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Rahim Barzegar Asghar Asghari Moghaddam Amir Hossein Nazemi Jan Adamowski 《Environmental Earth Sciences》2018,77(16):597
Rapid population growth, industrialization, and agricultural expansion in the Khoy area (northwestern Iran) have led to its dependence on groundwater and degradation of groundwater quality. This study attempts to decipher the major processes and factors that degrade the groundwater quality of the Khoy plain. For this purpose, 54 groundwater samples from unconfined and confined aquifers of the plain were collected in July 2017 and analyzed for major cations and anions (Na, K, Ca, Mg, HCO3, SO4, and Cl), minor ions (NO3 and F), and Al. Magnesium and bicarbonate were identified as the dominant cation and anion, respectively. Several ionic ratios and geochemical modeling using PHREEQC indicated that the most important hydrogeochemical processes to affect groundwater quality in the plain were weathering and dissolution of evaporitic and silicate minerals, mixing, and ion exchange. There were smaller effects from evaporation and anthropogenic factors (e.g., industries). Results showed that the high salinity of the groundwater in the northeast area of the plain was due to the high solubility of the evaporitic minerals, e.g., halite and gypsum. Reverse ion exchange and the contribution of mineral dissolution were more significant than ion exchange in the northeastern part of the plain. Elevated salinity of the groundwater in the southeast was attributed mostly to reverse ion exchange and somewhat to evaporation. 相似文献
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Asghar Farhadi 《Arabian Journal of Geosciences》2018,11(12):330
The present investigation focused on the numerical simulation of the gravity currents of non-Newtonian fluids by means of the incompressible smoothed particle hydrodynamics (ISPH) approach. Firstly, to solve the rheological properties of the non-Newtonian Bingham model by ISPH method, the multi-viscodensity approach has been introduced. Then, this methodology has been used to simulate the annular viscometer and landslide deformation test cases. Through simulating these test cases, the viscoplastic behavior of the non-Newtonian viscosity and propagation of tsunami waves due to underwater landslide movement have been observed. Numerical results were in good agreement with the theoretical and experimental studies and showed that this methodology can be used to investigate precisely the generation and propagation of tsunami surface waves. 相似文献
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Volume Contents
Contents Volume 21 (2003) 相似文献4.
P‐wave data from a time‐lapse 3D OBC survey have been analysed to estimate and interpret azimuthal seismic anisotropy. This is achieved by careful processing to preserve the azimuthal signature. The survey images a major reservoir body in a channelized turbidite field in the Gulf of Mexico. Three distinct and significant anisotropy anomalies are discovered on or around this particular ‘4500‐ft sand’, all of which change intensity but not orientation with hydrocarbon production. These anomalies are distributed along the highest concentration of cumulative sand thickness, with their symmetry axes aligned with the main channel axis. We suspect that this time‐lapse anisotropy could be caused by the alignment of the depositional grain fabric. Theoretical calculation predicts that this mechanism, when combined with fluid‐saturation changes, can generate the observed pattern of behaviour. If further supported by other researchers, this result would indicate that appropriately designed seismic surveys could be a useful tool for palaeo‐direction studies in clastic reservoirs and also a useful constraint for directional permeability in the reservoir flow simulation model. 相似文献
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Mohammad Reza Nikoo Reza Kerachian Akbar Karimi Ali Asghar Azadnia Keighobad Jafarzadegan 《Environmental Earth Sciences》2014,71(9):4127-4142
In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran. 相似文献
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This paper evaluates the feasibility of using an artificial neural network (ANN) methodology for estimating the groundwater levels in some piezometers placed in an aquifer in north‐western Iran. This aquifer is multilayer and has a high groundwater level in urban areas. Spatiotemporal groundwater level simulation in a multilayer aquifer is regarded as difficult in hydrogeology due to the complexity of the different aquifer materials. In the present research the performance of different neural networks for groundwater level forecasting is examined in order to identify an optimal ANN architecture that can simulate the piezometers water levels. Six different types of network architectures and training algorithms are investigated and compared in terms of model prediction efficiency and accuracy. The results of different experiments show that accurate predictions can be achieved with a standard feedforward neural network trained usung the Levenberg–Marquardt algorithm. The structure and spatial regressions of the ANN parameters (weights and biases) are then used for spatiotemporal model presentation. The efficiency of the spatio‐temporal ANN (STANN) model is compared with two hybrid neural‐geostatistics (NG) and multivariate time series‐geostatistics (TSG) models. It is found in this study that the ANNs provide the most accurate predictions in comparison with the other models. Based on the nonlinear intrinsic ANN approach, the developed STANN model gives acceptable results for the Tabriz multilayer aquifer. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
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The ever‐increasing population in cities intensifies environmental pollution that increases the number of asthmatic patients. Other factors that may influence the prevalence of asthma are atmospheric parameters, physiographic elements and personal characteristics. These parameters can be incorporated into a model to monitor and predict the health conditions of asthmatic patients in various contexts. Such a model is the base for any asthma early warning system. This article introduces a novel ubiquitous health system to monitor asthmatic patients. Ubiquitous systems can be effective in monitoring asthmatic patients through the use of intelligent frameworks. They can provide powerful reasoning and prediction engines for analyzing various situations. Our proposed model encapsulates several tools for preprocessing, reasoning and prediction of asthma conditions. In the preprocessing phase, outliers in the atmospheric datasets were detected and missing sensor data were estimated using a Kalman filter, while in the reasoning phase, the required information was inferred from the raw data using some rule‐based inference techniques. The asthmatic conditions of patients were predicted accurately by a Graph‐Based Support Vector Machine in a Context Space (GBSVMCS) which functions anywhere, anytime and with any status. GBSVMCS is an improved version of the common Support Vector Machine algorithm with the addition of unlabeled data and graph‐based rules in a context space. Based on the stored value for a patient's condition and his/her location/time, asthmatic patients can be monitored and appropriate alerts will be given. Our proposed model was assessed in Region 3 of Tehran, Iran for monitoring three different types of asthma: allergic, occupational and seasonal asthma. The input data to our system included air pollution data, the patients’ personal information, patients’ locations, weather data and geographical information for 270 different situations. Our results showed that 90% of the system's predictions were correct. The proposed model also improved the estimation accuracy by 15% in comparison to conventional methods. 相似文献
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M. Nejad‐Asghar 《Astronomische Nachrichten》2011,332(6):631-636
It is believed that protostellar accretion disks are formed from nearly ballistic infall of molecular matter in rotating core collapse. Collisions of this infalling matter leads to formation of strong supersonic shocks, which if they cool rapidly, result in accumulation of that material in a thin structure in the equatorial plane. Here, we investigate the relaxation time of the protostellar accretion post‐shock gas using the smoothed particle hydrodynamics (SPH). For this purpose, a one‐dimensional head‐on collision of two molecular sheets is considered, and the time evolution of the temperature and density of the post‐shock region simulated. The results show that in strong supersonic shocks, the temperature of the post‐shock gas quickly increases proportional to square of the Mach number, and then gradually decreases according to the cooling processes. Using a suitable cooling function shows that in appropriate time‐scale, the center of the collision, which is at the equatorial plane of the core, is converted to a thin dense molecular disk, together with atomic and ionized gases around it. This structure for accretion disks may justify the suitable conditions for grain growth and formation of proto‐planetary entities (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim) 相似文献
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Deflection amplification factor for estimating seismic lateral deformations of RC frames 总被引：1，自引：1，他引：0
Different values have been assigned to the ratio of the defl ection amplifi cation factor(Cd) to the response modifi cation factor(R) for a specifi ed force-resisting system in the seismic design provisions while the same application is defi ned for it. An analytical study of the seismic responses of several reinforced concrete frames subjected to a suite of earthquake records performed in this research indicate that the stories’ overstrength and stiffness distribution along the structural height can affect local defl ections more than global ones. Therefore, the Cd/R ratio is calculated based on the ratio of both maximum inelastic to maximum elastic displacements and interstory drifts. Due to damage concentration in some specifi c stories, the defl ection amplifi cation factor calculated based on inelastic interstory drifts was larger than that of the inelastic displacements. Consequently, a minimum value of 1.0 is recommended for the Cd/R ratio in order to estimate maximum inelastic drifts. The ratio of inelastic to elastic displacement was generally found to increase slightly along the structural height for the studied RC models. In addition, it was detected that the story damage indices of the studied RC frames decrease when the inverted value of inelastic interstory drift ratios are increased through a(negative) power form. 相似文献