Discrimination of sand dunes and loess deposits using grain-size analysis in northeastern Iran

Identification and characterization of aeolian deposits in arid environments provide information on mechanisms of loess and sand accumulation. The objectives of this study were to (i) identify the distribution of aeolian deposits, (ii) discriminate loess and sand deposits using granulometric data, and (iii) describe the aeolian deposition in Sarakhs area, northeastern Iran. Particle size distributions of 26 surface samples were determined using a laser grain-size analyzer. Fine sand, very fine sand, and very coarse silt were dominant fractions in studied sediments, and the sum of these fractions ranged from 46.9% in loess deposits to 93.8% in sand dunes. The mean grain size (M _z ) of sand dunes ranged from 3.31 to 3.54 ?, which gradually changed to 4.09 to 5.50 ? in loess deposits. Sorting, skewness, and kurtosis ranged from 0.84 to 1.94 ?, 0.18 to 0.49, and 0.76 to 2.38, respectively. Aeolian deposits in the area resulted in the incorporation of Hariroud River system and Kopeh Dagh Mountains for aeolian particle production and accumulation. Alluvial comminution in Hariroud River is suggested the main mechanism of sand and silt production and flood plain environment the main reservoir of these particles. The mountains of Kopeh Dagh act as a barrier and play a key role for sand and loess accumulation.     

Numerically based proposals for the stiffness and strength of masonry infills with openings in reinforced concrete frames

Aimed at investigating the effect of openings on the in‐plane behaviour of masonry infills in reinforced concrete frames, a parametric study is presented based on model calibration via experimental tests. Two types of openings are investigated: central window openings and different combinations of door and window openings based on the typologies of southern European countries. First, a finite element model of the structure is made using the DIANA software program. Then, after calibration with experimental results, a parametric analysis is carried out to investigate the effect of the presence and location of the different types of openings on the in‐plane behaviour of the infilled frame. Finally, different equations for predicting the initial stiffness and lateral strength of infilled frames with any types of openings were obtained. An α factor related to the geometry of the piers between openings is proposed to take into account the location of the openings in the developed equations. Subsequently, the masonry infill panel is replaced by a diagonal strut. An empirical equation is also proposed for the width of an equivalent strut to replace a masonry infill panel with openings in such a way that they possess the same initial stiffness. Copyright © 2015 John Wiley & Sons, Ltd.     

Evaluating the Sensitivity of Image Fusion Quality Metrics to Image Degradation in Satellite Imagery

Referring to the high potential of topographic satellite in collecting high resolution panchromatic imagery and high spectral, multi spectral imagery, the purpose of image fusion is to produce a new image data with high spatial and spectral characteristics. It is necessary to evaluate the quality of fused image by some quality metrics before using this product in various applications. Up to now, several metrics have been proposed for image quality assessment; which are also applicable for quality evaluation of fused images. However, it seems more investigations are needed to inspect the potentials of proposed Image Fusion Quality Metrics (IFQMs) to registration accuracy, especially in high resolution satellite imagery. This paper focuses on such studies and, using different image fusion quality metrics, experiments are conducted to evaluate the sensitivity of such metrics to a set of high resolution satellite imagery covering urban areas. The obtained results clearly reveal that these metrics sometimes do not behave robust in the whole area and also their obtained results are inconsistence in different patch areas in comparison with the whole image. These limitations are in minimum situation for an image quality metric such as SAM and are completely tangible for image quality metrics such as ERGAS in case of multi modal and DIV and CC from mono modal category.     

Burden prediction in blasting operation using rock geomechanical properties

Burden prediction is a vital task in the production blasting. Both the excessive and insufficient burden can significantly affect the result of blasting operation. The burden which is determined by empirical models is often inaccurate and needs to be adjusted experimentally. In this paper, an attempt was made to develop an artificial neural network (ANN) in order to predict burden in the blasting operation of the Mouteh gold mine, using considering geomechanical properties of rocks as input parameters. As such here, network inputs consist of blastability index (BI), rock quality designation (RQD), unconfined compressive strength (UCS), density, and cohesive strength. To make a database (including 95 datasets), rock samples are used from Iran’s Mouteh goldmine. Trying various types of the networks, a neural network, with architecture 5-15-10-1, was found to be optimum. Superiority of ANN over regression model is proved by calculating. To compare the performance of the ANN modeling with that of multivariable regression analysis (MVRA), mean absolute error (E _a), mean relative error (E _r), and determination coefficient (R ²) between predicted and real values were calculated for both the models. It was observed that the ANN prediction capability is better than that of MVRA. The absolute and relative errors for the ANN model were calculated 0.05 m and 3.85%, respectively, whereas for the regression analysis, these errors were computed 0.11 m and 5.63%, respectively. Moreover, determination coefficient of the ANN model and MVRA were determined 0.987 and 0.924, respectively. Further, a sensitivity analysis shows that while BI and RQD were recognized as the most sensitive and effective parameters, cohesive strength is considered as the least sensitive input parameters on the ANN model output effective on the proposed (burden).     

Characterization of underground tunnel water hydrochemical system and uses through multivariate statistical methods: a case study from Maddhapara Granite Mine,Dinajpur, Bangladesh

A quality study of the drained water from Maddhapara Granite Mine underground tunnel was undertaken to study their hydrochemical variations and suitability for various uses employing chemical analysis, basic statistics, correlation matrix (r), cluster analysis, principal component/factor analyses, and ANOVA as the multivariate statistical methods. The results of chemical analysis of water show the modest variation in their ionic assemblage among different sampling points of the tunnel where Ca–HCO₃ type of hydrochemical facies is principally dominated. The correlation matrix shows a very strong to very weak positive, even negative, correlation relationship, suggesting the influence of different processes such as geochemical, biochemical processes, and multiple anthropogenic sources on controlling the hydrochemical evolution and variations of water in the mine area. Cluster analysis confirms that cluster 1 contains 68.75% of total samples, whereas cluster 2 contains 31.25%. On the whole, the dominated chemical ions of first cluster groups are Ca and HCO₃, suggesting a natural process similar to dissolution of carbonate minerals. The second cluster group consisted of Cl^? and SO₄ ^2? ions representing natural and anthropogenic hydrochemical process. The results of PCA/FA analysis illustrate that different processes are involved in controlling the chemical composition of groundwater in the mine area. The factor 1 loadings showed that pH, EC, TDS, Na, Mg, chloride, and sulfate which have high loading in this factor are expected to come from carbonate dissolution to oxidation conditions. One-way ANOVA describes the significance of dependent variables with respect to independent variables. ANOVA gives us the idea that EC, K⁺, Fe^total, SO ₄ ² , As, and Pb are the most important factors in controlling spatial differences in water quality in this tunnel. But different results have been encountered for different independent variables which might be due to dissimilar sources of water. From the qualitative analysis, it is clear that water quality is not very favorable for aquatic creatures as well as for drinking purposes. The water can be used for irrigation purposes without any doubt as SAR and RSC analysis provides good results. Moreover, the results of this research confirmed that the application of multivariate statistical analysis methods is apposite to inferring complex water quality data sets with its possible pollution sources. At the end, this research recommends (1) as water becomes more and more important, water treatment plants should be built before the water being used; (2) a detailed water step utilization plan should be set beforehand to guarantee tunnel water being used effectively; and (3) after the water being used for agriculture, elements in crops should be monitored continuously to ensure that ions and compounds that come from the tunnel water are lower than guideline values for human beings health.     

Geological and soil engineering properties of shallow landslides occurring in the Kutupalong Rohingya Camp in Cox’s Bazar,Bangladesh

Landslides - The Forcibly Displaced Myanmar Nationals (FDMN), historically known as ‘Rohingya’ who fled the 2017 ethnic atrocities and genocide in the Northern Rakhine State of Myanmar,...     

Coastal management in the Persian Gulf region within the framework of the ROPME programme of action

Persian Gulf is a semi-enclosed sea located in the Middle East and is connected to oceans through the narrow 55-km Strait of Hormuz. The Persian Gulf holds an estimated 57–66% of the world's known reserves of oil. The occurrence of three major battles in the Gulf region during the past three decades has created an atmosphere of commotion and uncertainty. Because of its marine geology, geographical location, and geopolitical sensitivity, coastal management in the Gulf region cannot be considered independently of its vast oil and natural gas reserves and environmentally related matters. The Regional Organization for Protection of Marine Environment (ROPME) forum was established in Kuwait in 1979 and quickly ratified by seven new member states (Bahrain, Iran, Iraq, Oman, Qatar, Saudi Arabia and the United Arab Emirates). Rapid growth of ROPME and shared coastal and marine environmental issues among littoral States have resulted in numerous successful plans laying the basis for future coastal management and development in the Persian Gulf region.Different plans were investigated to reach sustainable coastal management and environmental pollution prevention programmes in the Persian Gulf region and it was concluded that such plans could only be implemented when littoral states prioritize the management schemes in the Persian Gulf region and incorporate them into their own national legislation.Similar to many Regional Sea Programmes, ROPME has faced many drawbacks since its inception. Military conflicts, poor enforcement of protocols, lack of adequate coordination, disharmony among littoral states and lack of sufficient funding have put many coastal management programmes on hold.Demilitarization, enforcement of ROPME resolutions, and implementation of long-term economical growth planning are all part of an integrated coastal management programme that can bring about significant changes in the Persian Gulf area. Despite all existing differences and difficulties, many important tasks have been accomplished in the past two decades. Coastal management issues have been analyzed and well documented by ROPME. With the existing situation in the Gulf region, ROPME can effectively coordinate and implement the following tasks: monitor water quality and coastal habitat, develop and implement a comprehensive pollution prevention scheme, educate the public in terms of coastal preservation, train technical staff, put in place an effective pollution prevention and waste management programme, and establish the basis for an integrated regional coastal zone management plan.     

Automatic Surface Reconstruction Based on the Fusion of Fuzzy Logic and Robust Estimation Techniques

Automatic surface reconstruction by means of digital image matching essentially involves computation in both image and object spaces. In image space, image matching is performed according to certain radiometric and geometric similarity criteria for conjugate point determination. The matching operations may therefore be regarded as decision–making processes. In practice, however, the similarity criteria for conjugate point determination demonstrate non–deterministic behaviour. Thus, the nature of these decision–making processes is more compatible with fuzzy reasoning concepts. In object space, on the other hand, surface reconstruction procedures, which operate on the basis of previously determined conjugate points, are essentially deterministic in nature and hence demand rigorous geometric modelling. In this paper, a new approach for automatic surface modelling is proposed, based on two different mathematical treatments: a fuzzy logic reasoning method for the conjugate point determination in image space; and a robust finite elements approach for the surface modelling in object space. Tests carried out on real data demonstrate the high potential of the strategy proposed.     

Identification of Pitch Dynamics of An Autonomous Underwater Vehicle Using Sensor Fusion

This paper presents a method for identification of the hydrodynamic coefficients of the dive plane of an autonomous underwater vehicle. The proposed identification method uses the governing equations of motion to estimate the coefficients of the linear damping, added mass and inertia, cross flow drag and control. Parts of data required by the proposed identification method are not measured by the onboard instruments. Hence, an optimal fusion algorithm is devised which estimates the required data accurately with a high sampling rate. To excite the dive plane dynamics and obtain the required measurements, diving maneuvers should be performed. Hence, a reliable controller with satisfactory performance and stability is needed. A cascaded controller is designed based on the coefficients obtained using a semi-empirical method and its robustness to the uncertainties is verified by the μ-analysis method. The performance and accuracy of the identification and fusion algorithms are investigated through 6-DOF numerical simulations of a realistic autonomous underwater vehicle.