective and constraint gradients, computed at low cost via adjoint solutions. A search procedure for finding an effective ensemble of shape parameters is also given. We first demonstrate this system on a multipoint drag miminization problem in 2D with many constraints, showing that an adaptive parameterization approach consistently achieves smoother, more robust, and faster design improvement than fixed parameterizations. We also establish a 3D shape- matching benchmark, where we demonstrate that our approach automatically discovers the necessary parameters to match a target shape. By largely automating shape parameterization, this work also aims to remove a time-consuming aspect of shape optimization.
We present a versatile discrete geometry manipulation platform for aerospace vehicle shape optimization. The platform is based on the geometry kernel of an open-source modeling tool called Blender and offers access to four parametric deformation techniques: lattice, cage-based, skeletal, and direct manipulation. Custom deformation methods are implemented as plugins, and the kernel is controlled through a scripting interface. Surface sensitivities are provided to support gradient-based optimization. The platform architecture allows the use of geometry pipelines, where multiple modelers are used in sequence, enabling manipulation difficult or impossible to achieve with a constructive modeler or deformer alone. We implement an intuitive custom deformation method in which a set of surface points serve as the design variables and user-specified constraints are intrinsically satisfied. We test our geometry platform on several design examples using an aerodynamic design framework based on Cartesian grids. We examine inverse airfoil design and shape matching and perform lift-constrained drag minimization on an airfoil with thickness constraints. A transport wing-fuselage integration problem demonstrates the approach in 3D. In a final example, our platform is pipelined with a constructive modeler to parabolically sweep a wingtip while applying a 1-G loading deformation across the wingspan. This work is an important first step towards the larger goal of leveraging the investment of the graphics industry to improve the state-of-the-art in aerospace geometry tools.