C. O’Sullivan

Cerebral immune activation in chronic hepatitis C infection: A magnetic resonance spectroscopy study☆

BACKGROUND/AIMS Abnormal cerebral metabolism and cognitive impairments have been reported in patients with chronic hepatitis C (HCV) but studies have failed to demonstrate a relationship between these findings. METHODS Twenty-five HCV-positive patients with histologically-mild liver disease were studied with cerebral proton magnetic resonance spectroscopy (MRS), using acquisition parameters to quantify myo-inositol (mI) and other metabolites in frontal white matter (FWM). Patients underwent automated attention and working memory tests (Cognitive Drug Research test system). RESULTS The mean mI/ creatine ratio in the HCV+ve patients (0.64, SD 0.21) was significantly higher (p=0.02) than in healthy controls (0.52, SD 0.10). On cognitive testing, the HCV+ve patients showed impairments in 2/4 composite scores, reflecting working memory and attention, compared to normative data from healthy volunteers (p<0.005) and HCV-ve controls (p=0.03). There was a significant association between elevated FWM mI/creatine and prolonged working memory reaction times (R=0.72, p=0.002). CONCLUSIONS Elevated FWM mI/ creatine is a feature of HIV-related minor cognitive-motor disorder. It is associated with infection and immune activation of microglial cells. The similar findings in this study suggest that cerebral immune activation may also occur in HCV infection. This may underlie the mild neurocognitive impairment and neuropsychological symptoms observed in a proportion of patients.

Sand production simulation coupling DEM with CFD

Sand production in oil wells is often predicted using continuum fluid-coupled models. However, a continuum approach cannot capture important features of the sanding problem, such as erosion and localised failure. This shortcoming of continuum-based analyses can be overcome using the particulate discrete element method (DEM). However, these models, apart from issues of computational cost, have the disadvantage of being difficult to calibrate. One way forward is to calibrate DEM models to capture the response observed in continuum models, where the material parameters can be selected with greater confidence. Adopting this philosophy here, a 3D numerical model based on DEM coupled with Computational Fluid Dynamics was built to simulate sand production around perforations. In the first instance, the basic DEM model (i.e. a dry case) is calibrated against a well-known poro-elastoplastic analytical solution by Risnes et al. (1982). Subsequently, a range of hydrostatic scenarios involving different levels of pore pressure and effective stress are considered. The numerical model shows an asymmetry of the eroded zone that is related to initial microscale inhomogeneity. The stress peak of the analytical solution at the elastic-plastic interface is smoothed because of that asymmetry. The presence of hydrostatic fluid decreases the plastic region and reduces the amount of sand produced. This is not due to changes in effective stress but rather by the particle-scale stabilizing effect of the fluid drag.

Image Segmentation Techniques for Granular Materials

To improve understanding of the mechanical behavior of granular materials it is important to be able to quantify the relative arrangement of the grains, i.e. the fabric. This can be done, for example, by measuring the orientations of the particles (e.g. the long axis orientation) or by considering the orientations of the vectors normal to each grain‐grain contact. In two dimensional (2D) analyses this information can be obtained by digital image analysis of images of thin sections obtained from an optical microscope. While such data is useful, granular materials of engineering interest are three dimensional (3D) materials and quantification of the 3D fabric is necessary. Micro Computed‐Tomography (μCT) together with 3D image analysis has emerged as a promising technique for obtaining the 3D data required. This paper aims to highlight the challenges associated with using image analysis to provide quantitative information on fabric. While automated image segmentation has proved to produce reasonable results in some cases, it is sometimes less successful when dealing with highly irregular and angular soil grains. This paper evaluates the effectiveness of 2D and 3D segmentation techniques that rely on the watershed segmentation algorithm. The primary material considered is Reigate Silver Sand, a natural quartzitic sand with grain diameters in the range of 150–300 μm. While the sand considered is primarily of interest to geotechnical engineers, the results of this study will be of interest to anyone seeking to quantify granular material fabric using either 2D microscopy data or μCT 3D data sets.

Geometric and Hydraulic Void Constrictions in Granular Media

AbstractConstrictions in the void space between soil particles govern hydraulic conductivity, internal stability, and filtration performance of sands and gravels. Various analytical, numerical, and image-based methods have been proposed to measure void constrictions based solely on analysis of particle and void geometry. These geometric constrictions are increasingly being used in models to predict hydraulic conductivity or filtration performance. However, both of these phenomena depend not only on the void geometry, but also on the directions and magnitudes of fluid velocities within the void space. This paper presents computational fluid dynamics (CFD) simulations performed on microcomputed tomography (microCT) images of voids in real sands, as well as idealized materials generated by discrete element modeling (DEM). Laminar flow conditions are considered and an alternative definition of a void constriction is presented, the hydraulic constriction, which is based on fluid velocities rather than void geo...

Closure to “Fabric and Effective Stress Distribution in Internally Unstable Soils” by T. Shire, C. O’Sullivan, K. J. Hanley, and R. J. Fannin

The authors have performed numerical tests to determine the distribution of fabric and effective stresses in internally unstable soils. Different grain size distribution curves as well as different densities were investigated. The authors have used the methods of Kezdi (1979) and Kenney and Lau (1985, 1986) to assess the internal stability. The relative density has a significant effect on the internal stability (Ahlinhan et al. 2012; ICOLD 2013). Accordingly, it is important to use a method takes into consideration the effect of density to assess the internal stability. Neither Kezdi’s method nor Kenney and Lau’s method takes the density in consideration. A suitable method is the one suggested by Dallo et al. (2013), which takes the effect of soil density in consideration. For instance, the soil (Gap med 18) is classified as border-line according to Kezdi’s method, whereas it is classified as unstable according to Kenney and Lau’s method, regardless of its relative density. According to Dallo et al. (2013), soil (Gap med 18) is unstable, transition (or border-line), and stable for the loose, medium, and dense relative densities, respectively. Also the internal stability prediction accuracy of Dallo et al. (2013)’s method is better than those of the Kezdi or Kenney and Lau methods (Dallo et al. 2013). The discusser used the method of Dallo et al. (2013) to assess the internal stability of the gap-graded soils tested by the authors (Table 1). It can be seen that the soils (Gap wide XX) are unstable, the soils (Gap narrow XX) are stable, whereas the internal stability of the soils (Gap med XX) depends on the relative density of the soil. Another discussion point is related to the authors’ adoption of the findings of Skempton and Brogan (1994) that the critical finer fraction (S ) falls between narrow limits of finer fractions by mass, Ffine 1⁄4 24–29% for dense and loose samples respectively. Also, the finer fraction (Smax) at which the finer particles completely separate the coarse particles from one another is given as Ffine 1⁄4 35%. The discusser believes that the critical finer fraction can be computed more accurately according to Indraratna et al. (2011), Eq. (1), or Dallo and Wang (2012), Eq. (2), as Smax 1⁄4 1 − nl 1 − nc nc ð1Þ

Discrete Simulation of Cone Penetration in Granular Materials

The simulation of penetration problems into granular materials is a challenging problem as it involves large deformations and displacements as well as strong non-linearities affecting material behaviour, geometry and contact surfaces. In this contribution, the Discrete Element Method (DEM) has been adopted as the modelling formulation. Attention is focused on the simulation of cone penetration, a basic reconnaissance tool in geotechnical engineering, although the approach can be readily extended to other penetration problems. It is shown that DEM analysis results in a very close quantitative representation of the cone resistance obtained in calibration chambers under a wide range of conditions. DEM analyses also provides, using appropriate averaging techniques, relevant information concerning mesoscale continuum variables (stresses and strains) that appear to be in agreement with physical calibration chamber observations. The examination of microstructural variables contributes to a better understanding of the mechanisms underlying the observed effects of a number of experimental and analysis features of the cone penetration test.

Exploring the Undrained Cyclic Behaviour of Sand Using DEM

This paper investigates the influences of confining pressure and cyclic deviatoric stress on the undrained cyclic loading behavior of saturated granular materials using DEM. Cyclic mobility, which is typical for sand under cyclic loading conditions in the absence of initial deviatoric stress, is captured. DEM simulation results show that the number of loading cycles to initial liquefaction increases with increasing confining pressure but decreases as cyclic deviatoric stress increases. Cyclic mobility is characterized by alternating abrupt drops and gains of coordination number accompanied by alternating abrupt decreases and increases of deviatoric fabric. The runaway deformation can be either compressive or extensive depending on whether the instability state under monotonic compression loading conditions or that under monotonic extension loading conditions is reached first during cyclic shearing.

Static Liquefaction and Instability in Granular Media Subjected to Monotonic Loading—A Micromechanical Investigation

Static liquefaction has caused a number of failures involving dam tailings, hydraulically placed fills and slopes. In order to understand the failure mechanisms that induce static liquefaction, the discrete element method (DEM) was used to study the behavior of a representative model of a granular sample at the micro level. Samples with different void ratios at same confining pressures were sheared under constant-volume conditions and the changes in the macro and micromechanical responses of the granular media were quantified. Characteristic states such as the instability state, quasi-steady state, phase transformation and critical state were identified in the simulations. The transitions between different characteristic states were related to micromechanical characteristics such as coordination number. Finally, the orientation of the weak contacts was seen to be dependent on the characteristic state, while the orientation of the strong contacts coincided with the major principal stress direction.