Computational Aerodynamics for Aircraft Drag Reduction

飞机减阻的计算空气动力学

• 批准号: RGPIN-2017-06760
• 负责人: Zingg, David
• 金额: $ 4.81万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=691377
• 关键词: Computational; Aerodynamics; Aircraft; Drag; Reduction

Motivated by the need to reduce the drag of transport aircraft and as a result their CO2 emissions, the proposed research program comprises algorithm development for computational fluid dynamics, algorithm development for aerodynamic shape optimization, and application to drag reduction via unconventional aircraft configurations and active flow control. *** The algorithm development for computational fluid dynamics is concentrated on promising higher-order operators having the generalized summation-by-parts property. This includes further development of tensor-product operators as well as novel multidimensional operators applicable to unstructured grids recently introduced by the applicant's group. These operators have similar properties to discontinuous Galerkin methods, but, as they do not rely on an explicit basis, they offer flexibility that hopefully can be exploited to improve efficiency on modern computer architectures.*** The algorithm development for aerodynamic shape optimization concentrates on two areas. The first involves adaptive geometry control based on free-form deformation that enables the optimization algorithm to modify the design space in search of the optimal geometry. Since this enables the optimization to go in directions not anticipated by the designer, it opens up the possibility of discovering novel aerodynamic concepts through optimization. The research will also include the development of a reliable and efficient methodology for incorporating prediction of laminar-turbulent transition within the optimization framework, thus enabling the development of aircraft configurations exploiting significant regions of natural laminar flow.*** The unconventional aircraft configurations under study include a variation of the blended wing-body developed in the applicant's group known as the lifting fuselage configuration, as well as the strut-braced wing and box-wing configurations. Emphasis will be on regional and single-aisle class aircraft, the former due to its relevance to Canada, the latter because it is the dominant class of aircraft globally. The three configurations will be optimized through aerodynamic shape optimization coupled with medium fidelity structural models and including trim and static margin constraints. A baseline conventional configuration will be optimized in an identical manner in order to provide a reference. The goal is to further advance these configurations and to identify which of the three is most promising for the regional and single aisle classes. *** Finally, the high-order methods will be utilized in direct and large-eddy simulations of turbulent flows applied to the development of active flow control techniques for drag reduction. In particular, the focus will be on synthetic jet actuation to control large structures in the outer layer of the turbulent boundary layer.

出于减少运输机阻力及其二氧化碳排放的需要，拟议的研究计划包括计算流体力学的算法开发，气动形状优化的算法开发，以及通过非传统飞机构型和主动流动控制来应用减阻。*计算流体力学的算法发展主要集中在具有广义部分求和性质的高阶算子上。这包括进一步发展张量积运算符以及适用于非结构网格的新的多维运算符，最近由申请人小组引入。这些算子具有与不连续Galerkin方法类似的性质，但由于它们不依赖于显式基础，它们提供了灵活性，有望被利用来提高现代计算机体系结构的效率。*气动形状优化的算法开发集中在两个方面。第一种是基于自由变形的自适应几何控制，它使优化算法能够修改设计空间以搜索最优几何。由于这使得优化可以朝着设计者没有预料到的方向进行，因此它为通过优化发现新的空气动力学概念打开了可能性。研究还将包括开发一种可靠而有效的方法，将层流-湍流转变的预测纳入优化框架，从而使开发利用大量自然层流的飞机构型成为可能。*正在研究的非传统飞机构型包括申请者所在组开发的混合机翼-机身构型的变体，称为提升机身构型，以及支柱支撑机翼和箱形机翼构型。重点将放在支线飞机和单通道飞机上，前者是因为它与加拿大相关，后者是因为它是全球占主导地位的飞机类别。这三种构型将通过气动形状优化与中等保真度结构模型相结合进行优化，并包括配平和静态裕度约束。基线常规配置将以相同的方式进行优化，以提供参考。我们的目标是进一步推进这些配置，并确定三种配置中哪一种最适合地区性和单通道等级。*最后，高阶方法将被用于湍流的直接和大涡模拟，应用于主动减阻流动控制技术的发展。特别是，重点将放在合成射流激励以控制湍流边界层外层的大型结构上。