A pairwise likelihood approach for the empirical estimation of the underlyingvariograms in the plurigaussian models

The plurigaussian model is particularly suited to describe categorical regionalized variables. Starting from a simple principle, the thresh-olding of one or several Gaussian random fields (GRFs) to obtain categories, the plurigaussian model is well adapted for a wide range ofsituations. By acting on the form of the thresholding rule and/or the threshold values (which can vary along space) and the variograms ofthe underlying GRFs, one can generate many spatial configurations for the categorical variables. One difficulty is to choose variogrammodel for the underlying GRFs. Indeed, these latter are hidden by the truncation and we only observe the simple and cross-variogramsof the category indicators. In this paper, we propose a semiparametric method based on the pairwise likelihood to estimate the empiricalvariogram of the GRFs. It provides an exploratory tool in order to choose a suitable model for each GRF and later to estimate its param-eters. We illustrate the efficiency of the method with a Monte-Carlo simulation study .The method presented in this paper is implemented in the R packageRGeostats.Comment: To be submitted to Spatial Statistic

Yielding of rockfill in relative humidity-controlled triaxial experiments

The final publication is available at Springer via http://dx.doi.org/10.1007/s11440-016-0437-9The paper reports the results of suction controlled triaxial tests performed on compacted samples of two well graded granular materials in the range of coarse sand-medium gravel particle sizes: a quartzitic slate and a hard limestone. The evolution of grain size distributions is discussed. Dilatancy rules were investigated. Dilatancy could be described in terms of stress ratio, plastic work input and average confining stress. The shape of the yield locus in a triaxial plane was established by different experimental techniques. Yielding loci in both types of lithology is well represented by approximate elliptic shapes whose major axis follows approximately the Ko line. Relative humidity was found to affect in a significant way the evolution of grain size distribution, the deviatoric stress-strain response and the dilatancy rules.Peer ReviewedPostprint (author's final draft

Mathematical models for erosion and the optimal transportation of sediment

We investigate a mathematical theory for the erosion of sediment which begins with the study of a non-linear, parabolic, weighted 4-Laplace equation on a rectangular domain corresponding to a base segment of an extended landscape. Imposing natural boundary conditions, we show that the equation admits entropy solutions and prove regularity and uniqueness of weak solutions when they exist. We then investigate a particular class of weak solutions studied in previous work of the first author and produce numerical simulations of these solutions. After introducing an optimal transportation problem for the sediment flow, we show that this class of weak solutions implements the optimal transportation of the sediment

Towards the optimal Pixel size of dem for automatic mapping of landslide areas

Determining appropriate spatial resolution of digital elevation model (DEM) is a key step for effective landslide analysis based on remote sensing data. Several studies demonstrated that choosing the finest DEM resolution is not always the best solution. Various DEM resolutions can be applicable for diverse landslide applications. Thus, this study aims to assess the influence of special resolution on automatic landslide mapping. Pixel-based approach using parametric and non-parametric classification methods, namely feed forward neural network (FFNN) and maximum likelihood classification (ML), were applied in this study. Additionally, this allowed to determine the impact of used classification method for selection of DEM resolution. Landslide affected areas were mapped based on four DEMs generated at 1m, 2m, 5m and 10m spatial resolution from airborne laser scanning (ALS) data. The performance of the landslide mapping was then evaluated by applying landslide inventory map and computation of confusion matrix. The results of this study suggests that the finest scale of DEM is not always the best fit, however working at 1m DEM resolution on micro-topography scale, can show different results. The best performance was found at 5m DEM-resolution for FFNN and 1m DEM resolution for results. The best performance was found to be using 5m DEM-resolution for FFNN and 1m DEM resolution for ML classification

NASA guidelines on report literature

NASA seeks for inclusion in its Scientific and Technical Information System research reports, conference proceedings, meeting papers, monographs, and doctoral and post graduate theses which relate to the NASA mission and objectives. Topics of interest to NASA are presented

Reconstruction of three-dimensional porous media using generative adversarial neural networks

To evaluate the variability of multi-phase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a novel method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image datasets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that GANs can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.Comment: 21 pages, 20 figure

Geochemical constraints on the Hadean environment from mineral fingerprints of prokaryotes

The environmental conditions on the Earth before 4 billion years ago are highly uncertain, largely because of the lack of a substantial rock record from this period. During this time interval, known as the Hadean, the young planet transformed from an uninhabited world to the one capable of supporting, and inhabited by the first living cells. These cells formed in a fluid environment they could not at first control, with homeostatic mechanisms developing only later. It is therefore possible that present-day organisms retain some record of the primordial fluid in which the first cells formed. Here we present new data on the elemental compositions and mineral fingerprints of both Bacteria and Archaea, using these data to constrain the environment in which life formed. The cradle solution that produced this elemental signature was saturated in barite, sphene, chalcedony, apatite, and clay minerals. The presence of these minerals, as well as other chemical features, suggests that the cradle environment of life may have been a weathering fluid interacting with dry-land silicate rocks. The specific mineral assemblage provides evidence for a moderate Hadean climate with dry and wet seasons and a lower atmospheric abundance of CO2 than is present today.Fil: Novoselov, Alexey A.. Universidad de Concepción; ChileFil: Silva, Dailto. Universidade Estadual de Campinas; BrasilFil: Schneider, Jerusa. Universidade Estadual de Campinas; BrasilFil: Abrevaya, Ximena Celeste. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Chaffin, Michael S.. State University Of Colorado Boulder; Estados UnidosFil: Serrano, Paloma. Alfred Wegener Institute Helmholtz Centre For Polar And Marine Research,; AlemaniaFil: Navarro, Margareth Sugano. Universidade Estadual de Campinas; BrasilFil: Conti, Maria Josiane. André Tosello Institute; BrasilFil: Souza Filho, Carlos Roberto de. Universidade Estadual de Campinas; Brasi