Ore deposits and epithermal evidences associated with intra-magmatic faults at Aïn El Araâr-Oued Belif ring structure (NW of Tunisia)

International Journal of Earth Sciences - Hydrothermal ore deposits at Aïn El Araâr-Oued Belif location are classified as epithermal deposits type. The ore bodies are hosted by upper...     

Paleoenvironment of geomorphic surfaces of an alluvial fan in the eastern Isfahan,Iran, in the light of micromorphology and clay mineralogy

Alluvial fans are one of the most important landforms in geomorphological and paloenvironmental studies. The objective of this study was the application of clay mineral assemblages and micromorphological properties of the studied paleosols in the geomorphic surfaces of an alluvial fan in the eastern Isfahan as proxies for paleoenvironmental and paleoclimatic changes. Micromorphology, X-ray diffraction, and scanning electron microscopy approaches were used to study the representative pedons. The results indicated that the illuviation process in the calcareous soils of the arid regions of the eastern Isfahan was probably in response to Quaternary moist conditions. There was no significant difference between clay coating properties of the studied relict and buried paleosols. Clay mineralogical study suggested that kaolinite and illite were inherited from the parent materials, while smectite and palygorskite were formed in the soil environment. Paleoargillic horizon was characterized by smectite and calcic (especially the calcrete) horizons were dominated by palygorskite. Palygorskite was accumulated by both neoformation and illuviation processes. High clay content, high intensity of smectite peak, and activity of the illuviation process in paleoargillic horizon demonstrated the seasonality of climate (rainfall) even in the moist periods of Quaternary in Central Iran. Clay mineralogical assemblages suggested a trend of increasing environmental aridity in the study area. This study, therefore, highlighted the role of clay mineralogical investigations in arid lands’ geomorphological and paleoenvironmental researches.     

Determination of zero difference GPS differential code biases for satellites and prominent receiver types

The differential code bias (DCB) is the differential hardware (e.g., the satellite or receiver) delay that occurs between two different observations obtained at the same or two different frequencies. There are two approaches used to estimate DCBs for receivers and satellites: the relative and absolute methods. The relative method utilizes a GPS network, while the absolute method determines DCBs from a single station (zero difference). Three receiver types based on the pseudo-range observables were used here to collect the GPS data: Codeless Tracking, Cross Correlation, and Non-Cross Correlation styles. According to its types, GPS receivers have responded to restrictions on the GPS signal structure in different ways. The main goal of the current research is providing a method to determine the DCBs of GPS satellites and dual frequency receivers. The developed mathematical model was based on spherical harmonic function and geometry-free combination of pseudo-range observables (C/A or/and P-code) according to receiver type. A new elevation-dependent weighting function with respect to GPS satellites in our algorithm was applied. The applied weighting function was used to consider the quality variation of satellite DCBs, which is caused by pseudo-range measurement errors. The code of the proposed mathematical model was written using MATLAB and is called “zero difference differential code bias estimation (ZDDCBE)”. This code was tested and evaluated using data from IGS GNSS stations and different types of GPS stations out of IGS network installed in Egypt and Saudi Arabia. The estimated values from the ZDDCBE code show a good agreement with the IGS analysis centers with a mean error of estimation for the receiver DCB equal 5.94%. Therefore, the ZDDCBE code can be used to estimate the DCB for any type of receiver regardless if the receiver is from IGS network or not.     

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na⁺), and sulfate concentration (SO₄ ^2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO₄ ^2?, 1.05 mEq/l for Na⁺, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄ ^2?, and HCO₃ ^?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs.     

Finite cube elements method for calculating gravity anomaly and structural index of solid and fractal bodies with defined boundaries

In this paper, we present the finite cube elements method (FCEM); a novel numerical tool for calculating the gravity anomaly g and structural index SI of solid models with defined boundaries and variable density distributions, tilted or in normal position (e.g. blocks, faulted blocks, cylinders, spheres, hemispheres, triaxial ellipsoids). Extending the calculation to fractal objects, such as Menger sponges of different orders and bodies defined by polyhedrons, demonstrates the robustness of FCEM. In addition, approximating the cube element by a sphere of equal volume makes the calculation of gravitation and related derivatives much simpler. In gravity modelling of a sphere, cubes with edges of 100 m and 200 m achieve a good compromise between running time and overall error.
Displaying the distribution of SI of the studied models on contour maps and profiles will have a strong impact on the forward and inverse modelling of potential field data, especially for Euler deconvolution.
For Menger sponges, plots of gravity elements g and its derivatives show similar patterns independent of fractal order. Moreover, both the pattern and magnitude of SI are independent of fractal order, allowing the use of SI as a new invariant measure for fractal objects. However, SI pattern and magnitude strongly depend on the depth to the buried bodies as do other elements
In this study, we also present a new type of plot; the structural index against distance variation diagrams from which we extract the three critical SI ( CSI ) values, one per axis. The inversion of gravity anomaly data at CSI values gives the optimal mean location of the buried body.     

Comparison of two intelligent models to estimate the instantaneous global solar radiation in semi-arid climate conditions: Application in Iran

Solar radiation incident on the earth’s surface is a fundamental input for many aspects of climatology, hydrology, biology, and architecture. In addition, it is an important parameter in solar energy applications. Due to the high cost of the measuring instruments of solar radiation, many researchers have suggested different empirical methods to estimate this essential parameter. In this study, with the help of fuzzy systems and neural networks, two models have been designed to estimate the instantaneous global solar radiation in Rafsanjan city which has a typical climatic conditions of semi-arid region of middle eastern countries. In fuzzy and neural network model, the inputs are the number of the given day in the year, time, ambient temperature and cloudiness, The comparison between the results of the models and the measurements, shows that the estimated global radiation is similar to the measurement; for fuzzy model, statistical indicators RMSE, MBE and t-test are 103.4367 \((\hbox {w/m}^{2})\), 4.1169 \((\hbox {w/m}^{2})\) and 9.1318, respectively and for ANN, they are 85.46 \((\hbox {w/m}^{2})\), 3.08 \((\hbox {w/m}^{2})\) and 5.41, respectively. As the results indicate, both models are able to estimate the amount of radiation well, while the neural network has a higher accuracy. The output of the modes for six other cities of Iran, with similar climate conditions, also proves the ability of the proposed models.     

Laboratory Characterization of Cemented Tailings Paste Containing Crushed Waste Rocks for Improved Compressive Strength Development

This paper aims at investigating some physical and mechanical characteristics of cemented tailings paste incorporating different amounts of crushed waste rocks (hereinafter called paste aggregate fill, PAF) for underground stope filling. Different mixture formulations were prepared with three classes of crushed waste rocks (or aggregate) grain size, namely 0/10, 0/15 and 0/20 mm. The amount of crushed waste rocks in the PAF mixtures ranges from 10 to 50% by volume (% v/v) (or 8–45% by mass, %m) of dry mill tailings and crushed waste rocks. The results show that the addition of crushed waste rocks in cemented tailings paste mixtures allows a significant unconfined compressive strength (UCS) development after 28 and 90 days of curing. The highest UCS was obtained from the mixtures containing 50% v/v of crushed waste rocks of class of size 0/15 mm. The PAF mixtures with the coarser crushed waste rocks (class of size of 0/20 mm) exhibit some particles segregation.     

Building frequency fluctuations from continuous monitoring of ambient vibrations and their relationship to temperature variations

Building frequencies (fundamental and higher modes) are a critical parameter especially in the field of structural health monitoring mainly based on the stability of the structural dynamic parameters of individual building (frequencies, damping and modes shape). One of the most used methods to find out these parameters is based on the use on ambient vibration analysis. In this work, we study the fluctuations over a month period of the fundamental frequencies (transverse and longitudinal) of a 3.5-story RC-building made of 2 identical units connected by a structural joint. Time independent building frequencies is a strong assumption; as illustrated by our experiment showing that over an observation period of a month, building frequencies fluctuate of about 3.5 %. A clear correlation is found between the building frequency fluctuations and temperature variations, with a phase-shift interpreted as the characteristic time of heat diffusion within the walls. This allows: (1) determining the thermal diffusivity of the structure, (2) inferring its relative stiffness variations, and (3) showing that its Young modulus varies linearly with temperature.     

Occurrence and significance of a cold-water carbonate pseudomorph in microbialites from a saline lake

Micron-scale pseudomorphs of calcite after ikaite were discovered in microbialites from Manito Lake, a large hypersaline lake in the Great Plains of western Canada. Although environmental conditions in the lakes of this region (seasonally cold temperatures, high salinities and elevated productivity) suggest that ikaite should be common, this is the first documentation of lacustrine ikaite in Canada and the Great Plains region of North America. The calcite pseudomorphs form a porous dendritic fabric, comprise the interiors of massive shoreline microbialite mounds and pinnacles, and are encased in centimeter-scale, laminated dolomite-aragonite rinds. Because of the limited thermodynamic stability of ikaite at or near freezing temperatures, the psuedomorphs of this mineral provide evidence of an extended cold episode during the first millennium AD. The Manito deposits also show high δ¹³C values, indicating elevated productivity and δ¹⁸O signatures are consistent with precipitation in a cold, somewhat fresher lake than present.