A hybrid framework for nonlinear dynamic simulations including full-field optical measurements and image decomposition algorithms

Abstract

Innovative designs of transport vehicles need to be validated in order to demonstrate reliability and provide confidence. It is normal practice to study the mechanical response of the structural elements by comparing numerical results obtained from finite element simulation models with results obtained from experiment. In this frame, the use of whole-field optical techniques has been proven successful in the validation of deformation, strain, or vibration modes. The strength of full-field optical techniques is that the entire displacement field can be acquired. The objective of this article is to integrate full-field optical measurement methodologies with state-of-the-art computational simulation techniques for nonlinear transient dynamic events. In this frame, composite car bonnet frame structures of dimensions about 1.8 m × 0.8 m are considered. They have been tested in low-velocity mass-drop impact loading with impact energies ranging from 20 to 200 J. In parallel, simulation models of the car bonnet frame have been developed using layered shell elements. The Zernike shape descriptor approach was used to decompose numerical and experimental data into moments for comparison purposes. A very good agreement between numerical and experimental results was observed. Therefore, integration of numerical analysis with full-field optical measurements along with sophisticated comparison techniques can increase design reliability.

On the validation of solid mechanics models using optical measurements and data decomposition

“…for fingerprint recognition [11] and human face recognition [12] can be appropriately adapted for this purpose. Orthogonal decomposition to reduce the dimensionality of 'raw' data has been recently applied to displacement and strain image decomposition [13][14][15], as well as to finite element model updating [16]. Orthogonal polynomials, such as Zernike, Tchebichef or Krawtchouk are advantageous because they are very effective in data reduction and are also invariant to scale, rotation and translation, thus enabling direct comparison of results regardless of whether the data fields are in the same coordinate system, have the same scale, orientation, or sampling grid.…”

Application of 3D Digital Image Correlation for Development and Validation of FEM Model of Self-Supporting Arch Structures

“…The displacements are marked as follows: U(X), V(Y) and W(Z). The horizontal displacements U (X)- Figure 9a, i.e., in the arch plane are compatible in the reference points U (3, 4), U (5,6) and U (7,8), whereas balance path of the reference points U (1, 2) obtained in the tests diverge from those determined in calculations. The situation is similar in vertical displacements W (Z)- Figure 9c.…”

“…This, in turn, may cause errors in the process of validation of the numerical model. Therefore, an advanced evaluation of numerical model is more often supported with the data obtained by means of full-field optical measurement methods, which determine displacements and deformations in critical areas of the objects [7,8]. In the case of investigations of large engineering structures, the most commonly used techniques are terrestrial laser scanning [9][10][11] and the 3D digital image correlation (3D DIC) method [1,[12][13][14][15][16][17].…”

Application of 3D digital image correlation for development and validation of FEM model of self-supporting metal plates structures

“…This in turn may cause errors in the process of validation of the numerical model. Therefore, we can observe increasing use of the full field optical measurement methods for determination of displacements and deformations in critical areas of objects, for advanced evaluation of numerical models [5,6]. In the case of measurement of large engineering structures, the most commonly used technique is Digital Image Correlation (DIC) method [1,7].…”