Computational Aerodynamics for Future Aircraft Design

飞机制造业面临着燃料成本上升和环境问题的双重挑战。因此，航空业致力于到2050年将航空业的总体二氧化碳排放量减少50%，这将需要大量的技术进步。提高飞机燃油效率可以解决不断上升的燃油成本和减少二氧化碳排放的需求，因此是未来飞机设计的优先事项。这里提出的研究旨在通过新颖的非常规飞机构型、创新的空气动力学概念和流动控制来减少阻力。它涵盖了空气动力学和多学科优化算法的发展及其在非常规构型和流动控制中的应用。 长期目标是为下一代飞机的设计做出贡献，减少对环境的影响。短期目标如下： 1.开发基于Newton-Krylov-Schur方法的高效和鲁棒的并行计算流体动力学（CFD）算法，该方法具有适用于雷诺平均Navier-Stokes方程（具有层流湍流转捩预测）的高阶逐部分求和算子，以及湍流的大涡和直接数值模拟。 2.基于上述CFD算法开发气动外形优化算法，包括伴随方法、几何参数化、全局优化和多点问题公式化，既作为独立工具，也作为多学科优化能力的组成部分。 3.利用上述计算流体动力学和气动外形优化算法，在分区和整体方法的基础上，开发用于飞机设计的气动结构优化算法。 4.上述算法在下列方面的应用：i）非常规飞机方案的研制和鉴定，ii）主动和被动层流控制策略的研制和鉴定。

The aircraft industry faces the twin challenges of rising fuel costs and environmental concerns. Consequently the industry is committed to reducing overall CO2 emissions from aviation by 50% by 2050, which will require a great deal of technological progress. Improving aircraft fuel efficiency can address both rising fuel costs and the need to reduce CO2 emissions and is therefore a high priority in future aircraft design. The research proposed here is aimed at drag reduction through novel unconventional aircraft configurations, innovative aerodynamic concepts, and flow control. It spans both the development of algorithms for aerodynamic and multidisciplinary optimization and their application to unconventional configurations and flow control. The long-term objective is to contribute toward the design of the next generation of aircraft with reduced environmental impact. The short-term objectives are as follows: 1. Development of highly efficient and robust parallel computational fluid dynamics (CFD) algorithms based on the Newton-Krylov-Schur approach with higher-order summation-by-parts operators applicable to the Reynolds-averaged Navier-Stokes equations (with laminar-turbulent transition prediction) as well as large-eddy and direct numerical simulations of turbulent flows. 2. Development of aerodynamic shape optimization algorithms based on the above CFD algorithms, including adjoint methods, geometry parameterization, global optimization, and multipoint problem formulation, both as a standalone tool and as a component of a multidisciplinary optimization capability. 3. Development of aerostructural optimization algorithms for aircraft design based on both partitioned and monolithic approaches using the above CFD and aerodynamic shape optimization algorithms. 4. Application of the above algorithms to i) development and evaluation of unconventional aircraft concepts, and ii) development and evaluation of active and passive laminar flow control strategies.