Numerical modelling of vibro-acoustic problem in presence of uncertainty: Application to a vehicle cabin

Dammak, Khalil; Koubaa, Sana; Hami, Abdelkhalak El; Walha, Lassâad; Haddar, Mohamed

doi:10.1016/j.apacoust.2017.06.001

Cited by 42 publications

(10 citation statements)

References 31 publications

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“…It is a coupled problem between the internal acoustic pressure and the vibration of the structure. The finite element discretization of the structural part and that of the fluid leads to the equations of motion corresponding to each part as follow [10,43,44]:…”

Section: Vibro-acoustic Formulationmentioning

confidence: 99%

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Uncertainty Analysis Based on Kriging Meta-Model for Acoustic-Structural Problems

2022

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This paper consists of evaluating the performance of a vibro-acoustic model in the presence of uncertainties in the geometric and material parameters of the model using Monte Carlo simulations (MCS). The purpose of using a meta-model is to reduce the computational cost of finite element simulations. Uncertainty analysis requires a large sample of MCS to predict the effect of uncertain parameters on the system response. So, if this study is done through the finite element method (FEM), then the computational cost will be very important. Furthermore, for that, we use meta-models to be able to conduct an efficient uncertainty analysis more quickly. In the present contribution, the approximated meta-model is verified and validated using error measures and cross-validation (CV). Then, the uncertainty analysis is performed by Monte Carlo simulations using the computed Kriging meta-model. The developed methodology has been applied in two vibro-acoustic models. In these two models, the covariance of uncertainty of geometric and physical (elasticity and density) parameters are equal to 2% and 5% respectively. The obtained results prove that the suggested methodology of uncertainty propagation based on the Kriging meta-model can be considered as a very efficient and sufficiently accurate approach for the quantification of uncertainties in acoustic-structural systems.

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Section: Vibro-acoustic Formulationmentioning

confidence: 99%

“…The finite element method (FEM) denotes a very powerful method, which can be used in order to obtain an approximate solution to the response of the coupled system. Dammak et al [10] studied the vibro-acoustic response of a vehicle cabin in presence of uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Analysis Based on Kriging Meta-Model for Acoustic-Structural Problems

2022

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“…Soize [1], among others, demonstrated a non-parametric approach by using randomized system matrizes for a vibro-acoustic model while Dammak et al [2] used spectral stochastic methods to model parametric uncertainties in the acoustics of a vehicle cabin. On the one hand, law regulation become more strict concerning noise pollution.…”

Section: Introductionmentioning

confidence: 99%

“…The uncertainty quantification (UQ) in acoustic systems forms a relatively new field of application in the UQ community. Soize [1], among others, demonstrated a non-parametric approach by using randomized system matrizes for a vibro-acoustic model while Dammak et al [2] used spectral stochastic methods to model parametric uncertainties in the acoustics of a vehicle cabin. Further applications can be found in the modelling of acoustic wave propagation in materials with spatially varying uncertain material properties [3] or acoustic scattering for obstacles with uncertain shapes [4].…”

Section: Introductionmentioning

confidence: 99%

Gaussian process based surrogate modelling of acoustic systems

Kohlsche

Lippert

Estorff

2019

Proc Appl Math and Mech

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The numerical simulation of acoustic problems is, for itself, a quite difficult task since the underlying systems are usually highly complex with a broad frequency range and high sensitivity. Due to this complexity and the corresponding computational burden, tasks like optimization and uncertainty quantification (UQ) are seldom performed in acoustics. Especially when dealing with polymorphic uncertainties where combined techniques of UQ might be required, a direct use of the model is not viable. To allow such engineering tasks, the construction of a cheap surrogate or reduced model is common practice in order to allow a large number of model evaluations at low costs. For acoustic systems, the construction of a reasonably accurate surrogate model can become a challenging task since many systems operate in the frequency domain where phenomena like resonance and interference can cause highly nonlinear responses. In this paper, a surrogate model based on the combination of a parametric model for capturing local nonlinearities and a random process regression for modelling the global trend is presented. The basic procedure based on previous works of the authors is extended to a predict the system response both for unobserved parameters and frequencies. The procedure is demonstrated for a representative example namely the acoustic simulation of a car interior, and further improvements in accuracy and efficiency by the usage of multilevel information are discussed.

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“…Several methods are proposed in the literature for considering uncertainties. Monte Carlo (MC) method is well-known in this field but it is often costly because of the great numbers of samples required in the aim to have a reasonable accuracy [5][6][7]. Polynomial chaos method is also presented in the literature as an attractive probabilistic method for considering uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling of shape memory alloy problem in presence of perturbation: application to Cu-Al-Zn-Mn specimen

Abid

Hami

Merzouki

et al. 2019

Int. J. Simul. Multidisci. Des. Optim.

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This paper proposes a methodology for taking into consideration uncertainties based on polynomial chaos (PC). The proposed approach is used in order to determine the response of Cu-Al-Zn-Mn shape memory alloy specimen with uncertainties associated to material parameters. The simulation results are obtained by PC method. The proposed method seems to be an efficient probabilistic tool. It is worth mentioning that PC approach is an interesting alternative for the parametric studies. This technique is more efficient compared to MC approach.

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Numerical modelling of vibro-acoustic problem in presence of uncertainty: Application to a vehicle cabin

Cited by 42 publications

References 31 publications

Uncertainty Analysis Based on Kriging Meta-Model for Acoustic-Structural Problems

Uncertainty Analysis Based on Kriging Meta-Model for Acoustic-Structural Problems

Gaussian process based surrogate modelling of acoustic systems

Numerical modeling of shape memory alloy problem in presence of perturbation: application to Cu-Al-Zn-Mn specimen

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