采用Coanda作动机构的d型钝体开闭环控制

P. Oswald, R. Semaan, B. R. Noack
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引用次数: 2

摘要

本文研究了在d型钝体上采用开环和闭环Coanda驱动的减阻和增效效果。开环测量是通过扫描驱动频率和力矩系数所跨越的驱动参数空间来实现的。在最大功率系数为0.22的情况下,相对于非驱动情况,阻力减少了33%。闭环控制采用机器学习控制(MLC)。MLC是一种无模型控制方法,旨在优化预定义的成本函数。优化了两个成本函数,即阻力系数和阻力动量系数之和。MLC系统的阻力降低高达27%,最大功率比为0.154,与开环系统的结果相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Open- and closed loop control on a D-shaped bluff body equipped with Coanda actuation
The present study investigates drag reductions and efficiency increases by open-and closed-loop Coanda actuation on a D-shaped bluff body. Open-loop measurements are performed by scanning the actuation parameter space spanned by the actuation frequency and the moment coefficient. At a maximum power coefficient of 0.22 a drag reduction of 33 % relative to the unactuated case is observed. Closed loop control is conducted using machine learning control (MLC). MLC is a model-free control methodology that seeks to optimize a predefined cost function. Two cost functions are optimized , the drag coefficient and the sum of drag & momentum coefficients. MLC yields a drag reduction of up to 27 % and a maximum power ratio of 0.154, which are comparable to the open-loop results.
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