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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=709714
• 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并减少其二氧化碳排放的需要，拟议的研究计划包括计算流体动力学算法开发、气动外形优化算法开发以及通过非常规飞机配置和主动减阻的应用。流量控制。 计算流体动力学的算法发展集中在有前途的高阶算子具有广义求和的部分属性。这包括进一步发展张量积算子以及申请人的小组最近引入的适用于非结构化网格的新颖多维算子。这些算子具有类似于间断伽辽金方法的性质，但是，由于它们不依赖于显式基，因此它们提供了灵活性，希望可以利用这些灵活性来提高现代计算机架构的效率。 气动外形优化的算法开发集中在两个方面。第一个涉及基于自由形式变形的自适应几何控制，其使得优化算法能够修改设计空间以搜索最优几何形状。由于这使得优化能够朝着设计师没有预料到的方向进行，因此它开辟了通过优化发现新的空气动力学概念的可能性。这项研究还将包括开发一种可靠和有效的方法，用于在优化框架内预测层流-湍流转捩，从而能够开发利用重要自然层流区域的飞机构型。 正在研究的非常规飞机构型包括在申请人的小组中开发的称为升力机身构型的翼身融合构型的变型，以及支杆-支撑机翼和箱形机翼构型。重点将放在区域和单通道类飞机上，前者是由于其与加拿大的相关性，后者是因为它是全球主要的飞机类别。这三种布局将通过气动外形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，以便提供参考。我们的目标是进一步推进这些配置，并确定这三个是最有前途的区域和单通道类。 最后，高阶方法将用于湍流的直接和大涡模拟，用于开发减阻的主动流动控制技术。特别是，重点将放在合成射流驱动，以控制湍流边界层外层的大型结构。