Computational Aerodynamics for Future Aircraft Design

航空业面临着燃料成本上涨和环境问题的双重挑战。因此，该行业致力于到2050年将航空业的二氧化碳排放总量减少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料成本和减少二氧化碳排放的需要，因此是未来飞机设计的高度优先事项。这里提出的研究旨在通过新的非传统飞机构型、创新的空气动力学概念和流动控制来减少阻力。它涵盖了气动和多学科优化算法的发展，以及它们在非传统构型和流量控制中的应用。 其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.发展了基于牛顿-克雷洛夫-舒尔方法的高效、健壮的并行计算流体力学(CFD)算法，其高阶逐部求和算子适用于雷诺平均的Navier-Stokes方程(具有层流-湍流过渡预测)以及大涡和直接的湍流数值模拟。 2.发展基于上述CFD算法的气动外形优化算法，包括伴随方法、几何参数化、全局优化和多点问题描述，作为独立的工具和多学科优化能力的组成部分。 3.利用上述CFD和气动外形优化算法，开发了基于分区和整体方法的飞机气动结构优化算法。 4.上述算法在i)非传统飞机概念的开发和评估，以及ii)主动和被动层流控制策略的开发和评估中的应用。

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.