Dynamic image analysis for three-dimensional particle shape characterisation

Particulate matter is ubiquitous in numerous industries, from energy storage to medicine, with many industrial processes being increasingly dependent on understanding particulate matter on a finer scale. As real particles have such a large variation in morphology, it is crucial to characterise them at scale, accurately, and in real-time. Current industrial standards are limited to 2D analysis of dynamic particulates or 3D analysis of static particulates, using technologies such as digital microscopy or X-ray CT scanner, respectively. The combination of several 2D images projected from different perspectives allows for 3D reconstruction and 3D characterisation of particle morphology. A real-time shape analysis is performed to classify particles with a higher degree of accuracy. Via use of these projections, several camera orientations have been set up in order to find the orientation of perspectives that provides the highest degree of accuracy with the lowest cost in creating 3D avatars of particles. In order to show the benefits of 3D analysis over 2D analysis, irregular particles of dolomite, silica sand, and waste glass beads are tested and compared with X-ray CT images. This study allows for a broad range of different morphological indices to be investigated and for the level of characterisation error to be quantified

How Do Roots Interact with Layered Soils?

Vegetation alters soil fabric by providing biological reinforcement and enhancing the overall mechanical behaviour of slopes, thereby controlling shallow mass movement. To predict the behaviour of vegetated slopes, parameters representing the root system structure, such as root distribution, length, orientation and diameter, should be considered in slope stability models. This study quantifies the relationship between soil physical characteristics and root growth, giving special emphasis on (1) how roots influence the physical architecture of the surrounding soil structure and (2) how soil structure influences the root growth. A systematic experimental study is carried out using high-resolution X-ray micro-computed tomography (\ub5CT) to observe the root behaviour in layered soil. In total, 2 samples are scanned over 15 days, enabling the acquisition of 10 sets of images. A machine learning algorithm for image segmentation is trained to act at 3 different training percentages, resulting in the processing of 30 sets of images, with the outcomes prompting a discussion on the size of the training data set. An automated in-house image processing algorithm is employed to quantify the void ratio and root volume ratio. This script enables post processing and image analysis of all 30 cases within few hours. This work investigates the effect of stratigraphy on root growth, along with the effect of image-segmentation parameters on soil constitutive properties

Exploring the micro-to-macro response of granular soils with real particle shapes via \u1d741\u1d46a\u1d47b-aided DEM analyses

This contribution provides high fidelity images of real granular materials with the aid of X-ray micro computed tomography (μCT ), and employs a multi-sphere approximation to reconstruct non-spherical particles. Through the discrete element method (DEM) simulations on granular samples composed of these non-spherical clumps, the effect of particle shape on the macroscopic mechanical response and microscopic soil fabric evolution is examined for sheared soil assemblies under triaxial loading conditions. Simulation results indicate that materials with more irregular particles tend to show higher shear resistance in both peak and critical stresses, while more sphere-like materials tend to exhibit lower void ratio and mean coordination number values under isotropic loading conditions and in the critical state. The proposed critical state parameters for describing the sensitivity of the mean coordination number to confining pressures are larger as particles become more irregular. At a microscopic level of observation, more irregular materials appear to exhibit higher fabric anisotropy in terms of contact normal and particle orientation in the critical state. The critical stress ratio determined through experimental and simulation results are found to be linearly linked to the shape-weighted fabric anisotropy index

Rigid clumps in the <em>MercuryDPM</em> particle dynamics code

Discrete particle simulations have become the standard in science and industrial applications exploring the properties of particulate systems. Most of such simulations rely on the concept of interacting spherical particles to describe the properties of particulates, although, the correct representation of the nonspherical particle shape is crucial for a number of applications. In this work we describe the implementation of clumps, i.e. assemblies of rigidly connected spherical particles, which can approximate given nonspherical shapes, within the MercuryDPM particle dynamics code. MercuryDPM contact detection algorithm is particularly efficient for polydisperse particle systems, which is essential for multilevel clumps approximating complex surfaces. We employ the existing open-source CLUMP library to generate clump particles. We detail the pre-processing tools providing necessary initial data, as well as the necessary adjustments of the algorithms of contact detection, collision/migration and numerical time integration. The capabilities of our implementation are illustrated for a variety of examples

Computation of an MRI brain atlas from a population of Parkinson’s disease patients

Abstract Parkinson’s Disease (PD) is a degenerative disorder of the brain. This study presents an MRI-based brain atlas of PD to characterize associated alterations for diagnostic and interventional purposes. The atlas standardizes primarily the implicated subcortical regions such as the globus pallidus (GP), substantia nigra (SN), subthalamic nucleus (STN), caudate nucleus (CN), thalamus (TH), putamen (PUT), and red nucleus (RN). The data were 3.0 T MRI brain images from 16 PD patients and 10 matched controls. The images used were T1-weighted ( T 1 w ), T2-weighted ( T 2 w ) images, and Susceptibility Weighted Images (SWI). The T1w images were the reference for the inter-subject non-rigid registration available from 3DSlicer. Anatomic labeling was achieved with BrainSuite and regions were refined with the level sets segmentation of ITK-Snap. The subcortical centers were analyzed for their volume and signal intensity. Comparison with an age-matched control group unravels a significant PD-related T1w signal loss in the striatum (CN and PUT) centers, but approximately a constant volume. The results in this study improve MRI based PD localization and can lead to the development of novel biomarkers

Z boson production in Pb+Pb collisions at √Snn = 5.02 TeV measured by the ATLAS experiment

The production yield of Z bosons is measured in the electron and muon decay channels in Pb+Pb collisions at √S = 5.02 TeV with the ATLAS detector. Data from the 2015 LHC run corresponding to an integrated luminosity of 0.49 nb are used for the analysis. The Z boson yield, normalised by the total number of minimum-bias events and the mean nuclear thickness function, is measured as a function of dilepton rapidity and event centrality. The measurements in Pb+Pb collisions are compared with similar measurements made in proton-proton collisions at the same centre-of-mass energy. The nuclear modification factor is found to be consistent with unity for all centrality intervals. The results are compared with theoretical predictions obtained at next-to-leading order using nucleon and nuclear parton distribution functions. The normalised Z boson yields in Pb+Pb collisions lie 1-3σ above the predictions. The nuclear modification factor measured as a function of rapidity agrees with unity and is consistent with a next-to-leading-order QCD calculation including the isospin effect. nn -

Search for flavour-changing neutral currents in processes with one top quark and a photon using 81 fb−1 of pp collisions at s=13TeV with the ATLAS experiment

A search for flavour-changing neutral current (FCNC) events via the coupling of a top quark, a photon, and an up or charm quark is presented using 81 fb−1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Events with a photon, an electron or muon, a b-tagged jet, and missing transverse momentum are selected. A neural network based on kinematic variables differentiates between events from signal and background processes. The data are consistent with the background-only hypothesis, and limits are set on the strength of the tqγ coupling in an effective field theory. These are also interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tuγ coupling of 36 fb (78 fb) and on the branching ratio for t→γu of 2.8×10−5 (6.1×10−5). In addition, they are interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tcγ coupling of 40 fb (33 fb) and on the branching ratio for t→γc of 22×10−5 (18×10−5)

Measurement of Azimuthal Anisotropy of Muons from Charm and Bottom Hadrons in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector.

The elliptic flow of muons from the decay of charm and bottom hadrons is measured in pp collisions at sqrt[s]=13  TeV using a data sample with an integrated luminosity of 150  pb^{-1} recorded by the ATLAS detector at the LHC. The muons from heavy-flavor decay are separated from light-hadron decay muons using momentum imbalance between the tracking and muon spectrometers. The heavy-flavor decay muons are further separated into those from charm decay and those from bottom decay using the distance-of-closest-approach to the collision vertex. The measurement is performed for muons in the transverse momentum range 4-7&nbsp;GeV and pseudorapidity range |η|&lt;2.4. A significant nonzero elliptic anisotropy coefficient v_{2} is observed for muons from charm decays, while the v_{2} value for muons from bottom decays is consistent with zero within uncertainties