Assessment and Optimization of Dynamic Stall Semi-empirical Model for Pitching Aerofoils

Enrico Galli, Gregorio Frassoldati, Davide Prederi, Giuseppe Quaranta
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Abstract

Dynamic stall is a phenomenon affecting aerofoils in unsteady flows which is particularly relevant in the rotary-wing field. Semi-empirical models are simplified tools to simulate this phenomenon, especially during preliminary design phases and for aeroelastic assessments. However, they need a large number of tuning parameters to provide reliable estimations of unsteady airloads. To face this problem, a parameter identification procedure based on sequential resolutions of optimization problems using a genetic algorithm is developed and it is applied to the state-space formulation of a modified version of the so-called "Second Generation” Leishman-Beddoes model. The effects of the optimal parameters on the model prediction capabilities are discussed and the variability of the parameters with reduced frequency is studied. The estimations of the unsteady airloads obtained by applying the optimization of parameters show a great improvement in the correlation of the experimental data if compared to the predictions obtained by using the parameters provided in the literature, especially for pitching moments where the negative peaks are very well described. These improvements justify the need for optimization to set the parameters.

俯仰气膜动态失速半经验模型的评估与优化
动态失速是影响非定常流动翼的一种现象,在旋翼领域尤为重要。半经验模型是模拟这种现象的简化工具,特别是在初步设计阶段和气动弹性评估中。然而,它们需要大量的调谐参数来提供可靠的非定常航空载荷估计。为了解决这一问题,开发了一种基于遗传算法的优化问题顺序求解的参数识别程序,并将其应用于所谓的“第二代”Leishman-Beddoes模型的修改版本的状态空间公式。讨论了最优参数对模型预测能力的影响,并研究了参数的降频变异性。应用参数优化得到的非定常气动载荷的估计,与使用文献中提供的参数得到的预测相比,在实验数据的相关性方面有了很大的提高,特别是俯仰力矩的负峰描述得很好。这些改进证明需要优化设置参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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