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

这个合作项目的目标是开发必要的算法和工具，通过气动形状优化来分析和设计飞机部件的层流扩展区域。该框架将使用雷诺平均的Navier-Stokes求解器，以及基于湍流和相关性的过渡模型来准确预测转换点，并使用基于伴随的设计优化方法来执行形状和平面优化。最终目标是开发能够设计出对环境负责的飞机的技术。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。现代飞机设计涉及多个学科的大量设计变量，最终产生极大量的数据集。目前，获得这些参数的所有组合的高保真解决方案在计算上是困难的。为了缓解这一问题，设计者经常依赖代理模型来模拟基于大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函数的连续近似。总而言之，合作研发将通过三个目标开发必要的新算法。目标一，使用横流模型实现、验证和验证基于RANS的求解器的过渡模型。目的二，建立自然层流的设计框架，并通过不确定性量化研究过渡流对外界扰动的敏感性。目的三，提出一种新的用于性能和负载分析的大数据集自适应导数增强型代理模型。

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.