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

Dense and accurate motion and strain estimation in high resolution speckle images using an image-adaptive approach

Digital image processing methods represent a viable and well acknowledged alternative to strain gauges and interferometric techniques for determining full-field displacements and strains in materials under stress. This paper presents an image adaptive technique for dense motion and strain estimation using high-resolution speckle images that show the analyzed material in its original and deformed states. The algorithm starts by dividing the speckle image showing the original state into irregular cells taking into consideration both spatial and gradient image information present. Subsequently the Newton-Raphson digital image correlation technique is applied to calculate the corresponding motion for each cell. Adaptive spatial regularization in the form of the Geman-McClure robust spatial estimator is employed to increase the spatial consistency of the motion components of a cell with respect to the components of neighbouring cells. To obtain the final strain information, local least-squares fitting using a linear displacement model is performed on the horizontal and vertical displacement fields. To evaluate the presented image partitioning and strain estimation techniques two numerical and two real experiments are employed. The numerical experiments simulate the deformation of a specimen with constant strain across the surface as well as small rigid-body rotations present while real experiments consist specimens that undergo uniaxial stress. The results indicate very good accuracy of the recovered strains as well as better rotation insensitivity compared to classical techniques

A three-frame digital image correlation (DIC) method for the measurement of small displacements and strains

Digital image correlation (DIC) has become a well established approach for the calculation of full-field displacement and strains within the field of experimental mechanics. Since their introduction, DIC methods have been relying on only two images to measure the displacements and strains that materials undergo under load. It can be foreseen that the use of additional image information for the calculus of displacements and strains, although computationally more expensive, can positively impact DIC method accuracy in both ideal and challenging experimental conditions. Such accuracy improvements are especially important when measuring very small deformations, which still constitutes a great challenge: small displacements and strains translate into equally small digital image intensity changes on the material’s surface, which are affected by the digitization processes of the imaging hardware and by other image acquisition effects such as image noise. This paper proposes a new threeframe Newton-Raphson DIC method and evaluates it from the accuracy and speed standpoints. The method models the deformations that are to be measured under the assumption that the deformation occurs at approximately the same rate between each two consecutive images in the three image sequences that are employed. The aim is to investigate how the use of image data from more than two images impacts accuracy and what is the effect on the computational speed. The proposed method is compared with the classic two-frame Newton-Raphson method in three experiments. Two experiments rely on numerically deformed images that simulate heterogeneous deformations. The third experiment uses images from a real deformation experiment. Results indicate that although it is computationally more demanding, the three-frame method significantly improves displacement and strain accuracy and is less sensitive to image noise

Experimentally induced errors in digital image correlation measurement of small strains with large gradients

Digital Image Correlation or DIC is an already widespread and commonly used technique to perform full field strain measurements. Usually, a so called 'speckle pattern' is put on the specimen and then, pictures are taken first in the undeformed stage, which is the reference and then in various deformed states. The technique itself consists of comparing the image of a deformed pattern with a reference image and determining the displacements of the so called 'subsets'. The mathematical algorithm eliminates rigid rotations of the subset and is able to determine the strain field. This technique was originally designed for large-strain measurements and as such, it works very well when large strains are present, but when determining (very) small strain fields, especially in combination with large (rigid body) deformations or large strain gradients, this technique becomes a lot more sensitive to the boundary conditions of the experimental setup. This manuscript will illustrate the errors induced by experimental factors such as in-plane rotation, in-plane rigid body translation, out-of-plane rigid body rotation, which are in fact all related to how the specimen is gripped in the tensile machine, on the eventual derived strain field. Furthermore, processing parameters such as subset and step size and the used strain window on numerically and experimentally induced transformations will be assessed

Research on combustion process of gasoline homogenous charge compression ignition engine

The paper presents the research designed to develop a HCCI (Homogenous Charge Compression Ignition) engine starting from a spark ignition engine platform. The chosen test engine was a single cylinder, four strokes provided with a carburettor. The results of experimental research data obtained on this version were used as a baseline for the next phase of the research. In order to obtain the HCCI configuration, the engine was modified, as follows: the compression ratio was increased from 9.7 to 11.5 to ensure that the air – fuel mixture auto-ignite and to improve the engine efficiency; the carburettor was replaced by a direct fuel injection system in order to control precisely the fuel mass per cycle taking into account the measured intake air-mass; the valves shape were modified to provide a safety engine operation by ensuring the provision of sufficient clearance beetween the valve and the piston; the exchange gas system was changed from fixed timing to variable valve timing to have the possibilities of modification of quantities of trapped burnt gases. The cylinder processes were simulated on virtual model. The experimental research works were focused on determining the parameters which control the combustion timing of HCCI engine to obtain the best energetic and ecologic parameters