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Analytical and numerical modeling, sensitivity analysis, and multi- objective optimization of the acoustic performance of the herschel- quincke tube

机译:分析与数值建模,灵敏度分析和Herschel-Quincke管的声学性能的多目标优化

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This study presents the assessments of the acoustic performance of a Herschel-Quincke (HQ) tube, which includes sensitivity analysis and multi-objective optimization of its design variables. A proper model introduced using the flow characteristics of the HQ tube. Input variables were frequency (f), temperature (T), the ratio of areas (R), and tube length (L). These variables were chosen to be varied in a specified range to best characterize the exhaust flow in internal combustion engines. Then a proper multi-objective genetic algorithm (MOGA) was developed for the acoustic performance and geometry optimization of a two-duct HQ tube; the objectives were maximizing the transmission loss (TL) and at the same time minimizing the backpressure (BP). Besides, the local sensitivity analysis using numerical derivative and variance-based global sensitivity analysis (GSA) using Monte Carlo sampling was performed for the analytical model of the HQ tube. The results showed that the length of the bypass tube is a crucial factor for the maximum sensitivity index (SI) of the TL, while the SI of the BP was maximum for the ratio of areas. The proposed analytical model was proved to be reliable for the TL, showing low values of the error of the sensitivity index (eSI) and less reliable for the BP parameter, showing higher eSI values. For the evaluation of the TL sensitivity, Monte Carlo sampling is relatively inaccurate in the small sample size of 200. It was also observed that the Uniform distribution had lower eSI in lower sample sizes; however, Sobol sampling showed better performance in higher sample sizes. The MOGA optimization proved to be successful in maximizing the TL for the frequencies between 105.84 and 1981.11 Hz, with the TL greater than 20 dB, and the BP less than 0.1. The most efficient solution among the Pareto set after a tradeoff was at 105.84 Hz, for which the TL and the BP were 36.47 dB and 1.50E-02, respectively. The model with the best goodness of fit to represent the Pareto front was the power model with two terms. Then, the acoustic performance of the optimized geometry was investigated using computational aeroacoustics (CAA) in the presence of mean flow in Fluent software. Using the CAA approach, the maximum TL value was obtained for 104 0.4 Hz as 12.14 dB. The simulated TL by CAA had more broadband behaviors with fewer peaks than the analytical approach. The results of this study demonstrated the remarkable potential of the MOGA optimization and sensitivity analysis for acoustic performance and topology optimization for possible applications in internal combustion engines. (C) 2021 Elsevier Ltd. All rights reserved.
机译:本研究介绍了Herschel-Quincke(HQ)管的声学性能的评估,包括灵敏度分析和其设计变量的多目标优化。使用HQ管的流动特性引入的适当模型。输入变量是频率(f),温度(t),区域(R)的比率和管长度(L)。选择这些变量在指定范围内变化,以最佳地表征内燃机中的排气流动。然后开发了一种适当的多目标遗传算法(MOGA),用于双管道HQ管的声学性能和几何优化;目标最大化变速器损耗(TL),同时最小化背压(BP)。此外,对HQ管的分析模型进行了使用Monte Carlo采样的使用数值衍生物和基于方差的全局敏感性分析(GSA)的局部敏感性分析。结果表明,旁通管的长度是T1的最大灵敏度指数(Si)的关键因素,而BP的Si最大限制地为区域的比例。已证明所提出的分析模型对TL可靠,显示了敏感性指数(ESI)误差的低值,并且对BP参数的可靠性不太可靠,显示出更高的ESI值。为了评价T1敏感性,蒙特卡罗采样在比200的小样本尺寸中相对不准确。还观察到均匀分布在较低样本尺寸下具有较低的ESI;然而,Sobol采样在更高的样本尺寸下表现出更好的性能。 MOGA优化证明是成功的,以最大化105.84和1981.11 Hz的频率的TL,TL大于20 dB,BP小于0.1。在权衡后,帕累托设定的最有效的解决方案是105.84 Hz,其中TL和BP分别为36.47dB和1.50E-02。具有最佳贴合性的模型代表帕累托前线是具有两个术语的电力模型。然后,在流利软件的平均流量存在下,使用计算气流理学(CAA)研究了优化几何体的声学性能。使用CAA方法,获得104 0.4Hz为12.14dB的最大TL值。 CAA的模拟TL具有比分析方法更少的宽频率行为。本研究的结果表明了MOGA优化和声学性能和拓扑优化的敏感性分析的显着潜力,用于内燃机中可能的应用。 (c)2021 elestvier有限公司保留所有权利。

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