3D Lagrangian Particle Tracking in Fluid Mechanics

In the past few decades various particle image based volumetric flow measurement techniques have been developed which showed their potential in accessing unsteady flow properties quantitatively in various experimental applications in fluid mechanics. In this article we would like to focus on physical properties and circumstances of 3D particle-based measurements and what knowledge can be used for gaining advancements in the reconstruction accuracy, spatial and temporal resolution and completeness. The natural candidate for our focus is 3D Lagrangian Particle Tracking (LPT), which allows determining position, velocity and acceleration along a large number of individual particle tracks in the investigated volume. With the advent of the dense 3D LPT technique Shake-The-Box in the past decade further possibilities for characterizing unsteady flows have been opened by delivering input data for powerful data assimilation techniques which use Navier-Stokes constraints. As a result, high-resolution Lagrangian and Eulerian data can be gained including long particle trajectories embedded in time-resolved 3D velocity- and pressure fields

Baseline and triangulation geometry in a standard plenoptic camera

In this paper, we demonstrate light field triangulation to determine depth distances and baselines in a plenoptic camera. The advancement of micro lenses and image sensors enabled plenoptic cameras to capture a scene from different viewpoints with sufficient spatial resolution. While object distances can be inferred from disparities in a stereo viewpoint pair using triangulation, this concept remains ambiguous when applied in case of plenoptic cameras. We present a geometrical light field model allowing the triangulation to be applied to a plenoptic camera in order to predict object distances or to specify baselines as desired. It is shown that distance estimates from our novel method match those of real objects placed in front of the camera. Additional benchmark tests with an optical design software further validate the model’s accuracy with deviations of less than 0:33 % for several main lens types and focus settings. A variety of applications in the automotive and robotics field can benefit from this estimation model

Coalescence of Liquid Drops: Different Models Versus\ud Experiment

The process of coalescence of two identical liquid drops is simulated numerically in the framework of two essentially different mathematical models, and the results are compared with experimental data on the very early stages of the coalescence process reported recently. The first model tested is the ‘conventional’ one, where it is assumed that coalescence as the formation of a single body of fluid occurs by an instant appearance of a liquid bridge smoothly connecting the two drops, and the subsequent process is the evolution of this single body of fluid driven by capillary forces. The second model under investigation considers coalescence as a process where a section of the free surface becomes trapped between the bulk phases as the drops are pressed against each other, and it is the gradual disappearance of this ‘internal interface’ that leads to the formation of a single body of fluid and the conventional model taking over. Using the full numerical solution of the problem in the framework of each of the two models, we show that the recently reported electrical measurements probing the very early stages of the process are better described by the interface formation/disappearance model. New theory-guided experiments are suggested that would help to further elucidate the details of the coalescence phenomenon. As a by-product of our research, the range of validity of different ‘scaling laws’ advanced as approximate solutions to the problem formulated using the conventional model is\ud established

The Optical Alignment System of the ATLAS Muon Spectrometer Endcaps

The muon spectrometer of the ATLAS detector at the Large Hadron Collider (LHC) at CERN consists of over a thousand muon precision chambers, arranged in three concentrical cylinders in the barrel region, and in four wheels in each of the two endcaps. The endcap wheels are located between 7m and 22m from the interaction point, and have diameters between 13m and 24m. Muon chambers are equipped with a complex on-line optical alignment system to monitor their positions and deformations during ATLAS data-taking. We describe the layout of the endcap part of the alignment system and the design and calibration of the optical sensors, as well as the various software components. About 1% of the system has been subjected to performance tests in the H8 beam line at CERN, and results of these tests are discussed. The installation and commissioning of the full system in the ATLAS cavern is well underway, and results from approximately half of the system indicate that we will reach the ambitious goal of a 40mu alignment accuracy, required for reconstructing final-state muons at the highest expected energies

Quantitative 3d reconstruction from scanning electron microscope images based on affine camera models

Scanning electron microscopes (SEMs) are versatile imaging devices for the micro-and nanoscale that find application in various disciplines such as the characterization of biological, mineral or mechanical specimen. Even though the specimen’s two-dimensional (2D) properties are provided by the acquired images, detailed morphological characterizations require knowledge about the three-dimensional (3D) surface structure. To overcome this limitation, a reconstruction routine is presented that allows the quantitative depth reconstruction from SEM image sequences. Based on the SEM’s imaging properties that can be well described by an affine camera, the proposed algorithms rely on the use of affine epipolar geometry, self-calibration via factorization and triangulation from dense correspondences. To yield the highest robustness and accuracy, different sub-models of the affine camera are applied to the SEM images and the obtained results are directly compared to confocal laser scanning microscope (CLSM) measurements to identify the ideal parametrization and underlying algorithms. To solve the rectification problem for stereo-pair images of an affine camera so that dense matching algorithms can be applied, existing approaches are adapted and extended to further enhance the yielded results. The evaluations of this study allow to specify the applicability of the affine camera models to SEM images and what accuracies can be expected for reconstruction routines based on self-calibration and dense matching algorithms. © MDPI AG. All rights reserved

Postural injury risk assessment for industrial processes using advanced sensory systems

The major contributions of this research delivered both advancements and novel frameworks to enhance the current methods of postural assessments within industrial environments. This included the development of load vs repetition analysis, A novel BVH Model and a low cost ergonomic scoring tool relying on pixel labelling

Gait Analysis for Early Neurodegenerative Diseases Classification through the Kinematic Theory of Rapid Human Movements

Neurodegenerative diseases are particular diseases whose decline can partially or completely compromise the normal course of life of a human being. In order to increase the quality of patient's life, a timely diagnosis plays a major role. The analysis of neurodegenerative diseases, and their stage, is also carried out by means of gait analysis. Performing early stage neurodegenerative disease assessment is still an open problem. In this paper, the focus is on modeling the human gait movement pattern by using the kinematic theory of rapid human movements and its sigma-lognormal model. The hypothesis is that the kinematic theory of rapid human movements, originally developed to describe handwriting patterns, and used in conjunction with other spatio-temporal features, can discriminate neurodegenerative diseases patterns, especially in early stages, while analyzing human gait with 2D cameras. The thesis empirically demonstrates its effectiveness in describing neurodegenerative patterns, when used in conjunction with state-of-the-art pose estimation and feature extraction techniques. The solution developed achieved 99.1% of accuracy using velocity-based, angle-based and sigma-lognormal features and left walk orientation