EAGER: CFD-based Adjoint Methods for Design Applications with Unsteady Separated Flows

在飞行器设计中使用了一种称为伴随优化的计算方法，以找到满足所需性能的最佳外形，如增强升力或减小气动外形的阻力。过去，这种方法被用于简单流场中的流线型形状，但最近它被应用于更复杂的形状，如复杂、湍流流场中的汽车。然而，流动模拟的准确性和设计过程的有效性尚不清楚。空气动力优化的准确性至关重要的一个应用是鲁格冬奥会项目。历史表明，奥运会奖牌是由千分之几秒的时差决定的。空气动力学是复杂的，因为几何形状本身是复杂的，而且骑手/雪橇后面的流动涉及大范围的非定常湍流运动(类似于车辆)。传统上，雪橇设备是由前运动员开发的，是根据直觉、感觉和经验手工塑造的。流动条件，以及历史上缺乏基于科学的设计优化，使得雪橇成为研究基于伴随的优化执行气动优化的有效性的理想选择。本项目中针对非定常流动的伴随设计的成功设计、建造和实验验证将潜在地对汽车/卡车、船/船和先进的飞行器的未来设计具有显著的益处，以最小化阻力、提高转弯/机动时的性能、或防止加/减速时的流分离。本工作的目的是通过实验验证来研究伴随方法的有效性，以达到在湍流、非定常、分离流动中的最佳形状。将开发一种基于伴随的方法，并将其应用于雪橇/骑手模型，其目标是修改雪橇形状以将阻力降至最低。将进行实验测试，以提供整个过程中中间形状的性能数据，以确定伴随过程是否准确地预测了实际性能并收敛到最优解。实验验证将通过表面压力测量、阻力测量和模型周围流场的测量相结合来完成。除了这些技术目标之外，还有一个高级目标，即将科学优化的比赛技术转让给美国鲁格协会用于奥运会比赛。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

A computational method called adjoint based optimization is used in vehicle design to find optimal shapes for desired performance, such enhanced lift or reduced drag of aerodynamic shapes. Historically, this method has been used on streamlined shapes in simple flow fields, but more recently it has been applied to more complex shapes such as automobiles in complex, turbulent flow fields. However, the accuracy of the flow simulations and the effectiveness of the design process are unclear. An application where the accuracy of aerodynamic optimization is critical is the Winter Olympic sport of Luge. History has shown that Olympic medals have been determined by time differences of only a few thousandths of a second. The aerodynamics are complicated because the geometry itself is complex and the flow behind the rider/sled involves large scale unsteady turbulent motion (similar to a vehicle). Traditionally luge equipment has been developed by former athletes and was hand shaped based on hunches, feel, and experience. The flow conditions, and historic lack of science based design optimization, make luge sleds an ideal choice for investigation of the effectiveness of adjoint based optimization to perform aerodynamic optimization The successful design, build, and experimentally validating adjoint designs for unsteady flows in this project can potentially have a significant benefit to future designs of cars/trucks, boat/ships, and advanced air vehicles for drag minimization, increased performance during turns/maneuvering, or the prevention of flow separation while accelerating/decelerating.The goal of this work is to investigate the effectiveness of adjoint methods to reach an optimal shape in turbulent, unsteady, separated flows using experimental validation. An adjoint based method will be developed and applied to a luge sled/rider model that targets modification of the sled shape to minimize drag. Experimental testing will be performed to provide performance data of the intermediate shapes throughout the process to ascertain if the adjoint process is accurately predicting the actual performance and converging towards an optimal solution. The experimental validation will be accomplished by a combination of surface pressure measurement, drag measurement and measurement of the flow fields around the model. Beyond these technical goals is the high-level goal of transferring scientifically optimized race technology to the US Luge Association for use in Olympic competition.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.