Identification of hidden faults using determining velocity structure profile by spatial autocorrelation method in the west of Mashhad plain (Northeast of Iran)

Characterizing the subsurface structure is an important parameter for the improvement of seismic hazard assessment.Due to the tectonic complexity of the earth,s...     

Zircon U-Pb geochronology and geochemistry of Late Devonian–Carboniferous granitoids in NW Iran: implications for the opening of Paleo-Tethys

ABSTRACT

We present zircon U-Pb crystallization ages combined with bulk rock major and trace element geochemistry and Sr-Nd-Pb and zircon in-situ Hf isotopic compositions of the Amand and Moro granitoid intrusions in northwest Iran. The Amand and Moro plutons include granite and syeno-diorite with LA-ICP-MS U-Pb zircon ages of 367 ± 6.8 Ma and 351 ± 1.3 Ma, respectively, representative of Late Devonian-Early Carboniferous magmatic activity in NW Iran. Geochemical characteristics such as typical enrichments in alkalis, Nb, Zr, Ga and Y, depletion in P and Sr and fractionated REE patterns with high Ga/Al ratios and Eu negative anomalies are consistent with A-type magmatic signatures. The granitoids are classified as A₂-type and within-plate granitoids. The bulk rock geochemistry (enrichments in Th, Nb and, high Th/Yb, Zr/Y ratios) along with low variation of ¹⁴³Nd/¹⁴⁴Nd_(i) and ⁸⁷Sr/⁸⁶Sr_(i) ratios and positive zircon εHf_(t) support the role of a mantle plume component for the evolution of the Amand and Moro A-type granitoids in an extensional tectonic environment. In fitting with wider regional knowledge, this magmatism occurred during Paleo-Tethys opening in northern Gondwana.     

Evaluation of two satellite-based products against ground-based observation for drought analysis in the southern part of Iran

Natural Hazards - Water stress or more specifically drought assessment plays a key role in water management, especially in extreme climate conditions. Basically, globally gridded satellite-based...     

The Effect of Impervious Clay Core Shape on the Stability of Embankment Dams

One of the most important dangers that treat earth dams which can lead to interior failure over a prolonged period is the hydraulic fracturing factor. In the case of zoned dams, due to differences in stiffness of the core and its abutment zone, differential settlements occur between them. This factor is responsible for the arching phenomenon. Differential settlements between core and shell cause cracks within the core initially sub-surface, Those cracks may develop the first impounding causing internal erosion on the dam core. In this research, using a computer modeling of Ghavoshan rockfill dam (located the west part of Iran) as a case study computed by SIGMA/W program, the role of the dam core shape on those factors is demonstrated. It is found that an inclined core shape is preferred in a condition that is especially important settlements of construction during for dam body. The result of finite element analysis indicates desired conditions from the point of view of stress, deformation and resistance against hydraulic fracturing for the same width of dam designs. Moreover, this can be higher priority for embankment dam designs.     

Comparison of LLR,MLP, Elman,NNARX and ANFIS Models—with a case study in solar radiation estimation

Despite the widespread application of nonlinear mathematical models, comparative studies of different models are still a huge task for modellers. This is because a large number of trial and error processes are needed to develop each model, so the workload will be multiplied into an unmanageable level if many types of models are involved. This study presents an efficient approach by using the Gamma test (GT) to select the input variables and the training data length, so that the trial and error workload can be greatly reduced. The methodology is tested in estimating solar radiation at the Brue catchment, UK. Several nonlinear models have been developed efficiently with the aid of the GT, including local linear regression, multi-layer perceptron (MLP), Elman neural network, neural network auto-regressive model with exogenous inputs (NNARX) and adaptive neuro-fuzzy inference system (ANFIS). This work is only feasible within the time and resources constraint, due to the GT in reducing huge workload of the trial and error process.     

Numerical Simulation of Solute Transport in Saturated Porous Media with Bounded Domains

This work presents the first attempt to develop unconditionally stable, implicit finite difference solutions of one-sided spatial fractional advection-dispersion equation (s-FADE) by imposing the nonzero Dirichlet boundary condition (ND BC) or the nonzero fractional Robin boundary condition (NFR BC) at inlet boundary and the zero fractional Neumann boundary condition (ZFN BC) at outlet boundary. The results of the numerical studies performed using artificial solute transport parameters demonstrated that the numerical solution with the NFR BC as the inlet boundary produced much more realistic concentration values. The numerical solution with the NFR BC at the inlet boundary was capable of correctly describing the Fickian and non-Fickian behaviors of the solute transport at different α values, and it had the relatively same accuracy at different numbers of the spatial nodes. Also, the practical application of the numerical solution with the NFR BC as the inlet boundary was investigated by conducting tracer experiments in homogeneous and heterogeneous soil columns. According to the obtained results, this numerical solution described well solute transport in the homogenous and heterogeneous soils. The α values of the homogeneous and heterogeneous soils were obtained in the ranges of 1.849–1.999 and 1.248–1.570, respectively, which were in excellent agreement with the physical properties of the soils. In a nutshell, the numerical solution of the s-FADE with the NFR BC as the inlet boundary can be successfully applied to describe the solute transport in the homogeneous and heterogeneous soils with bounded spatial domains.     

Adaptive neuro-fuzzy inference system coupled with shuffled frog leaping algorithm for predicting river streamflow time series

ABSTRACT

Accurate runoff forecasting plays a key role in catchment water management and water resources system planning. To improve the prediction accuracy, one needs to strive to develop a reliable and accurate forecasting model for streamflow. In this study, the novel combination of the adaptive neuro-fuzzy inference system (ANFIS) model with the shuffled frog-leaping algorithm (SFLA) is proposed. Historical streamflow data of two different rivers were collected to examine the performance of the proposed model. To evaluate the performance of the proposed ANFIS-SFLA model, six different scenarios for the model input–output architecture were investigated. The results show that the proposed ANFIS-SFLA model (R² = 0.88; NS = 0.88; RMSE = 142.30 (m³/s); MAE = 88.94 (m³/s); MAPE = 35.19%) significantly improved the forecasting accuracy and outperformed the classic ANFIS model (R² = 0.83; NS = 0.83; RMSE = 167.81; MAE = 115.83 (m³/s); MAPE = 45.97%). The proposed model could be generalized and applied in different rivers worldwide.     

Axial compressive bearing capacity of piles in ‎oil-contaminated sandy soil using FCV

ABSTRACT

Oil and its derivatives contaminate many soils and not only affect their chemical and biological properties but also their geotechnical properties. As oil contamination may deteriorate the functioning of piles, this paper addresses the effects of oil contamination on soil–pile interactions. Axial compressive bearing capacities of two close-ended, instrumented piles were investigated in different oil-contaminated sand using frustum confining vessel. Three different oils (gasoil, crude oil, and used motor oil) at different contamination levels were considered and using some strain gauges, the toe, shaft, and the net total bearing capacity of piles, as well as load distributions along the pile length, were derived. The results show that the presence of oil between soil particles has considerable adverse effects on bearing capacities of model piles, especially the shaft bearing capacity. The oil viscosity and percentage, as well as the contaminated sand bed thickness around the piles, are the most influential parameters. The higher the oil viscosity and oil content, the lower the values of the piles’ bearing capacities in comparison to the uncontaminated sand. With some modifications on the bearing capacity parameters of CFEM method, a good agreement was observed between measured and calculated bearing capacity values.     

Earthquake-induced landslide prediction using back-propagation type artificial neural network: case study in northern Iran

Natural Hazards - Landslides can cause extensive damage, particularly those triggered by earthquakes. The current study used back propagation of an artificial neural network (ANN) to conduct risk...