The Mechanical Coupling of Fluid-Filled Granular Material Under Shear

The coupled mechanics of fluid-filled granular media controls the physics of many Earth systems, for example saturated soils, fault gouge, and landslide shear zones. It is well established that when the pore fluid pressure rises, the shear resistance of fluid-filled granular systems decreases, and, as a result, catastrophic events such as soil liquefaction, earthquakes, and accelerating landslides may be triggered. Alternatively, when the pore pressure drops, the shear resistance of these geosystems increases. Despite the great importance of the coupled mechanics of grain–fluid systems, the basic physics that controls this coupling is far from understood. Fundamental questions that must be addressed include: what are the processes that control pore fluid pressurization and depressurization in response to deformation of the granular skeleton? and how do variations of pore pressure affect the mechanical strength of the grains skeleton? To answer these questions, a formulation for the pore fluid pressure and flow has been developed from mass and momentum conservation, and is coupled with a granular dynamics algorithm that solves the grain dynamics, to form a fully coupled model. The pore fluid formulation reveals that the evolution of pore pressure obeys viscoelastic rheology in response to pore space variations. Under undrained conditions elastic-like behavior dominates and leads to a linear relationship between pore pressure and overall volumetric strain. Viscous-like behavior dominates under well-drained conditions and leads to a linear relationship between pore pressure and volumetric strain rate. Numerical simulations reveal the possibility of liquefaction under drained and initially over-compacted conditions, which were often believed to be resistant to liquefaction. Under such conditions liquefaction occurs during short compactive phases that punctuate the overall dilative trend. In addition, the previously recognized generation of elevated pore pressure under undrained compactive conditions is observed. Simulations also show that during liquefaction events stress chains are detached, the external load becomes completely supported by the pressurized pore fluid, and shear resistance vanishes.     

Bayesian data fusion in a spatial prediction context: a general formulation

In spite of the exponential growth in the amount of data that one may expect to provide greater modeling and predictions opportunities, the number and diversity of sources over which this information is fragmented is growing at an even faster rate. As a consequence, there is real need for methods that aim at reconciling them inside an epistemically sound theoretical framework. In a statistical spatial prediction framework, classical methods are based on a multivariate approach of the problem, at the price of strong modeling hypotheses. Though new avenues have been recently opened by focusing on the integration of uncertain data sources, to the best of our knowledges there have been no systematic attemps to explicitly account for information redundancy through a data fusion procedure. Starting from the simple concept of measurement errors, this paper proposes an approach for integrating multiple information processing as a part of the prediction process itself through a Bayesian approach. A general formulation is first proposed for deriving the prediction distribution of a continuous variable of interest at unsampled locations using on more or less uncertain (soft) information at neighboring locations. The case of multiple information is then considered, with a Bayesian solution to the problem of fusing multiple information that are provided as separate conditional probability distributions. Well-known methods and results are derived as limit cases. The convenient hypothesis of conditional independence is discussed by the light of information theory and maximum entropy principle, and a methodology is suggested for the optimal selection of the most informative subset of information, if needed. Based on a synthetic case study, an application of the methodology is presented and discussed.     

Dynamical attitude model for Gaia

The Dynamical Attitude Model (DAM) is a simulation package developed to achieve a detailed understanding of the Gaia spacecraft attitude. It takes into account external physical effects and considers internal hardware components controlling the satellite. The main goal of the Gaia mission is to obtain extremely accurate astrometry, and this necessitates a good knowledge of Gaia’s behaviour as a spinning rigid body under the influence of various perturbations. This paper describes these perturbations and how they are modelled in DAM.     

Linear mechanism of generation and intencification of internal gravity waves in the ionosphere at their interaction with a nonuniform zonal wind: 1. Model of the medium and initial dynamic equations

The specific features of the generation and intensification of internal gravity wave structures in different atmospheric-ionospheric regions, caused by zonal local nonuniform winds (shear flows), are studied. The model of the medium has been explained and an initial closed system of equations has been obtained in order to study the linear and nonlinear dynamics of internal gravity waves (IGWs) when they interact with the geomagnetic field in a dissipative ionosphere (for the D, E, and F regions).     

Correlation of trace elements with hydrocarbon microseepage

Direct correlation have been observed between certain trace element and hydrocarbon anomalies in the near subsurface soils of Vindhyan basin, India. This relationship with hydrocarbon is very useful in hydrocarbon exploration. 52 soil samples from Vindhyan basin were collected from a depth of 2.5m. All the soil samples were analyzed for light hydrocarbon, isotope and trace element concentrations. The adsorbed light gaseous hydrocarbon analyses show the presence of methane (8–328 ppb), ethane (0–27 ppb) and propane (0–11 ppb) respectively and these values indicate the presence of hydrocarbon micro-seepage in the study area. The carbon isotopic values determined for methane and ethane for these soil samples are (?26.41 to ?47.70 ‰ PDB) and (?20.07 to ?35.30 ‰ PDB) respectively and they are thermogenic in nature. The trace element concentrations of nickel (33–220 ppm), vanadium (72–226 ppm), copper (20–131 ppm), chromium (94–205 ppm), zinc (66–561 ppm) and cobalt (9–39 ppm) have higher than the normal concentrations in soils. Trace element concentrations are used to plot with the data obtained from light gaseous hydrocarbon concentrations and carbon isotopic values of soil samples of the Vindhyan basin. Trace element anomalies have been observed around the hydrocarbon anomalies in the study area.