Parameter Identification of a Sandwich Beam Using Numerical-Based Inhomogeneous Wave Correlation Method

Author(s):  
R. Ajili ◽  
O. Bareille ◽  
M.-L. Bouazizi ◽  
M.-N. Ichchou ◽  
N. Bouhaddi
2018 ◽  
Vol 35 (6) ◽  
pp. 2126-2164 ◽  
Author(s):  
Ramzi Lajili ◽  
Olivier Bareille ◽  
Mohamed Lamjed Bouazizi ◽  
Mohamed Ichchou ◽  
Noureddine Bouhaddi

Purpose This paper aims to propose numerical-based and experiment-based identification processes, accounting for uncertainties to identify structural parameters, in a wave propagation framework. Design/methodology/approach A variant of the inhomogeneous wave correlation (IWC) method is proposed. It consists on identifying the propagation parameters, such as the wavenumber and the wave attenuation, from the frequency response functions. The latters can be computed numerically or experimentally. The identification process is thus called numerical-based or experiment-based, respectively. The proposed variant of the IWC method is then combined with the Latin hypercube sampling method for uncertainty propagation. Stochastic processes are consequently proposed allowing more realistic identification. Findings The proposed variant of the IWC method permits to identify accurately the propagation parameters of isotropic and composite beams, whatever the type of the identification process in which it is included: numerical-based or experiment-based. Its efficiency is proved with respect to an analytical model and the Mc Daniel method, considered as reference. The application of the stochastic identification processes shows good agreement between simulation and experiment-based results and that all identified parameters are affected by uncertainties, except damping. Originality/value The proposed variant of the IWC method is an accurate alternative for structural identification on wide frequency ranges. Numerical-based identification process can reduce experiments’ cost without significant loss of accuracy. Statistical investigations of the randomness of identified parameters illustrate the robustness of identification against uncertainties.


2020 ◽  
Vol 135 ◽  
pp. 106407 ◽  
Author(s):  
G. Tufano ◽  
F. Errico ◽  
O. Robin ◽  
C. Droz ◽  
M. Ichchou ◽  
...  

Author(s):  
D. E. Luzzi ◽  
L. D. Marks ◽  
M. I. Buckett

As the HREM becomes increasingly used for the study of dynamic localized phenomena, the development of techniques to recover the desired information from a real image is important. Often, the important features are not strongly scattering in comparison to the matrix material in addition to being masked by statistical and amorphous noise. The desired information will usually involve the accurate knowledge of the position and intensity of the contrast. In order to decipher the desired information from a complex image, cross-correlation (xcf) techniques can be utilized. Unlike other image processing methods which rely on data massaging (e.g. high/low pass filtering or Fourier filtering), the cross-correlation method is a rigorous data reduction technique with no a priori assumptions.We have examined basic cross-correlation procedures using images of discrete gaussian peaks and have developed an iterative procedure to greatly enhance the capabilities of these techniques when the contrast from the peaks overlap.


2013 ◽  
Vol 58 (2) ◽  
pp. 122-125 ◽  
Author(s):  
O.V. Gnatovskyy ◽  
◽  
A.M. Negriyko ◽  
V.O. Gnatovskyy ◽  
A.V. Sidorenko ◽  
...  

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