The maximum expected earthquake magnitudes in different future time intervals of six seismotectonic zones of Iran and its surroundings     

Mona Salamat  Gert Zöller  Mehdi Zare  Mortaza Amini 《Journal of Seismology》2018,22(6):1485-1498

One of the crucial components in seismic hazard analysis is the estimation of the maximum earthquake magnitude and associated uncertainty. In the present study, the uncertainty related to the maximum expected magnitude μ is determined in terms of confidence intervals for an imposed level of confidence. Previous work by Salamat et al. (Pure Appl Geophys 174:763-777, 2017) shows the divergence of the confidence interval of the maximum possible magnitude m_max for high levels of confidence in six seismotectonic zones of Iran. In this work, the maximum expected earthquake magnitude μ is calculated in a predefined finite time interval and imposed level of confidence. For this, we use a conceptual model based on a doubly truncated Gutenberg-Richter law for magnitudes with constant b-value and calculate the posterior distribution of μ for the time interval T_f in future. We assume a stationary Poisson process in time and a Gutenberg-Richter relation for magnitudes. The upper bound of the magnitude confidence interval is calculated for different time intervals of 30, 50, and 100 years and imposed levels of confidence α?=?0.5, 0.1, 0.05, and 0.01. The posterior distribution of waiting times T_f to the next earthquake with a given magnitude equal to 6.5, 7.0, and 7.5 are calculated in each zone. In order to find the influence of declustering, we use the original and declustered version of the catalog. The earthquake catalog of the territory of Iran and surroundings are subdivided into six seismotectonic zones Alborz, Azerbaijan, Central Iran, Zagros, Kopet Dagh, and Makran. We assume the maximum possible magnitude m_max?=?8.5 and calculate the upper bound of the confidence interval of μ in each zone. The results indicate that for short time intervals equal to 30 and 50 years and imposed levels of confidence 1???α?=?0.95 and 0.90, the probability distribution of μ is around μ?=?7.16???8.23 in all seismic zones.  相似文献   

Review Paper: Post-stack 4D seismic time-shifts: Interpretation and evaluation     

Colin MacBeth  Maria-Daphne Mangriotis  Hamed Amini 《Geophysical Prospecting》2019,67(1):3-31

A review and analysis of post-stack time-lapse time-shifts has been carried out that covers published literature supplemented by in-house datasets available to the authors. Time-shift data are classified into those originating from geomechanical effects and those due to fluid saturation changes. From these data, conclusions are drawn regarding the effectiveness of post-stack time-shifts for overburden and reservoir monitoring purposes. A variety of field examples are shown that display the range and magnitude of variation for each class of application. The underlying physical mechanisms creating these time-shifts are then described, and linked to a series of generic and field-specific rock physics calculations that predict their magnitudes. These calculations serve as a guide for practitioners wishing to utilize this information on their own datasets. Conclusions are drawn regarding the reliability of this attribute for monitoring purposes, and the extent to which further development is required and how it should be reported by authors.  相似文献   

Reduction of local scour at river conf luences using a collar     

Nargess Amini  Behnam Balouchi  Mahmood Shafai Bejestan 《国际泥沙研究》2017,32(3)

River confluences (RCs) are important features within river systems where the three dimensional (3D) flow structures and the downstream mixing of flows can cause deep scour holes. Despite this, few methods have been proposed to control scouring at RCs. In this study, application of a collar was experimentally examined for local scour control at the point where two rivers flow together. In parti-cular, experimental tests were done with and without collar application at three different locations. The results reveal that the scour depth is directly proportional to the discharge ratio, i.e. the ratio of lateral discharge to that in the channel downstream of the confluence, and the densimetric Froude number (Frg). In addition, installation of a collar at RCs can decrease the scour depth up to 100%, thus completely avoiding the scour process. The results also show that by increasing the Frg the optimal installation location for a collar changes and moves towards the river bed level. Using a collar can also reduce the height of the point bar formed downstream of the confluence. The outcomes of the study allow deri-vation of an equation for predicting scour depth when a collar is applied as a countermeasure. The analysis of this equation shows that the estimates are mostly affected by the Frg.  相似文献   

A comparative study of support vector machines and artificial neural networks for predicting precipitation in Iran     

Omid Hamidi  Jalal Poorolajal  Majid Sadeghifar  Hamed Abbasi  Zohreh Maryanaji  Hamid Reza Faridi  Lily Tapak 《Theoretical and Applied Climatology》2015,119(3-4):723-731

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Turbulence Effect on Slope Stability of an Earthen Levee Strengthened by HPTRM Under Overtopping Conditions     

Lin Li  Farshad Amini  Jianhua Wu 《Geotechnical and Geological Engineering》2015,33(1):1-13

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Investigating the Slide Mechanism of Heap Leaching Structures Based on Physical Modeling     

Mehdi Amini  Mohammad Shafiei  Masuod Torabikhah 《Geotechnical and Geological Engineering》2015,33(6):1499-1510

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Prediction of flyrock and backbreak in open pit blasting operation: a neuro-genetic approach   总被引：5，自引：1，他引：4  

M. Monjezi  H. Amini Khoshalan  A. Yazdian Varjani 《Arabian Journal of Geosciences》2012,5(3):441-448

An ideally performed blasting operation enormously influences the mining overall cost. This aim can be achieved by proper prediction and attenuation of flyrock and backbreak. Poor performance of the empirical models has urged the application of new approaches. In this paper, an attempt has been made to develop a new neuro-genetic model for predicting flyrock and backbreak in Sungun copper mine, Iran. Recognition of the optimum model with this method as compared with the classic neural networks is faster and convenient. Genetic algorithm was utilized to optimize neural network parameters. Parameters such as number of neurons in hidden layer, learning rate, and momentum were considered in the model construction. The performance of the model was examined by statistical method in which absolutely higher efficiency of neuro-genetic modeling was proved. Sensitivity analysis showed that the most influential parameters on flyrock are stemming and powder factor, whereas for backbreak, stemming and charge per delay are the most effective parameters.  相似文献   

Major,minor element chemistry and oxygen and hydrogen isotopic compositions of Marun oil‐field brines,SW Iran: Source history and economic potential     

H. Mirnejad  V. Sisakht  H. Mohammadzadeh  A. H. Amini  B. J. Rostron  G. Haghparast 《Geological Journal》2011,46(1):1-9

Cation and anion concentrations and oxygen and hydrogen isotopic ratios of brines in the Asmari Formation (Oligocene–early Miocene) from the Marun oil field of southwest Iran were measured to identify the origin of these brines (e.g. salt dissolution vs. seawater evaporation) as well as the involvement of water–rock reaction processes in their evolution. Marun brines are characterized by having higher concentrations of calcium (11 000–20 000 mg/L), chlorine (120 000–160 000 mg/L) and bromide (600–1000 mg/L) compared to modern seawater. Samples are also enriched in ¹⁸O relative to seawater, fall to the right of the Global Meteoric Water Line and local rain water, and plot close to the halite brine trajectory on the δD versus δ¹⁸O diagram. Geochemical characteristics of Marun brines are inconsistent with a meteoric origin, but instead correspond to residual evaporated seawater modified by water–rock interaction, most significantly dolomitization. In addition, anhydrite precipitation or sulphate reduction appears to be important in chemical modification of the Marun brines, as indicated by lower sulphate contents relative to evaporated seawater. Extensive dolomitization, the presence of anhydrite nodules and high salinity fluid inclusions in the upper parts of the Asmari Formation fit a model whereby the Marun brines likely originated from the seepage reflux of concentrated seawater during the deposition of the overlying Gachsaran Formation evaporites in the Miocene. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

Metal Concentrations in the Coastal Fauna of the Caspian Sea     

Mirzajani  Alireza  Hamidian  Amir Hossein  Hassan  Jalal 《Ocean Science Journal》2021,56(3):256-265

Ocean Science Journal - Metal concentrations were measured in predominant coastal fauna of the Caspian Sea including six macro-invertebrates (Mnemiposis leidyi, Balanus improvisus, Pontogammarus...  相似文献   

Suspended load estimation using L1-fuzzy regression,L2-fuzzy regression and MARS-fuzzy regression models     

Jalal Chachi  Seyed Mahmoud Taheri  Hojat Rezaee Pazhand 《水文科学杂志》2013,58(8):1489-1502

ABSTRACT

The problem of estimation of suspended load carried by a river is an important topic for many water resources projects. Conventional estimation methods are based on the assumption of exact observations. In practice, however, a major source of natural uncertainty is due to imprecise measurements and/or imprecise relationships between variables. In this paper, using the Multivariate Adaptive Regression Splines (MARS) technique, a novel fuzzy regression model for imprecise response and crisp explanatory variables is presented. The investigated fuzzy regression model is applied to forecast suspended load by discharge based on two real-world datasets. The accuracy of the proposed method is compared with two well-known parametric fuzzy regression models, namely, the fuzzy least-absolutes model and the fuzzy least-squares model. The comparison results reveal that the MARS-fuzzy regression model performs better than the other models in suspended load estimation for the particular datasets. This comparison is done based on four goodness-of-fit criteria: the criterion based on similarity measure, the criterion based on absolute errors and the two objective functions of the fuzzy least-absolutes model and the fuzzy least-squares model. The proposed model is general and can be used for modelling natural phenomena whose available observations are reported as imprecise rather than crisp.