Hybrid finite element/statistical energy method for mid-frequency analysis of structure−acoustic systems with interval parameters

Yin, Hui; Yu, Dejie; Lü, Hui; Yin, Shengwen; Xia, Baizhan

doi:10.1016/j.jsv.2015.05.031

Cited by 22 publications

(12 citation statements)

References 24 publications

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“…The Taylor expansion is used to speed up the evaluation of the deterministic model and its derivatives in the vertex points. Recently, many sub-types of perturbation methods for interval analysis have been proposed (see e.g., [208,222,209]). However, their accuracy tends to degrade quickly when the width of the intervals increases, or when highly non-linear problems are considered.…”

Section: Perturbation Methodsmentioning

confidence: 99%

Recent Trends in the Modeling and Quantification of Non-probabilistic Uncertainty

Faes

Moens

2019

Arch Computat Methods Eng

139

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This paper gives an overview of recent advances in the field of nonprobabilistic uncertainty quantification. Both techniques for the forward propagation and inverse quantification of interval and fuzzy uncertainty are discussed. Also the modeling of spatial uncertainty in an interval and fuzzy context is discussed. An in depth discussion of a recently introduced method for the inverse quantification of spatial interval uncertainty is provided and its performance is illustrated using a case studies taken from literature. It is shown that the method enables an accurate quantification of spatial uncertainty under very low data availability and with a very limited amount of assumptions on the underlying uncertainty. Finally, also a conceptual comparison with the class of Bayesian methods for uncertainty quantification is provided.

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Section: Perturbation Methodsmentioning

confidence: 99%

Recent Trends in the Modeling and Quantification of Non-probabilistic Uncertainty

Faes

Moens

2019

Arch Computat Methods Eng

139

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“…In order to effectively deal with the uncertainty of hybrid parameters, Wang et al [91] have introduced the first-order fuzzy interval perturbation method into the hybrid FE-SEA framework, proposed the first-order fuzzy interval perturbation FE/statistical energy analysis (FFIPFE/SEA), and verified the effectiveness of the method. Yin et al [92] introduced interval parameter uncertainty and dynamic interval into a structural acoustic system based on hybrid FE-SEA framework, established a nonparametric equation and nonparametric hybrid model, and obtained interval parameter uncertainty parameters of the structural acoustic system. To further improve the computational efficiency, they put forward the second-order interval perturbation finite element/ statistical energy analysis method (SIPFEM/SEA).…”

Section: Hybrid Parameter Analysismentioning

confidence: 99%

Research Progress on High‐Intermediate Frequency Extension Methods of SEA

Zheng

Deng

et al. 2019

Shock and Vibration

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Statistical energy analysis (SEA) can accurately describe the average vibration characteristics through system energy flow and transmission feedback. It is a powerful tool to solve the problem of high-frequency acoustics-vibration. SEA is widely used in vehicles, ships, aviation, and other transportation engineering fields. However, the expansion of SEA, based on the assumption of modal equipartition and weak coupling, is limited to the intermediate frequency. Although the SEA basic theory can be extended by relaxing the hypothesis conditions or the analysis of the medium-frequency acoustics-vibration can be carried out using the finite element method (FEM) and SEA mixing method, there are still many challenges associated with these options. To improve the basic theory of SEA and knowledge of intermediate frequency extension methods, as well as attract the attention of domestic scholars, this paper describes classical SEA and intermediate frequency extension methods. First, coupling loss factor (CLF) error propagation and parameter acquisition in classical SEA are introduced, and the three relative error calculation methods of CLF are compared. Then, the method of obtaining parameters is described from three aspects of energy transfer, input load, and modal density. Second, SEA intermediate frequency extension technology (experimental statistical energy analysis (ESEA), finite element statistical energy analysis (FE-SEA), statistical modal energy distribution analysis (SMEDA), and waveguide analysis (WGA)) are introduced. Neutron structure assembly and modeling, interval and mixed interval analysis, interval variable and mixed interval variable response are also described, so as to justify the development of a hybrid, large-scale interval algorithm. Finally, the engineering application of the above method is introduced, the limitations and shortcomings of SEA and intermediate frequency extension methods are reviewed, and unsolved problems are further discussed.

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“…Finally, the integral of the probability density was solved by the numerical method. Yin et al [10,11] introduced interval parameter uncertainty into the hybrid FE-SEA method. A hybrid nonparametric-interval parameter uncertainty model is established for the acoustic vibration system.…”

Section: Introductionmentioning

confidence: 99%

Study on FE-SEA Modeling and Acoustic Performance of Heavy Duty Commercial Vehicle Based on Experimental Statistical Energy Parameters

Deng

2021

Applied Sciences

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Due to the difficulty of obtaining statistical energy parameters of complex structures and the complexity of modeling connection and model verification, the hybrid FE-SEA model has many problems in modeling complex structures. Therefore, in order to solve the above problems, this paper provides a reference for the application of the hybrid FE-SEA model in complex structures. In this paper, the hybrid FE-SEA commercial vehicle model is established by an experimental statistical energy parameter modeling method and a modification method. The model division and subsystem connection modeling of a complex substructure of a heavy vehicle cab are studied. In the hybrid model, the hybrid line connection and the hybrid point connection are established. On this basis, the parameters of the cab model were studied, and the statistical energy parameters such as modal density, internal loss factor, and coupling loss factor were obtained by the experimental method. The statistical energy parameters of the cab acoustic model are modified. Finally, the accuracy of the model is verified by vehicle test. In addition, the acoustic performance of the cab was optimized, and airtightness and acoustic packaging were verified. The full parameter modeling and correction method is adopted in this paper, which is an effective supplement to the traditional statistical energy parameter modeling method.

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Hybrid finite element/statistical energy method for mid-frequency analysis of structure−acoustic systems with interval parameters

Cited by 22 publications

References 24 publications

Recent Trends in the Modeling and Quantification of Non-probabilistic Uncertainty

Recent Trends in the Modeling and Quantification of Non-probabilistic Uncertainty

Research Progress on High‐Intermediate Frequency Extension Methods of SEA

Study on FE-SEA Modeling and Acoustic Performance of Heavy Duty Commercial Vehicle Based on Experimental Statistical Energy Parameters

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