Sm Kleinendorst

Novel image correlation based techniques for mechanical analysis of MEMS

Three techniques have been developed to analyze the mechanical behavior of micromechanical systems, in particular stretchable electronic interconnects. The techniques are all digital image correlation (DIC) based and vary in the type of images used for correlation and the way of regularizing the displacement field, needed because of the ill-posed nature of DIC problems. The first two techniques use Non-Uniform Rational B-Splines (NURBS) which are adaptively refined to autonomously obtain an optimized set of shape functions for the considered problem. The first method applies this to regular grayscale speckle images, while the second technique requires profilometric height images to calculate not only the in-plane deformation, but also the out-of-plane component of the displacement field. The third method is an integrated DIC approach and is coupled to a finite element (FE) model of the sample for regularization of the displacement field. It correlates projections of the sample contour rather than a speckle pattern, which makes the method suitable for large, complex and three-dimensional displacements and cases where speckle pattern application is difficult, such as microscale samples. Application of the techniques to i.a. stretchable electronic interconnects yields good results.

Mechanical shape correlation:a novel integrated digital image correlation approach

Mechanical Shape Correlation (MSC) is a novel integrated digital image correlation technique, used to determine the optimal set of constitutive parameters to describe the experimentally observed mechanical behavior of a test specimen, based on digital images taken during the experiment. In contrast to regular digital image correlation techniques, where grayscale speckle patterns are correlated, the images used in MSC are projections of the sample contour. This enables the analysis of experiments for which this was previously not possible, because of restrictions due to the speckle pattern. For example, analysis becomes impossible if parts of the specimen move or rotate out of view as a result of complex and three-dimensional deformations and if the speckle pattern degrades due to large deformations. When correlating on the sample outline, these problems are overcome. However, it is necessary that the outline is large with respect to the structure volume and that its shape changes significantly upon deformation, to ensure sufficient sensitivity of the images to the model parameters. Virtual experiments concerning stretchable electronic interconnects, which because of their slender wire-like structure satisfy the conditions for MSC, are executed and yield accurate results in the objective model parameters. This is a promising result for the use of the MSC method for tests with stretchable electronics and other (micromechanical) experiments in general.

On the Boundary Conditions and Optimization Methods in Integrated Digital Image Correlation

In integrated digital image correlation (IDIC) methods attention must be paid to the influence of using a correct geometric and material model, but also to make the boundary conditions in the FE simulation match the real experiment. Another issue is the robustness and convergence of the IDIC algorithm itself, especially in cases when (FEM) simulations are slow. These two issues have been explored in this proceeding. The basis of the algorithm is the minimization of the residual. Different approaches for this minimization exist, of which a Gauss-Newton method is used most often. In this paper several other methods are presented as well and their performance is compared in terms of number of FE simulations needed, since this is the most time-consuming step in the iterative procedure. Beside method-specific recommendations, the main finding of this work is that, in practical use of IDIC, it is recommended to start using a very robust, but slow, derivative-free optimization method (e.g. Nelder-Mead) to determine the search direction and increasing the initial guess accuracy, while after some iterations, it is recommended to switch to a faster gradient-based method, e.g. (update-limited) Gauss-Newton.

Self-adaptive isogeometric global digital image correlation and digital height correlation

This work explores the full potential of isogeometric shape functions for global digital image correlation. To this end, a novel DIC and DHC (digital height correlation) methodology have been developed based on adaptive refinement of isogeometric shape functions. Non-Uniform Rational B-Spline (NURBS) shape functions are used employed of their flexibility and versatility, which enables a wide range of kinematic descriptions. In the adaptive refinement algorithm, the shape functions are automatically adjusted to be able to describe the kinematics of the sought (2D or 3D) displacement field with an optimized number of degrees of freedom. Both methods show high accuracy as demonstrated by various virtual experiments with predefined, highly localized (2D and 3D) displacement field. For adaptive iso-GDIC, real tensile tests of complex sample geometries demonstrate its effectiveness in practice, showing local refinement at the areas of localization, without the need of making problem-specific choices regarding the structure of the shape functions. For adaptive iso-GDHC, the correlation of surface height profiles of deforming stretchable electronics structures shows successful autonomous refinement at two localized buckles, thereby strongly reducing the 3D residual, while also analytical differentiation of the C1-continuous 3D displacement field yields the curvature field of the deforming stretchable interconnect.