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.

该合作项目的目标是开发必要的算法和工具，通过气动外形优化来分析和设计飞机部件层流扩展区域。该框架将采用雷诺平均Navier-Stokes求解器，湍流和相关的过渡模型，以准确地预测过渡点和基于伴随的设计优化方法来执行形状和平面形状优化。最终目标是开发使能技术，以设计对环境负责的飞机。该项目将有助于开发满足N+3（2025）或同等欧盟标准的先进飞机概念。现代飞机设计涉及大量的设计变量，涉及众多学科，最终产生极其大量的数据集。获得高保真度的解决方案，所有这些参数的组合是目前计算上棘手的。为了缓解这一问题，设计人员通常依赖于代理模型来模拟基于大型数据集的复杂系统的输入-输出行为，以便在参数空间中获得感兴趣的函数的连续近似。总之，合作研究和开发将通过三个目标开发必要的新算法。目标一，实现，验证，并验证一个过渡模型的RANS为基础的求解器与横流模型。目的二，建立自然层流设计框架，通过不确定度量化研究过渡流对外界扰动的敏感性。目的三，提出一种新的大数据集自适应导数增强代理模型，用于性能和负载分析。