An orthotropic interface damage model for simulating drying processes in soils

The study of drying process in soils has received an increased attention in the last few years. This is very complex phenomenon that generally leads to the formation and propagation of desiccation cracks in the soil mass. In recent engineering applications, high aspect ratio elements have proved to be well suited to tackle this type of problem using finite elements. However, the modeling of interfaces between materials with orthotropic properties that generally exist in this type of problem using standard (isotropic) constitutive model is very complex and challenging in terms of the mesh generation, leading to very fine meshes that are intensive CPU demanding. A novel orthotropic interface mechanical model based on damage mechanics and capable of dealing with interfaces between materials in which the strength depends on the direction of analysis is proposed in this paper. The complete mathematical formulation is presented together with the algorithm suggested for its numerical implementation. Some simple yet challenging synthetic benchmarks are analyzed to explore the model capabilities. Laboratory tests using different textures at the contact surface between materials were conducted to evaluate the strengths of the interface in different directions. These experiments were then used to validate the proposed model. Finally, the approach is applied to simulate an actual desiccation test involving an orthotropic contact surface. In all the application cases the performance of the model was very satisfactory.     

Accessing effects and signals of leakage from a CO<Subscript>2</Subscript> reservoir to a shallow freshwater aquifer by reactive transport modelling

CO₂ geological storage is a transitional technology for the mitigation of climate change. In the vicinity of potential CO₂ reservoirs in Hungary, protected freshwater aquifers used for drinking water supplies exist. Effects of disaster events of CO₂ escape and brine displacement to one of these aquifers have been studied by kinetic 1D reactive transport modelling in PHREEQC. Besides verifying that ion concentrations in the freshwater may increase up to drinking water limit values in both scenarios (CO₂ or brine leakage), total porosity of the rock is estimated. Pore volume is expected to increase at the entry point of CO₂ and to decrease at further distances, whereas it shows minor increase along the flow path for the effect of brine inflow. Additionally, electrical conductivity of water is estimated and suggested to be the best parameter to measure for cost-effective monitoring of both worst-case leakage scenarios.     

Exploratory Factor Analysis of Wireline Logs Using a Float-Encoded Genetic Algorithm

In the paper, a novel inversion approach is used for the solution of the problem of factor analysis. The float-encoded genetic algorithm as a global optimization method is implemented to extract factor variables using open-hole logging data. The suggested statistical workflow is used to give a reliable estimate for not only the factors but also the related petrophysical properties in hydrocarbon formations. In the first step, the factor loadings and scores are estimated by Jöreskog’s fast approximate method, which are gradually improved by the genetic algorithm. The forward problem is solved to calculate wireline logs directly from the factor scores. In each generation, the observed and calculated well logs are compared to update the factor population. During the genetic algorithm run, the average fitness of factor populations is maximized to give the best fit between the observed and theoretical data. By using the empirical relation between the first factor and formation shaliness, the shale volume is estimated along the borehole. Permeability as a derived quantity also correlates with the first factor, which allows its determination from an independent source. The estimation results agree well with those of independent deterministic modeling and core measurements. Case studies from Hungary and the USA demonstrate the feasibility of the global optimization based factor analysis, which provides a useful tool for improved reservoir characterization.     

Composition of barian mica in multiphase solid inclusions from orogenic garnet peridotites as evidence of mantle metasomatism in a subduction zone setting

Multiphase solid inclusions in minerals formed at ultra-high-pressure (UHP) provide evidence for the presence of fluids during deep subduction. This study focuses on barian mica, which is a common phase in multiphase solid inclusions enclosed in garnet from mantle-derived UHP garnet peridotites in the Saxothuringian basement of the northern Bohemian Massif. The documented compositional variability and substitution trends provide constraints on crystallization medium of the barian mica and allow making inferences on its source. Barian mica in the multiphase solid inclusions belongs to trioctahedral micas and represents a solid solution of phlogopite KMg₃(Si₃Al)O₁₀(OH)₂, kinoshitalite BaMg₃(Al₂Si₂)O₁₀(OH)₂ and ferrokinoshitalite BaFe₃(Al₂Si₂)O₁₀(OH)₂. In addition to Ba (0.24–0.67 apfu), mica is significantly enriched in Mg (X_Mg ~ 0.85 to 0.95), Cr (0.03–0.43 apfu) and Cl (0.04–0.34 apfu). The substitution vector involving Ba in the I-site which describes the observed chemical variability can be expressed as BaFe^IVAlClK_?1Mg_?1Si_?1(OH)_?1. A minor amount of Cr and ^VIAl enters octahedral sites following a substitution vector ^VI(Cr,Al)₂□^VI(Mg,Fe)_?3 towards chromphyllite and muscovite. As demonstrated by variable Ba and Cl contents positively correlating with Fe, barian mica composition is partly controlled by its crystal structure. Textural evidence shows that barian mica, together with other minerals in multiphase solid inclusions, crystallized from fluids trapped during garnet growth. The unusual chemical composition of mica reflects the mixing of two distinct sources: (1) an internal source, i.e. the host peridotite and its garnet, providing Mg, Fe, Al, Cr, and (2) an external source, represented by crustal-derived subduction-zone fluids supplying Ba, K and Cl. At UHP–UHT conditions recorded by the associated diamond-bearing metasediments (c. 1100 °C and 4.5 GPa) located above the second critical point in the pelitic system, the produced subduction-zone fluids transporting the elements into the overlying mantle wedge had a solute-rich composition with properties of a hydrous melt. The occurrence of barian mica with a specific chemistry in barium-poor mantle rocks demonstrates the importance of its thorough chemical characterization.     

3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE

Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as “The Internet of Things” solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.     

Long- and short-term volcanic hazard assessment of El Chichón Volcano (Mexico) through Bayesian inference

Natural Hazards - The 1982 eruption of El Chichón volcano constitutes the worst volcanic disaster in Mexico producing more than 2000 fatalities, thousands of displaced people and severe...     

Full-waveform topographic lidar: State-of-the-art

Airborne laser scanning (ALS) is an active remote sensing technique providing range data as 3D point clouds. This paper aims at presenting a survey of the literature related to such techniques, with emphasis on the new sensors called full-waveform lidar systems. Indeed, an emitted laser pulse interacts with complex natural and man-made objects leading to a temporal distortion of the returned energy profile. The new technology of full-waveform laser scanning systems permits one to digitize the complete waveform of each backscattered pulse. Full-waveform lidar data give more control to an end user in the interpretation process of the physical measurement and provide additional information about the structure and the physical backscattering characteristics of the illuminated surfaces. In this paper, the theoretical principles of full-waveform airborne laser scanning are first described. Afterwards, a review of the main sensors as well as signal processing techniques are presented. We then discuss the interpretation of full-waveform measures with special interest on vegetated and urban areas.     

Magnetic Lasso: A New Kinematic Solar Wind Propagation Method

Solar wind propagation from the point of measurement to an arbitrary target in the heliosphere is an important input for heliospheric, planetary and cometary studies. In this paper a new kinematic propagation method, the magnetic lasso method is presented. Compared to the simple ballistic approach our method is based on reconstructing the ideal Parker spiral connecting the target with the Sun by testing a previously defined range of heliographic longitudes. The model takes into account the eventual evolution of stream–stream interactions and handles these with a simple model based on the dynamic pressure difference between the two streams. Special emphasis is given to input data cleaning by handling interplanetary coronal mass ejection events as data gaps due to their different propagation characteristics. The solar wind bulk velocity is considered radial and constant. Density and radial magnetic field are propagated by correcting with the inverse square of the radial distance. The model has the advantage that it can be coded easily and fitted to the problem; it is flexible in selecting and handling input data and requires little running time.     

On the use of logistic regression for stellar classification

We are totally immersed in the Big Data era and reliable algorithms and methods for data classification are instrumental for astronomical research. Random Forest and Support Vector Machines algorithms have become popular over the last few years and they are widely used for different stellar classification problems. In this article, we explore an alternative supervised classification method scarcely exploited in astronomy, Logistic Regression, that has been applied successfully in other scientific areas, particularly biostatistics. We have applied this method in order to derive membership probabilities for potential T Tauri star candidates from ultraviolet-infrared colour-colour diagrams.