Statistical analysis of stress transmission in wet granular materials

The micromechanics of wet granular materials encompasses complex microstructural and capillary interconnects that can be readily described through a formal derivation of stress transmission in such a 3‐phase medium. In the quest for defining an appropriate stress measure, the stress tensor expression that results from homogenization [Duriez et al. J Mech Phys Solids 99 (2017): 495‐511] of such a medium provides theoretical insights necessary to extract useful information on the relationship between capillary effects and microforce interactions via several small‐scale parameters whose evaluation can be challenging. Using instead a statistical approach where microvariable distributions are described by probability density functions, the current study provides simple estimates of stress components in terms of only a few tractable microvariables such as coordination number and fabric anisotropy. In particular, the latter recognizes details of contacts such as force interactions being either mechanical or capillary, including interactions with and without mechanical contact. The developed expressions are in a good agreement with discrete element method simulation results of the triaxial loading of a wet granular assembly, notably for hydrostatic (mean) pressure. A new set of dimensionless groups is also identified to characterize the significance of mechanical and capillary physics, which facilitates a better understanding of the contribution of dominating elements to stress, while also providing the opportunity to incorporate important capillary effects in micromechanically based constitutive formulations.     

Multi-level Optimization of Reservoir Scheduling Using Multi-resolution Wavelet-Based Up-scaled Models

This paper presents a multi-level procedure for production and injection scheduling through a numerical model-based optimization of well control variables. To calculate the net present value (NPV), the objective function of optimization, this procedure uses a number of discretized systems for a reservoir model with different degrees of up-scaling prepared according to a multi-resolution wavelet technique. These up-scaled models were incorporated into optimization based on a probability function. In early optimization iterations, due to the necessity to explore the search space quickly, the coarsest grid model has a higher chance for selection than the others; however, by a selection (with a low probability) of the finest up-scaled grid model in these iterations, solutions and objective function were tuned. In the later iterations of optimization, the finest up-scaled grid model probability was the highest in order to ensure the reliability of the final solution. The optimization algorithm is an adaptive simulated annealing algorithm coupled with a polytope. This procedure was evaluated in two case studies. The first case study was a horizontal 2D oil model with water flooding. The second case study was a vertical 2D oil model with gas injection. The results show that the proposed optimization procedure provides approximately the same accuracy compared to the situation in which the fine grid model is used for all the optimization iterations. Also, the run-time for the proposed optimization procedure is comparable to the run-time of the optimization in which only the coarsest grid model is used to calculate objective function. Moreover, the superiority of the wavelet-based up-scaling over an analogous multiple grid system optimization using uniformly up-scaled models is presented.

     

Analysis of Spatial Autocorrelation Patterns of Heavy and Super-Heavy Rainfall in Iran

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran's heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord Gistatistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran,have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.     

Soil Moisture Estimation in a Vegetated Area Using Combination of AIRSAR and Landsat5-TM Images

High difference between dielectric constant of water (dielectric constant about 80) and dielectric constant of dried soil (dielectric constant about 2–3) makes Synthetic Aperture Radar (SAR) highly capable in soil moisture estimation. However, there are other factors which affect on radar backscattering coefficient. The most important parameters are vegetation cover, surface roughness and sensor parameters (frequency, polarization and incidence angle). In this paper, the importance of considering the effects of these parameters on SAR backscatter coefficients is shown by comparing different soil moisture estimation models. Moreover, an experimental soil moisture estimation model is developed. It is shown that this model can be used to estimate soil moisture under a variety of vegetation cover densities. The new developed model is based on combination of different indices derived from Landsat5-Thematic Mapper and AIRSAR images. The AIRSAR image is used for extraction of backscattering coefficient and incidence angle while TM image is used for calculation of Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI) and Brightness Temperature. Then a soil moisture estimation model which is named as Hybrid model is developed based on integration of all of these parameters. The accuracies of this model are assessed in the NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7 by using SAR data in C band and L band frequencies and also in different polarizations of HH, HV, VV and TP. The results show that for instance in L band with HV polarization, R-square values of 0.728, 0.628 and 0.527 are obtained between ground measured soil moisture and estimated soil moisture values using the Hybrid model for NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7, respectively.     

Reworking of intra-oceanic rocks in a deep sea basin: example from the Bou-Maiza complex (Edough massif,eastern Algeria)

Metagabbros and amphibolites exposed in the Bou-Maïza area of the Edough massif (northeast Algeria) are described in detail. Field and petro-structural observations point to the syn-sedimentary emplacement of gabbros as clasts, blocks and lenses of polymictic gabbroic breccias. Associated amphibolites display fine-scale parallel sedimentary bedding and represent mafic epiclastites, litharenites and mafic greywackes. The mafic beds and lenses are intercalated with aluminous pelitic schists of continental origin, quartzite and marble. It is concluded that all mafic rocks from this locality derive from the erosion of an oceanic plutono-volcanic complex of MORB affinity that was reworked in a block matrix mélange and emplaced as turbidites and debris flows during the Mesozoic. We propose a convergent plate margin setting for these formations connected with the subducted Calabrian branch of the Tethyan slab.     

Early Mesozoic sedimentary‒tectonic evolution of the Central-East Iranian Microcontinent: Evidence from a provenance study of the Nakhlak Group

In Central Iran, the mixed siliciclastic?carbonate Nakhlak Group of Triassic age is commonly seen to have a Cimmerian affinity, although it shows considerable resemblances with the Triassic Aghdarband Group in far northeastern Iran, east of Kopeh-Dagh area, with Eurasian affinity. The Nakhlak Group is composed of the Alam (Late Olenekian?Anisian), Baqoroq (Late Anisian??Early Ladinian), and Ashin (Ladinian??Early Carnian) formations consisting mainly of volcanoclastic sandstone and shale and fossiliferous limestone. The Baqoroq Formation contains also metamorphic detritus. Sandstone petrofacies reflect the detrital evolution from active volcanism to growing orogen and again active volcanism. Textural and modal analyses of volcanic lithic fragments from the Alam Formation reflect the eruption style and magma composition of a felsic to intermediate syn-sedimentary arc activity. The detrital modes of the Baqoroq Formation sediments suggest a recycled orogenic source followed by arc activity in a remnant fore-arc basin. The sandstone samples from the Ashin Formation demonstrate a continuity of felsic to intermediate arc activity. Major and trace element concentrations of the Nakhlak Group clastic samples support sediment supply from first-cycle material and felsic magmatic arc input. The enrichment in LREE, the negative Eu anomalies, and the flat HREE patterns indicate origination from the old upper continental crust and young arc material. The chemical index of alteration (CIA ～51–70 for sandstone and 64–76 for shale samples) indicates medium degrees of chemical weathering at the source. Petrographical and geochemical evidence together with facies analysis constructed the following depositional conditions for the Nakhlak Group sediments: In the Olenekian, a fore-arc shallow to deep marine depositional basin developed that later was filled by recycled and arc-related detritus and changed into a continental basin in the Anisian. Ladinian extension let to a deepening of the basin. With respect to the similarities between the Nakhlak and Aghdarband (NE Iran) groups and unusual present-day position of the Nakhlak Group with no stratigraphic connection to the surrounding area, the development of first a fore-arc basin and later change into a back-arc depositional basin in close relation with the Aghdarband basin at the southern Eurasian active margin in the Triassic are here proposed. Understanding the basin development recorded in the Nakhlak Group provides constraints on the closure history of Palaeotethys and of the tectonic evolution of early Mesozoic basins at the southern Eurasian margin before the Cimmerian Orogeny.     

Geoid modelling based on EGM08 and recent Earth gravity models of GOCE

In this paper an estimator for geoid is presented and applied for geoid computation which considers the topographic and atmospheric effects on the geoid. The total atmospheric effect is mathematically developed in terms of spherical harmonics to degree and order 2,160 based on a recent static atmospheric density model. Also the contribution of its higher degrees is formulated. Another idea of this paper is to combine one of the recent Earth gravity models (EGMs) of the Gravity field and steady-state Ocean Circulation Explorer (GOCE) mission with EGM08 and the terrestrial gravimetric data of Fennoscandia in an optimum way. To do so, the GOCE EGMs are compared with the Global Positioning System (GPS)/levelling data over the area for finding the most suited one. This comparison is done in two different ways: with and without considering the errors of the EGMs. Comparison of the computed geoids with the GPS/levelling data shows that a) considering the total atmospheric effect will improve the geoid by about 5 mm, b) GOCO03S is the most suited GOCE EGM for Fennoscandia, c) the errors of some of the GOCE EGMs are optimistic and far from reality. Combination of GOCO03S from degree 120 to 210 and EGM08 for the rest of degrees shows its good quality in these frequencies.     

Optimal fusion of optical and SAR high-resolution images for semiautomatic building detection

Building detection from different high-resolution aerial and satellite images has been a notable research topic in recent decades. The primary challenges are occlusions, shadows, different roof types, and similar spectral behavior of urban covers. Integration of different data sources is a solution to supplement the input feature space and improve the existing algorithms. Regarding the different nature and unique characteristics of optical and radar images, there are motivations for their fusion. This paper is aimed to identify an optimal fusion of radar and optical images to overcome their individual shortcomings and weaknesses. For this reason, panchromatic, multispectral, and radar images were first classified individually, and their strengths and weaknesses were evaluated. Different feature-level fusions of these data sets were then assessed followed by a decision-level fusion of their results. In both the feature and decision levels of integration, artificial neural networks were applied as the classifiers. Several post-processing methods using normalized different vegetation index, majority filter, and area filter were finally applied to the results. Overall accuracy of 92.8% and building detection accuracy of 89.1% confirmed the ability of the proposed fusion strategy of optical and radar images for building detection purposes.     

Paleoenvironmental conditions of Early Miocene corals,western Makran,Iran

Miocene coral-bearing limestones, distributed in the western Makran Basin, are attributed to Aquitanian and Burdigalian. This investigation is focused on three Early Miocene coral-bearing limestone sections in western Makran. Remarkably, well-preserved scleractinian corals and other components could be very definitive to reconstruct paleoenvironmental conditions. Lithologically, there are some differences between the studied sections. Furthermore, zooxanthellate corals are diverse and abundant in all sections. Based on different components and richness of zooxanthellate corals, it seems that the studied carbonate corals are precipitated in a subtropical condition, between 19 and 20 °C in all sections. In light of the dominancy of corals, the presence of symbiont-bearing larger benthic foraminifera (LBF), lithological features, bioeroding features, and encrusting organisms, the oligotrophic to slightly mesotrophic conditions are considered for Tejek section and the mesotrophic condition had been prevailed in Kermestan and Irer sections. According to light intensity in water column and coral morphotypes, Tejek section is considered to precipitate under euphotic to slightly mesophotic condition, while Kermestan and Irer sections were deposited under mesophotic to euphotic light conditions. In transparent water, photic zones continue to deeper depths, while in less transparent water, these zones are limited to shallower parts. A defined depth in the photic zone may represent euphotic, mesophotic, or oligophotic zone. Based on the water transparency, a taxon in a defined photic zone can occur in various depths. On the basis of trophic-light intensity-depth chart, the estimated depth ranges are 12–85 m for Tejek section and 5–62 m for Kermestan and Irer sections. Water energy as another important factor in environmental condition is acquired from coral morphotypes. Accordingly, Tejek section is precipitated under moderate-high energy and Kermestan and Irer sections are deposited in low to moderate-high energy. The presence of encrusting coralline algae, corals, and other constituents is indicative of different substrates in the studied areas. Corals favorably develop in normal salinity waters. The existence of colonial corals and occurrence of benthic foraminifera with hyaline wall indicate normal seawater conditions.     

Large‐scale regional delineation of riparian vegetation in the arid and semi‐arid Pilbara region,WA

Multiscene Landsat 5 TM imagery, Principal Component Analysis, and the Normalized Difference Vegetation Index were used to produce the first region‐scale map of riparian vegetation for the Pilbara (230,000 km²), Western Australia. Riparian vegetation is an environmentally important habitat in the arid and desert climate of the Pilbara. These habitats are supported by infrequent flow events and in some locations by groundwater discharge. Our analysis suggests that riparian vegetation covers less than 4% of the Pilbara region, whereas almost 10.5% of this area is composed of groundwater dependent vegetation (GDV). GDV is often associated with open water (river pools), providing refugia for a variety of species. GDV has an extremely high ecological value and are often important Indigenous sites. This paper demonstrates how Landsat data calibrated to Top of Atmosphere reflectance can be used to delineate riparian vegetation across 16 Landsat scenes and two Universal Transverse Mercator spatial zones. The proposed method is able to delineate riparian vegetation and GDV, without the need for Bidirectional Reflectance Distribution Function correction. Results were validated using ground truth data from local and regional scale vegetation surveys.