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Acoustics design sensitivity analysis for the noise optimization of landing gears

机译:声学设计灵敏度降落齿轮噪声优化的敏感性分析

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This paper provides a new Acoustic Design Sensitivity (ADS) method for the minimization of noise on landing gear parts. The idea consists of direct differentiation of the closed-forms expressions of the acoustic pressure levels with respect to the landing gear design parameters. The outlines of the method are presented herein by considering semi-empirical formulations proposed for the acoustic pressure level but can be straightforwardly applied to other acoustics weak integral formulations or analogies. Indeed, the estimates of the noise level derivatives allow assessment of the most acoustically sensitive design parameters. Numerical implementation of the ADS method has been performed using SCILAB open code and validated by comparing with the derivatives calculated using Finite Difference Methods (FDM). Then, the sensitivity estimates have been used to minimize different (SPL and OASPL) noise objectives for a generic landing gear. The numerical examples clearly demonstrated the ability of the (ADS) method to accurately identify the appropriate design parameters that will control the bulk of the noise sensitivity. In addition, the optimum solution of the noise minimization problems is exclusively dependent on these design parameters. (C) 2019 Elsevier Ltd. All rights reserved.
机译:本文提供了一种新的声学设计灵敏度(ADS)方法,用于最小化着陆齿轮件上的噪声。该思想包括关于着陆齿轮设计参数的声压水平的闭合形式表达的直接分化。该方法的轮廓通过考虑所提出的声压水平,但可以直接施加到其他声学弱整体制剂或类似物中的半实验室。实际上,噪声水平衍生物的估计允许评估最理敏感的设计参数。已经使用Scilab开放代码执行了ADS方法的数值实现,并通过与使用有限差分方法(FDM)计算的衍生物进行比较来进行验证。然后,已经使用灵敏度估计来最小化通用着陆齿轮的不同(SPL和OASPL)噪声物体。数值示例清楚地证明了(ADS)方法准确识别将控制大部分噪声灵敏度的适当设计参数的能力。此外,噪声最小化问题的最佳解决方案仅依赖于这些设计参数。 (c)2019 Elsevier Ltd.保留所有权利。

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