Submicron Deformation Field Measurements II: Improved Digital Image Correlation

This is the second paper in a series of three devoted to the applicaiton of Scanning Tunneling Microscopy to mechanics problems. In this paper improvements to the Digital Image Correlation method are outlined, a technique that compares digital images of a specimen surface before and after deformation to deduce its (2-D) surface displacement field and strains. The necessity of using the framework of large deformation theory for accurately addressing rigid body rotations to reduce associated errors in the strain components is pointed out. In addition, the algorithm is extended to compute the three-dimensional surface displacement field from Scanning Tunneling Microscope data; also, significant improvements are achieved in the rate as well as the robustness of the convergence. For Scanning Tunneling Microscopy topographs the resolution yields 4.8 nm for the in-plane and 1.5 nm for the out-of-plane displacement components spanning an area of 10 μm x 10 μm

An inexact Newton-Krylov algorithm for constrained diffeomorphic image registration

We propose numerical algorithms for solving large deformation diffeomorphic image registration problems. We formulate the nonrigid image registration problem as a problem of optimal control. This leads to an infinite-dimensional partial differential equation (PDE) constrained optimization problem. The PDE constraint consists, in its simplest form, of a hyperbolic transport equation for the evolution of the image intensity. The control variable is the velocity field. Tikhonov regularization on the control ensures well-posedness. We consider standard smoothness regularization based on $H^1$- or $H^2$-seminorms. We augment this regularization scheme with a constraint on the divergence of the velocity field rendering the deformation incompressible and thus ensuring that the determinant of the deformation gradient is equal to one, up to the numerical error. We use a Fourier pseudospectral discretization in space and a Chebyshev pseudospectral discretization in time. We use a preconditioned, globalized, matrix-free, inexact Newton-Krylov method for numerical optimization. A parameter continuation is designed to estimate an optimal regularization parameter. Regularity is ensured by controlling the geometric properties of the deformation field. Overall, we arrive at a black-box solver. We study spectral properties of the Hessian, grid convergence, numerical accuracy, computational efficiency, and deformation regularity of our scheme. We compare the designed Newton-Krylov methods with a globalized preconditioned gradient descent. We study the influence of a varying number of unknowns in time. The reported results demonstrate excellent numerical accuracy, guaranteed local deformation regularity, and computational efficiency with an optional control on local mass conservation. The Newton-Krylov methods clearly outperform the Picard method if high accuracy of the inversion is required.Comment: 32 pages; 10 figures; 9 table

A priori error for unilateral contact problems with Lagrange multiplier and IsoGeometric Analysis

In this paper, we consider unilateral contact problem without friction between a rigid body and deformable one in the framework of isogeometric analysis. We present the theoretical analysis of the mixed problem using an active-set strategy and for a primal space of NURBS of degree $p$ and $p-2$ for a dual space of B-Spline. A inf-sup stability is proved to ensure a good property of the method. An optimal a priori error estimate is demonstrated without assumption on the unknown contact set. Several numerical examples in two- and three-dimensional and in small and large deformation demonstrate the accuracy of the proposed method

Deformation Measurements at the Sub-Micron Size Scale: II. Refinements in the Algorithm for Digital Image Correction

Improvements are proposed in the application of the Digital Image Correlation method, a technique that compares digital images of a specimen surface before and after deformation to deduce its sureface (2-D) displacement field and strains. These refinements, tested on translations and rigid body rotations were significant with regard to the computer efficiency and covergence properties of the method. In addition, the formulation of the algorithm was extended so as to compute the three-dimensional surface displacement field from Scanning Tunneling Microscope tomographies of a deforming specimen. The reolsution of this new displacement measuring method at the namometer scale was assessed on translation and uniaxial tensile tests and was found to be 4.8 nm for in-plane displacement components and 1.5 nm for the out-of-plane one spanning a 10 x 10 μm area

Regularized Newton-Raphson method for small strain calculation

Digital Image Correlation (DIC) has been proven to be a highly reliable framework for the full-field displacement and strain measurement of materials that undergo deformation when subjected to physical stresses. This paper presents a new method that extends the popular Newton-Raphson algorithm through the inclusion of spatial regularization in the minimization process used to obtain the motion data. The basic principle is that the motion data is calculated between corresponding blocks in the reference and deformed images using adaptively previously obtained motion estimates in the immediate vicinity of the respective location along with the local block-based image information. The results indicate significant accuracy improvements over the classic approach especially when the block sizes and strain calculation windows used for motion and strain estimation decrease in size

Inverse modelling of image-based patient-specific blood vessels : zero-pressure geometry and in vivo stress incorporation

In vivo visualization of cardiovascular structures is possible using medical images. However, one has to realize that the resulting 3D geometries correspond to in vivo conditions. This entails an internal stress state to be present in the in vivo measured geometry of e.g. a blood vessel due to the presence of the blood pressure. In order to correct for this in vivo stress, this paper presents an inverse method to restore the original zero-pressure geometry of a structure, and to recover the in vivo stress field of the final, loaded structure. The proposed backward displacement method is able to solve the inverse problem iteratively using fixed point iterations, but can be significantly accelerated by a quasi-Newton technique in which a least-squares model is used to approximate the inverse of the Jacobian. The here proposed backward displacement method allows for a straightforward implementation of the algorithm in combination with existing structural solvers, even if the structural solver is a black box, as only an update of the coordinates of the mesh needs to be performed

Computing stationary free-surface shapes in microfluidics

A finite-element algorithm for computing free-surface flows driven by arbitrary body forces is presented. The algorithm is primarily designed for the microfluidic parameter range where (i) the Reynolds number is small and (ii) force-driven pressure and flow fields compete with the surface tension for the shape of a stationary free surface. The free surface shape is represented by the boundaries of finite elements that move according to the stress applied by the adjacent fluid. Additionally, the surface tends to minimize its free energy and by that adapts its curvature to balance the normal stress at the surface. The numerical approach consists of the iteration of two alternating steps: The solution of a fluidic problem in a prescribed domain with slip boundary conditions at the free surface and a consecutive update of the domain driven by the previously determined pressure and velocity fields. ...Comment: Revised versio