SEA modeling and experimental validation of structure-borne noise paths in an aircraft fuselage

Cordioli, Júlio A.; Klug, Francisco K.; Gerges, Samir N. Y.; Santos, Marcelo; Mello, Rafael de

doi:10.4271/2008-36-0066

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Joana [5] predicted the cabin noise caused by the turbulent boundary noise source of blended wing body aircraft using engineering methods. Cordioli [6] studied the structural sound transmission path of the fuselage using Statistical Energy Analysis (SEA) method. Wang Yigang [7] studied the sound transmission characteristics of typical cabin structures using SEA method.…”

Section: Introductionmentioning

confidence: 99%

Prediction of aircraft cabin noise by statistical energy analysis

Song,

Xu,

Lin

2024

J. Phys.: Conf. Ser.

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The noise level in the aircraft cabin is an important indicator on market competitiveness, and it is a considerable challenge to reduce the noise in the cabin at a relatively small cost, so efficient and accurate forecasting tools are required. In the aviation industry, Statistical Energy Analysis (SEA) is widely used to predict mid- and high-frequency noise in aircraft cabins. It has the advantages of simple method and low requirement of structure details. This paper models the cabin of a certain type of aircraft, and uses statistical energy methods to predict the noise level in the cabin during ground and cruise conditions. Among them, the prediction result of the cabin noise on the ground is in good agreement with the test results above 250Hz, which verifies the correctness of the model. During cruise, the pressure fluctuation on the outer surface of the front fuselage is dominated by turbulent boundary layer noise. The analysis shows that the Robertson model can predict turbulent boundary layer noise well, and the difference between the predicted single-point spectrum and the experimental value is less than 1dB. The cabin noise predicted by only loading the turbulent boundary layer noise source is consistent with the experimental results, but the sound pressure level in some frequency bands is low.

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Section: Introductionmentioning

confidence: 99%

Prediction of aircraft cabin noise by statistical energy analysis

Song,

Xu,

Lin

2024

J. Phys.: Conf. Ser.

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“…Nowadays, some achievements have been obtained in vehicle NVH field. Forssén et al built the interior sound field of a railway vehicle by using SEA method [8] Cordioli et al presented the SEA modeling and experimental validation of structure borne noise paths in an aircraft fuselage [9]. Musser et al applied the SEA method in component level vehicle target setting, vehicle NVH design cycle, and sound package optimization [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Vehicle Sound Package in Middle Frequency Using Gray Relational Analysis Coupled with Principal Component Analysis

et al. 2014

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Communicated by Edmund NowakThis research studies optimization design of the thickness of sound packages for a passenger car. The major characteristics indexes for performance determined to evaluate the process are sound pressure level of the interior middle frequency noise and weight of the sound package. Three kinds of materials of sound packages are selected for the optimization process. The corresponding parameters of the sound packages are the thickness of the insulation plate for outer side of the firewall, thickness of the sound absorbing wool for inner side of the firewall, thickness of PU foam for the front floor, and thickness of PU foam for the rear floor, respectively. In this paper, the optimization procedure is a multi-objective optimization. Therefore, gray relational analysis (GRA) is applied to decide the optimal combination of sound package parameters. Furthermore, the principal component analysis (PCA) is used to calculate the weighting values which are corresponding to multiple performance characteristics. Then, the results of the confirmation tests uncover that GRA coupled with principal analysis methods can effectively be applied to find the optimal combination of the thickness of the sound packages at different positions for a passenger car. Thus, the proposed method can be a useful tool to improve the automotive interior middle frequency noise and lower the weight of the sound packages. Additionally, it will also be useful for automotive manufactures and designers in other fields.

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SEA modeling and experimental validation of structure-borne noise paths in an aircraft fuselage

Cited by 2 publications

References 12 publications

Prediction of aircraft cabin noise by statistical energy analysis

Prediction of aircraft cabin noise by statistical energy analysis

Multi-Objective Optimization of Vehicle Sound Package in Middle Frequency Using Gray Relational Analysis Coupled with Principal Component Analysis

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