An Analysis and Design Framework for Extensive Natural Laminar Flow of Aircraft Wings

飞机机翼大范围自然层流分析与设计框架

• 批准号: 538870-2019
• 负责人: Nadarajah, Sivakumaran
• 金额: $ 5.1万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 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=699362
• 关键词: Analysis; Design; Framework; Extensive; Natural

The objective of this collaborative project is to develop the necessary algorithms and tools for the analysis and design of extended region of laminar flow over aircraft components via aerodynamic shape optimization. The framework will employ a Reynolds-averaged Navier-Stokes solver, and turbulence and correlation-based transition models to accurately predict the transition point and an adjoint-based design optimization approach to perform both shape and planform optimization. The ultimate objective is to develop the enabling technologies to design environmentally responsible aircraft. This project will contribute towards the development of advanced aircraft concepts that satisfy the N+3 (2025) or equivalent EU standards. Modern aircraft design involves a large number of design variables for a multitude of disciplines culminating in extremely large number of data sets. Obtaining high fidelity solutions for all combinations of such parameters is currently computationally intractable. To alleviate this issue, designers often rely on surrogate models to simulate the input-output behaviour of complex systems based on large data sets in order to obtain a continuous approximation of functions of interest across the parameter space. In summary, the collaborative research and development will develop the necessary novel algorithms through three objectives. Objective One, implement, verify, and validate a transition model for a RANS-based solver with crossflow models. Objective Two, develop a design framework for natural laminar flow and investigate sensitivity of transitional flow to external perturbations through uncertainty quantification. Objective Three, develop a novel adaptive derivative-enhanced surrogate model of large data sets for performance and load analysis.

该协作项目的目的是开发必要的算法和工具，以通过空气形状优化的优化来分析和设计飞机组件上的扩展区域。该框架将采用雷诺平均的Navier-Stokes求解器，以及基于湍流和基于相关的过渡模型，以准确预测过渡点和基于伴随的设计优化方法，以执行形状和平面形式优化。最终目标是开发有能力的技术来设计对环境负责的飞机。该项目将有助于开发满足N+3（2025）或同等欧盟标准的高级飞机概念。现代飞机的设计涉及大量的设计变量，用于许多学科，最终以大量的数据集达到最终形式。目前，对于此类参数的所有组合，获得高保真溶液在计算上是棘手的。为了减轻此问题，设计人员通常依靠替代模型来模拟基于大数据集的复杂系统的投入输出行为，以便在整个参数空间中获得连续的感兴趣函数。总而言之，协作研究与开发将通过三个目标制定必要的新算法。物镜One，实施，验证和验证具有跨流模型的基于跑车的求解器的过渡模型。目标二，开发了自然层流的设计框架，并通过不确定性定量来研究过渡流到外部扰动的敏感性。目标三，开发了一个新型的自适应衍生衍生物增强的替代模型，用于大型数据集，用于性能和负载分析。