Numerical modeling of long waves in shallow water using Incremental Differential Quadrature Method

Incremental Differential Quadrature Method (IDQM) as a rapid and accurate method for numerical simulation of Nonlinear Shallow Water (NLSW) waves is employed. To the best of authors’ knowledge, this is the first endeavor to exploit DQM in coastal hydraulics. The one-dimensional NLSW equations and related boundary conditions are discretized in space and temporal directions by DQM rules and the resulting system of equations are used to compute the state variables in the entire computational domain. It was found that the splitting of total simulation time into a number of smaller time increments, could significantly enhance the performance of the proposed method. Furthermore, results of this study show two main advantages for IDQM compared with other conventional methods, namely; unconditional stability and minimal computational effort. Indeed, using IDQM, one can use a few grid points (in spatial or time direction) without imposing any stability condition on the time step to obtain an accurate convergent solution.     

Geochemistry of sedimentary rocks from Permian–Triassic boundary sections of Tethys Himalaya: implications for paleo-weathering,provenance, and tectonic setting

The geochemical characteristics of two sections—the Permian–Triassic boundary (PTB) Guryul Ravine section, Kashmir Valley, Jammu and Kashmir, India; and the Attargoo section, Spiti Valley, Himachal Pradesh, India—have been studied in the context of provenance, paleo-weathering, and plate tectonic setting. These sections represent the siliciclastic sedimentary sequence from the Tethys Himalaya. The PTB siliciclastic sedimentary sequence in these regions primarily consists of sandstones and shales with variable thickness. Present studied sandstones and shales of both sections had chemical index of alteration values between 65 and 74; such values reveal low-to-moderate degree of chemical weathering. The chemical index of weathering in studied samples ranged from 71 to 94, suggesting a minor K-metasomatism effect on these samples. Plagioclase index of alteration in studied sections ranged from 68 to 92, indicating a moderate degree of weathering of plagioclase feldspars. The provenance discriminant function diagram suggests that the detritus involved in the formation of present studied siliciclastic sedimentary rocks fall in quartzose sedimentary and felsic igneous provenances. These sediments were deposited in a passive continental margin plate tectonic setting according to their location on a Si₂O versus K₂O/Na₂O tectonic setting diagram.     

Steady critical discharge rates from vertical and horizontal wells in fresh–saline aquifers with sharp interfaces

In this study, the critical (or maximum) discharge rates before saline water enters a well were determined for vertical and horizontal wells in a freshwater aquifer which is separated from a static saline aquifer by a sharp interface. Flow around the well was solved by integration of a point sink solution along the well axis, and both the critical discharge rate and critical interface rise were determined through a comparison of the heads and vertical gradients at the saline–fresh water interface. The rates were determined for vertical and horizontal wells with various lengths and depths for different aquifer salinities. Results were generalized by drawing dimensionless type curves. The results showed that the dimensionless total critical discharge rates are higher for the longer horizontal wells and longer vertical wells with a certain bottom depth, and they almost linearly decrease with well depth at rates of 0.7–0.9. For the dimensionless well length of 0.2, the dimensionless total discharge rate of a horizontal well is about 0.1 more than that of a vertical well with the same length and well-top depth. Also, the critical discharge rates per unit length of well are inversely proportional to well length and remarkably higher for shallower wells. Additionally, the critical pumping rate is proportional to the salinity difference of the aquifers. These results were confirmed by comparison to existing solutions for vertical wells with dimensionless lengths of 0.2, 0.5 and 0.6, and for critical interface rises in the range of 0.75–0.9.     

APG:A novel python-based ArcGIS toolbox to generate absence-datasets for geospatial studies

One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of outputs.To solve this problem,this study develops the Absence Point Generation(APG)toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial studies.The APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude,slope degree,topographic wetness index,and distance from rivers,and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are gener-ated.To test the APG toolbox,we applied two benchmark algorithms of random forest(RF)and boosted regression trees(BRT)in a case study to investigate groundwater potential using three absence datasets i.e.,the APG,random,and selection of absence samples(SAS)toolbox.The BRT-APG and RF-APG had the area under receiver operating curve(AUC)values of 0.947 and 0.942,while BRT and RF had weaker per-formances with the SAS and Random datasets.This effect resulted in AUC improvements for BRT and RF by 7.2,and 9.7％from the Random dataset,and AUC improvements for BRT and RF by 6.1,and 5.4％from the SAS dataset,respectively.The APG also impacted the importance of the input factors and the pattern of the groundwater potential maps,which proves the importance of absence points in environmental bin-ary issues.The proposed APG toolbox could be easily applied in other environmental hazards such as landslides,floods,and gully erosion,and land subsidence.     

Application of Rock Mass Characterization for Determining the Mechanical Properties of Rock Mass: a Comparative Study

The results of geotechnical explorations, engineering geological investigation (including laboratory and in situ tests) and field observations have been used, along with borehole logging charts, to obtain the rock mass geotechnical data. Based on the data, the rock mass along the Sabzkuh water conveyance tunnel route was classified by rock mass rating (RMR), Q-system (Q), rock mass index (RMi) and geological strength index (GSI) (3 methods). A new series of correlations were established between the systems based on the data collected from the study area. These relationships were then compared with those reported in the literature, and two new relations were recommended. The classifications were utilized to calculate mechanical properties (rock mass strength and deformation modulus) of the rock mass along the tunnel according to available empirical relations, and to distinguish the upper-bound and lower-bound relations.     

Performance analysis of Diesel engines fueled by biodiesel blends via thermodynamic simulation of an air-standard Diesel cycle

Because of environmental problems, it becomes necessary to develop alternative fuels that give engine performance at par with diesel. Among the alternative fuels, biodiesel and its blends hold good promises as an eco-friendly and the most promising alternative fuel for Diesel engine. The properties of biodiesel and its blends are found similar to that of diesel. Many researchers have experimentally evaluated the performance characteristics of conventional Diesel engines fueled by biodiesel and its blends. However, experiments require enormous effort, money and time. Hence, via finite-time thermodynamics simulation, an air-standard Diesel cycle model with heat transfer loss and variable specific heats of working fluid is analyzed to predict the performance of Diesel engine. The effect of compression ratio, cut-off ratio and fuel type on output work and thermal efficiency is investigated through the model. The fuels considered for the analysis are conventional diesel, rapeseed oil biodiesel and its blend (20 % biodiesel and 80 % diesel by volume). Numerical simulations showed that the output work and thermal efficiency of the engine decrease with increase of cut-off ratio for all fuels. Also, the model predicts similar performance with diesel and biodiesel blend which means that the biodiesel blend (20 % biodiesel and 80 % diesel by volume) could be a good alternative and eco-friendly fuel for conventional Diesel engines without any need to modify the engine.     

Uranium (U) concentration and its genetic significance in the phosphorites of the Paleoproterozoic Bijawar Group of the Lalitpur district,Uttar Pradesh,India

The paper presents the uranium (U) concentration and distribution pattern in the Paleoproterozoic phosphorites of Lalitpur district of Uttar Pradesh. The study of thin sections, SEM and XRD reveal that apatite is the essential phosphate mineral while quartz and feldspars are the dominant gangue in the phosphorites of the investigated area. The collophane is observed to be mostly oolitic in form and microspherulitic in texture. The major element geochemistry indicated that the phosphorite samples are rich in P₂O₅, CaO, SiO₂ and Fe₂O₃ whereas depletion of MgO, MnO, K₂O and Al₂O₃ was observed. The CaO/P₂O₅ ratio ranges from 1.13 to 1.46 which is slightly lower than that of cations and anions substituted francolite (1.621) and close to that of carbonate-fluorapatite (1.318). The trace element geochemistry indicates that the phosphorites of Lalitpur have the significant range of U concentration (1.67 to 129.67 μg/g) which is more than that of Th (0.69 to 0.09 μg/g) among the analysed trace elements in the phosphorite samples of the area. The positive correlation of U with P₂O₅, CaO and U/P₂O₅ indicates a close association of U with phosphate minerals like collophane (apatite), whereas negative correlation of U with SiO₂ and Fe₂O₃ may be due to mutual replacement. The antipathetic relationship of U with Ni may be an indication of high oxidizing conditions, whereas sympathetic relationship of U with K₂O points towards higher alkaline conditions of the basin of deposition during phosphatization. The variable concentration of U and its relationship with significant major and trace elements in most of the phosphorite samples lead one to believe that the deposition of these phosphorites might have taken place in highly alkaline medium during fairly oxidizing to weakly reducing environmental conditions of geosynclinal basin.     

Artificial Neural Network as a Tool for Backbreak Prediction

Backbreak is one of the destructive side effects of the blasting operation. Reducing of this event is very important for economic of a mining project. Involvement of various parameters has made the backbreak analyzing difficult. Currently there is no any specific method to predict or control the phenomenon considering all the effective parameters. In this paper, artificial neural network (ANN) as a powerful tool for solving such complicated problems is used to predict backbreak in blasting operation of the Sangan iron mine, Iran. Network training was fulfilled using a collected database of the practiced operation including blast design details and rock condition. Trying various types of the networks, a network with two hidden layers was found to be optimum. Performance of the ANN model was compared with statistical analysis using datasets which were kept apart from the original database. According to the obtained results, for the ANN model there existed a higher correlation (R² = 0.868) and lesser error (RMSE = 0.495) between the predicted and measured backbreak as compared to the regression model. Also, sensitivity analysis revealed that the inputs rock factor and number of rows are the most and the least sensitive parameters on the output backbreak, respectively.     

Verification of two hydrological models for real-time flood forecasting in the Hindu Kush Himalaya (HKH) region

Natural Hazards - The Hindu Kush Himalayan region is extremely susceptible to periodic monsoon floods. Early warning systems with the ability to predict floods in advance can benefit tens of...