A statistical characterization method for damping material properties and its application to structural-acoustic system design

Jung, Byung C.; Lee, Dooho; Youn, Byeng D.; Lee, Soo-Bum

doi:10.1007/s12206-011-0517-6

Cited by 24 publications

(12 citation statements)

References 23 publications

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“…Then, the experimental data for the rubber and the maximum likelihood approach can be used to estimate the uncertainties of the material properties and of the modelling error in terms of the material model parameters. 10,23 This procedure is briefly explained here.…”

Section: Characterization Of Uncertaintiesmentioning

confidence: 99%

“…[31][32][33] Among the uncertainty propagation analysis methods, the eigenvector dimension reduction (EDR) method 24 is used in this study because it requires only three or five samples (responses from the automotive systems) for each random variable. Thus, the EDR method was used due to its enhanced accuracy and efficiency in probability analysis of complex systems such as structural design problems, 10,[34][35][36] vibro-acoustic problems, 23 automotive problems, 37 and various fields. 38,39 …”

Section: Uncertainty Propagation Analysismentioning

confidence: 99%

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Variability analysis of vibrational responses in a passenger car considering the uncertainties of elastomers

Kwon

Lee

2015

Proceedings of the Institution of Mechanical Engineers, Part C:

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Passenger cars have many elastomeric joints that are used to reduce the vibration transmission from the source to the cabin structure. In the design stage, the dynamic characteristics of the elastomeric joints are optimally determined in order to satisfy the design goals for interior noise and vibration. However, the material properties of the elastomeric joints have large variations due to production variability. In addition, operational conditions, e.g. environmental temperature, vary according to the locations of the car. As a result, the vibrational comfort of a passenger car exhibits large variations. In this paper, the amount of vibration fluctuation due to uncertain elastomeric joint parameters is estimated using a statistical approach. First, the dynamic characteristics of the elastomers are described using the fractional derivative model. The uncertainties of the fractional derivative model parameters of the elastomers are characterized using a statistical calibration approach based on specimen test data. Then, a finite element model for the elastomers and the passenger car structure are constructed in order to calculate the vibrational response. In order to estimate the variability of the vibrational response due to the uncertainties of the elastomers, uncertainty propagation analyses are conducted using the eigenvector dimension reduction (EDR) method. The operational conditions such as temperature are also included in the variability analysis. The performance of the EDR method is assessed through comparing the estimated response distribution with that of the Monte Carlo simulation (MCS) method in a simplified structure. The variability analysis results demonstrate that the vibrational response variation due to the uncertainties of the elastomers can be efficiently predicted using the proposed method. The proposed variability analysis procedure could be an effective tool in the design stage for quality control of passenger car comfort.

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Section: Characterization Of Uncertaintiesmentioning

confidence: 99%

Section: Uncertainty Propagation Analysismentioning

confidence: 99%

Variability analysis of vibrational responses in a passenger car considering the uncertainties of elastomers

Kwon

Lee

2015

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…From the estimated statistical moments, the EDR method extracts its samples to obtain the PDF of a system response. It has been demonstrated that the EDR method is accurate in calculating the PDF and reliability in structural-acoustic systems [28]. For further details on the EDR method, refer to Ref.…”

Section: Uncertainty Propagation Analysis In the Fe Modelmentioning

confidence: 99%

Statistical calibration of a finite element model for human middle ear

Lee

Ahn²

2015

J Mech Sci Technol

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A Finite element (FE) model of a human middle ear is developed, assessed, and updated using a statistical approach. The model consists of three ossicles (malleus, incus, and stapes), a tympanic membrane, tendons, and ligaments. The uncertainty of the model input parameters associated with the material properties and boundary conditions are considered in order to assess the validity of the model. The variation of the umbo displacement transfer function (UDTF) as a result of the uncertainty of the model input parameters is estimated and compared with those from experiments. Using the analysis of variance (ANOVA) with a three-level orthogonal array, the most important calibration parameters, which are composed of stiffness-related and density variables, are selected. Furthermore, a metric for statistical calibration is introduced. Through minimizing the calibration metric, the calibration parameters are updated in order to enhance the performance of the middle ear FE model. The proposed statistical calibration framework effectively improves the middle ear FE model performance.

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“…Damping materials are widely used in modern industries as a kind of crucial material to reduce vibration . In the automobile, precise instrument, and construction industries, vibration causes immaterial abrasion, damage of structure, degradation of stability, and decrease of service lifetime.…”

Section: Introductionmentioning

confidence: 99%

4,4′‐Methylenebis(2,6‐di‐t‐butylphenol) as filler in high‐damping chlorinated polyethylene composites

Sheng²,

Zhang

2019

J of Applied Polymer Sci

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Damping materials are widely used in the modern industry as a kind of material for reducing vibration. The high‐damping composites consisting of chlorinated polyethylene (CPE) and 4,4′‐Methylenebis(2,6‐di‐t‐butylphenol) (AO‐4426) were successfully prepared in this work. The microstructural and mechanical properties of the CPE/AO‐4426 composites were systematically investigated by using SEM, DSC, FTIR, and DMA. From the SEM, most of hindered phenol was dissolved in the CPE matrix and formed a fine dispersion. The results of DSC and FTIR suggested that strong intermolecular interaction like the hydrogen bonding was formed between the AO‐4426 and CPE. It was found that with the increase of AO‐4426 content, a new transition appeared above the glass transition temperature of the CPE matrix, with higher glass transition temperature and higher tan δ value than the neat CPE. As expected, the hybrid displayed excellent performance and had exciting potential applications as a damping material. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 48321.

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A statistical characterization method for damping material properties and its application to structural-acoustic system design

Cited by 24 publications

References 23 publications

Variability analysis of vibrational responses in a passenger car considering the uncertainties of elastomers

Variability analysis of vibrational responses in a passenger car considering the uncertainties of elastomers

Statistical calibration of a finite element model for human middle ear

4,4′‐Methylenebis(2,6‐di‐t‐butylphenol) as filler in high‐damping chlorinated polyethylene composites

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