Estimation of the 3D residual strain field in the arterial wall of a bovine aorta using optical full-field measurements and finite element reconstruction

Author(s):  
Genovese Katia ◽  
Badel Pierre ◽  
Avril Stéphane
2020 ◽  
Vol 77 ◽  
pp. 125-129
Author(s):  
Alexander Abel ◽  
Stephanie L. Kahmann ◽  
Stephen Mellon ◽  
Manfred Staat ◽  
Alexander Jung

2006 ◽  
Vol 3-4 ◽  
pp. 161-166 ◽  
Author(s):  
Raphaël Moulart ◽  
Stephane Avril ◽  
Fabrice Pierron

This paper deals with the simultaneous identification of the four through-thickness orthotropic rigidities of a thick composite tube. A diametral compression test has been carried out on a glass/epoxy ring cut from the tube. The full strain field has been measured over one face of the sample with the grid method. The measured fields have been processed with the Virtual Fields Method to identify the rigidities of the material. At the beginning, discrepancies and significant variations occurred in the identified moduli due to inhomogeneous distribution of the strains through the thickness. A method based on a simultaneous measurement on both sides of the ring has been adopted. Very satisfactory results have been obtained using this methodology.


2016 ◽  
Vol 49 (5) ◽  
pp. 802-806 ◽  
Author(s):  
Lorenzo Grassi ◽  
Sami P. Väänänen ◽  
Matti Ristinmaa ◽  
Jukka S. Jurvelin ◽  
Hanna Isaksson

2010 ◽  
Vol 24-25 ◽  
pp. 365-370 ◽  
Author(s):  
Wei Zhuo Wang ◽  
John E. Mottershead ◽  
Amol Patki ◽  
Eann A Patterson

The achievement of high levels of confidence in finite element models involves their validation using measured responses such as static strains or vibration mode shapes. A huge amount of data with a high level of information redundancy is usually obtained in both the detailed finite element prediction and the full-field measurements so that achieving a meaningful validation becomes a challenging problem. In order to extract useful shape features from such data, image processing and pattern recognition techniques may be used. One of the most commonly adopted shape feature extraction procedures is the Fourier transform in which the original data may be expressed as a set of coefficients (coordinates) of the decomposition kernels (bases) in the feature space. Localised effects can be detected by the wavelet transform. The acquired shape features are succinct and therefore simplify the model validation, based on the full-field data, allowing it to be achieved in a more effective and efficient way. In this paper, full-field finite element strain patterns of a plate with a centred circular hole are considered. A special set of orthonormal shape decomposition kernels based on the circular Zernike polynomials are constructed by the Gram-Schmidt orthonormalization process. It is found that the strain patterns can suitably be represented by only a very small number of shape features from the derived kernels.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1388
Author(s):  
Daniele Oboe ◽  
Luca Colombo ◽  
Claudio Sbarufatti ◽  
Marco Giglio

The inverse Finite Element Method (iFEM) is receiving more attention for shape sensing due to its independence from the material properties and the external load. However, a proper definition of the model geometry with its boundary conditions is required, together with the acquisition of the structure’s strain field with optimized sensor networks. The iFEM model definition is not trivial in the case of complex structures, in particular, if sensors are not applied on the whole structure allowing just a partial definition of the input strain field. To overcome this issue, this research proposes a simplified iFEM model in which the geometrical complexity is reduced and boundary conditions are tuned with the superimposition of the effects to behave as the real structure. The procedure is assessed for a complex aeronautical structure, where the reference displacement field is first computed in a numerical framework with input strains coming from a direct finite element analysis, confirming the effectiveness of the iFEM based on a simplified geometry. Finally, the model is fed with experimentally acquired strain measurements and the performance of the method is assessed in presence of a high level of uncertainty.


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