Reduced transition probabilities for 4~He radiative capture reactions at astrophysical energies     

Hossein Sadeghi  Reza Ghasemi 《中国天文和天体物理学报》2014,(3):367-372

The reduced transition probabilities from an electric quadrupole B(E2) and reduced transition probabilities from a magnetic dipole B(M1) between the ground state and the first excited state have been calculated for the3He(α,γ)7Be,8Be(α,γ)12C and12C(α,γ)16O radiative capture reactions with the M3Y potential.These reactions are important in stellar evolution.The calculated B(M1) and B(E2) for7Be nuclei are found to be 1.082×10-3e2fm2and 1.921 e2fm4from transitions 3/2-to 1/2-,respectively.The obtained values for reduced transition probabilities B(E2) for the12C and16O nuclei from transitions 0+to 2+are 12.54 e2fm4and 14.18 e2fm4,respectively.The results are in satisfactory agreement with available experimental data.  相似文献   

Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran   总被引：2，自引：1，他引：1  

Hossien Ahani  Mehrzad Kherad  Mohammad Reza Kousari  Lieke van Roosmalen  Ramin Aryanfar  Seyyed Mashaallah Hosseini 《Theoretical and Applied Climatology》2013,112(3-4):553-564

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955–2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann–Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.  相似文献   

Development of Rock Engineering Systems-Based Models for Flyrock Risk Analysis and Prediction of Flyrock Distance in Surface Blasting   总被引：2，自引：1，他引：1  

Farhad Faramarzi  Hamid Mansouri  Mohammad Ali Ebrahimi Farsangi 《Rock Mechanics and Rock Engineering》2014,47(4):1291-1306

The environmental effects of blasting must be controlled in order to comply with regulatory limits. Because of safety concerns and risk of damage to infrastructures, equipment, and property, and also having a good fragmentation, flyrock control is crucial in blasting operations. If measures to decrease flyrock are taken, then the flyrock distance would be limited, and, in return, the risk of damage can be reduced or eliminated. This paper deals with modeling the level of risk associated with flyrock and, also, flyrock distance prediction based on the rock engineering systems (RES) methodology. In the proposed models, 13 effective parameters on flyrock due to blasting are considered as inputs, and the flyrock distance and associated level of risks as outputs. In selecting input data, the simplicity of measuring input data was taken into account as well. The data for 47 blasts, carried out at the Sungun copper mine, western Iran, were used to predict the level of risk and flyrock distance corresponding to each blast. The obtained results showed that, for the 47 blasts carried out at the Sungun copper mine, the level of estimated risks are mostly in accordance with the measured flyrock distances. Furthermore, a comparison was made between the results of the flyrock distance predictive RES-based model, the multivariate regression analysis model (MVRM), and, also, the dimensional analysis model. For the RES-based model, R ² and root mean square error (RMSE) are equal to 0.86 and 10.01, respectively, whereas for the MVRM and dimensional analysis, R ² and RMSE are equal to (0.84 and 12.20) and (0.76 and 13.75), respectively. These achievements confirm the better performance of the RES-based model over the other proposed models.  相似文献   

Characterisation of the Sarcheshmeh copper mine tailings,Kerman province,southeast of Iran     

Sajjad Jannesar Malakooti  Seyed Ziaedin Shafaei Tonkaboni  Mohammad Noaparast  Faramarz Doulati Ardejani  Reza Naseh 《Environmental Earth Sciences》2014,71(5):2267-2291

Mineral processing operation at the Sarcheshmeh porphyry copper mine has produced huge quantities of tailings materials containing sulphide minerals in particular pyrite. These tailings materials were geochemically and mineralogically characterised to assess pyrite and chalcopyrite oxidation, acid mine drainage generation, and trace element mobility to lead development of a proper remediation plan. Five vertical trenches up to 4.2 m deep were excavated from the tailings surface, and 70 solid samples were taken in 0.3 m intervals. The samples were first mineralogically analysed. Pyrite was the main sulphide mineral found in the tailings. The gangue minerals include quartz ± muscovite–illite ± chlorite ± albite ± orthoclase ± halite. The samples were geochemically analysed for total concentrations of 62 elements, paste pH, SO₄ ^2?, CO₃ ^2?, and HCO₃ ^?. The maximum concentrations of SO₄ ^2? (1,300, 1,170, 1,852, 1,960 and 837 mg/L) were observed at a depth of 0.9 m in profiles A, B, C, D and E, respectively. The tailings have a high acid-producing potential and low acid-neutralising potential (pyrite 4–6 wt %, calcite 1 wt %). Fe₂(SO₄)₃, CuSO₄, MgSO₄ and MnSO₄ were the dominant secondary sulphate minerals in the tailings. The lowest pH values (2.9, 3 and 3) were measured at a depth of 0.3 m in the profiles A, B and C, 3.9 at a depth of 0.6 m in the profile D and 3 at a depth of 0.9 m in the profile E. The upper portions of the profiles C (1.8 m) and D (2.1 m) were moderately oxidised, while oxidation in the profiles A, B and E did not extend more than 1.2, 1.2 and 1.5 m beneath the tailings surface. Zn, Pb, Rb, U, Hf, Nd, Zr and Ga show almost a constant trend with depth. Cd, Sr, Th, La and Ce increased with increasing depth of the tailings materials while, Co, V, Ti, Cr, Cu, As, Mn, Ag, Mo and Ni exhibit initially a decreasing trend from tailings surface to the depths that vary between 0.9 and 1.2. They then remained constant with the depth. The results show pyrite and chalcopyrite oxidation at surface layers of the tailings and subsequent leaching of the oxidation products and trace elements by infiltrated atmospheric precipitation.  相似文献   

Petrography and geochemistry of Silurian Niur sandstones,Derenjal Mountains,East Central Iran: implications for tectonic setting,provenance and weathering     

Zohreh Nowrouzi  Reza Moussavi-Harami  Asadollah Mahboubi  Mohammad Hossein Mahmudy Gharaie  Farzin Ghaemi 《Arabian Journal of Geosciences》2014,7(7):2793-2813

Petrographical and geochemical studies of Silurian Niur sandstones, Derenjal Mountains, Central Iran, were carried out to infer their provenance and tectonic setting. Modal analysis data of 37 medium sand size and well-sorted samples revealed that most quartz is composed of monocrystalline grains with straight to slightly undulos extinction and about 3 % polycrystalline quartz has inclusions, such as rutile needles. The sandstones are classified as quartzarenite, sublitharenite, and subarkose types based on framework composition and geochemistry. Petrographic studies reveal that these sandstones contain quartz, feldspars, and fragments of sedimentary rocks. The detrital modes of these sandstones indicate that they were derived from recycled orogen and stable cratonic source. Major and trace element contents of them are generally depleted (except SiO₂) relative to upper continental crust which is mainly due to the presence of quartz and absence of Al-bearing minerals. Modal composition (e.g., quartz, feldspar, and lithic fragments) and discrimination diagrams based on major elements, trace elements (Ti, La, Th, Sc, and Zr), and also such ratios as La/Sc, Th/Sc, La/Co, and Th/Co, in sandstones suggest a felsic igneous source rock and quartzose polycyclic sedimentary provenance in a passive continental margin setting. Furthermore, high Zr/Sc values in these sandstones are considered as a sign of recycling. We indicated paleo-weathering conditions by modal compositions, the CIA index and Al₂O₃?+?K₂O?+?Na₂O% vs. SiO₂% bivariate for these sandstones. Based on these results, although recycling is important to increase the maturity of the Niur sandstones, humid climate conditions in the source area have played a decisive role.  相似文献   

Volume,gravitational potential energy reduction,and regional centroid position change in the wake of landslides triggered by the 14 April 2010 Yushu earthquake of China     

Chong Xu  Xiwei Xu  Hamid Reza Pourghasemi  Biswajeet Pradhan  Javed Iqbal 《Arabian Journal of Geosciences》2014,7(6):2129-2138

In recent years, earthquake-triggered landslides have attracted much attention in the scientific community as a main form of seismic ground response. However, little work has been performed concerning the volume and gravitational potential energy reduction of earthquake-triggered landslides and their severe effect on landscape change. This paper presents a quantitative study on the volume, gravitational potential energy reduction, and change in landscape related to landslides triggered by the 14 April 2010 Yushu earthquake. At least 2,036 landslides were triggered by the earthquake. A total landslide scar area of 1.194 km² was delineated from the visual interpretation of aerial photographs and satellite images and was supported by selected field checking. In this paper, we focus on possible answers to the following five questions: (1) What is the total volume of the 2,036 landslides triggered by the earthquake, and what is the average landslide erosion thickness in the earthquake-stricken area? (2) What are the elevations of all landslide materials in relation to pre- and post-landsliding? (3) How much was the gravitational potential energy reduced due to the sliding of these landslide materials? (4) What is the average elevation change caused by these landslides in the study area? (5) What is the vertical change of the regional centroid position above sea level, as induced by these landslides? It is concluded that the total volume of the 2,036 landslides is 2.9399?×?10⁶ m³. The landslide erosion thickness throughout the study area is 2.02 mm. The materials of these landslides moved from an elevation of 4,145.243 to 4,104.697 m, resulting in a decreased distance of 40.546 m. The gravitational potential energy reduction related to the landslides triggered by the earthquake was 2.9213?×?10¹² J. The average regional elevation of the study area is 4,427.160 m, a value consistent with the assumption that the accumulated materials were remained in situ. This value changes from 4,427.160 to 4,427.158 m with all landslide materials moved out of the study area, resulting in a reduction in elevation of 2 mm. Based on the assumption that all landslide materials moved out of the study area, the elevations of the centroid of the study area’s crust changed from 2,222.45967 to 2,222.45867 m, which means the centroid value decreased by 1 mm. This value is 0.001 mm when assuming that the materials were remained in situ, which is almost negligible, compared with the situation of “all landslide materials moved out of the study area.”  相似文献   

Investigating 2-D MT inversion codes using real field data   总被引：1，自引：0，他引：1  

Reza Ghaedrahmati  Ali Moradzadeh  Nader Fathianpour  Seong Kon Lee 《Arabian Journal of Geosciences》2014,7(6):2315-2328

There are currently a significant number of two-dimensional (2-D) and three-dimensional (3-D) inversion codes available for magnetotelluric (MT) data. Through various 2-D inversion algorithms suggested so far, the classical Occam's inversion, the data space Occam's inversion, the nonlinear conjugate gradient (NLCG) method, and the Gauss–Newton (GN) method are fundamental driving methods to find optimum earth models, and OCCAM, DASOCC, NLCG, and MT2DInvMatlab are possible candidates one can find in the public domain that implement these algorithms for 2-D MT inversions, respectively. In this study, we investigate the pros and cons (strength and weakness) of these codes to help one use them efficiently in practical works and, as an introductory guide, further develop (sophisticate or extend) them, especially for the 3-D case. To achieve this goal, we applied each one of the four aforementioned codes on a profile of real MT field dataset. Then, further investigations have been done by performing several inversion tests to see how each code can find the appropriate model to reconstruct the subsurface resistivity structure. Numerical experiments show that the two parameters, regularization and target misfit, in addition to the main criteria of inversion (such as the forward and the sensitivities calculation method, and the type of inversion algorithm), are very important to produce the expected model in inversion. The regularization parameter that acts to trade off between model norm and data misfit can affect the inversion process in terms of both the computational efficiency and the accuracy of the obtained model. Also, lack of insufficient precision to choose the target misfit can lead the inversion to produce and reach an incorrect model.  相似文献   

A new rating system approach for risk analysis of rock slopes     

Nassirzadeh Goorchi  Reza  Amini  Mehdi  Memarian  Hossein 《Natural Hazards》2017,91(1):75-102

In this paper, an approach is presented to analyze the stability risk of rock slopes based on a new rating system. Three factors are used to estimate the risk level of rock slopes: (1) failure probability, (2) element at risk rating, and (3) vulnerability rating. Element at risk and vulnerability ratings are both given a range from 0 to 10, and the probability of failure is varied between 0 and 1, so the risk rating ranges between 0 and 100. This risk rating can be used to determine both the quantitative and qualitative risk levels of slopes at the same time. The method is tested on the western sector of the slopes facing Songun copper plant phase III, Iran, to clarify its procedures and assess its validity. Deterministic kinematic analyses showed that the slope has a potential for circular failure. Risk assessments revealed that the risk levels of the slope in both static and pseudo-static conditions are “very low” and “high,” respectively.

  相似文献   

Prediction of longitudinal dispersion coefficient in natural rivers using a cluster-based Bayesian network   总被引：1，自引：0，他引：1  

Mohamad Javad Alizadeh  Hosein Shahheydari  Mohammad Reza Kavianpour  Hamid Shamloo  Reza Barati 《Environmental Earth Sciences》2017,76(2):86

The longitudinal dispersion coefficient is a key element in determining the distribution and transmission of pollution, especially when cross-sectional mixing is completed. However, the existing predictive techniques for this purpose exhibit great amounts of uncertainty. The main objective of this study is to present a more accurate model for predicting longitudinal dispersion coefficient in natural rivers and streams. Bayesian network (BN) approach was considered in the modeling procedure. Two forms of input variables including dimensional and dimensionless parameters were examined to find the best model structure. In order to increase the performance of the model, the clustering method as a preprocessing data technique was applied to categorize the data in separate groups with similar characteristics. An expansive data set consisting of 149 field measurements was used for training and testing steps of the developed models. Three performance evaluation criteria were adopted for comparison of the results of the different models. Comparison of the present results with the artificial neural network (ANN) model and also well-known existing equations showed the efficiency of the present model. The performance of dimensionless BN model 30% is more than dimensional ones in terms of the root mean square error. The accuracy criterion was increased from 70 to 83% by performing clustering analysis on the BN model. The BN-cluster model 43% is more accurate than ANN model in terms of the accuracy criterion. The results indicate that the BN-cluster model give 16% better results than the best available considered model in terms of the accuracy criterion. The developed model provides a suitable approach for predicting pollutant transport in natural rivers.  相似文献   

Applying different scenarios for landslide spatial modeling using computational intelligence methods     

Alireza Arabameri  Hamid Reza Pourghasemi  Mojtaba Yamani 《Environmental Earth Sciences》2017,76(24):832

Landslides every year impose extensive damages to human beings in various parts of the world; therefore, identifying prone areas to landslides for preventive measures is essential. The main purpose of this research is applying different scenarios for landslide susceptibility mapping by means of combination of bivariate statistical (frequency ratio) and computational intelligence methods (random forest and support vector machine) in landslide polygon and point formats. For this purpose, in the first step, a total of 294 landslide locations were determined from various sources such as aerial photographs, satellite images, and field surveys. Landslide inventory was randomly split into a testing dataset 70% (206 landslide locations) for training the different scenarios, and the remaining 30% (88 landslides locations) was used for validation purposes. To providing landslide susceptibility maps, 13 conditioning factors including altitude, slope angle, plan curvature, slope aspect, topographic wetness index, lithology, land use/land cover, distance from rivers, drainage density, distance from fault, distance from roads, convergence index, and annual rainfall are used. Tolerance and the variance inflation factor indices were used for considering multi-collinearity of conditioning factors. Results indicated that the smallest tolerance and highest variance inflation factor were 0.31 and 3.20, respectively. Subsequently, spatial relationship between classes of each landslide conditioning factor and landslides was obtained by frequency ratio (FR) model. Also, importance of the mentioned factors was obtained by random forest (RF) as a machine learning technique. The results showed that according to mean decrease accuracy, factors of altitude, aspect, drainage density, and distance from rivers had the greatest effect on the occurrence of landslide in the study area. Finally, the landslide susceptibility maps were produced by ten scenarios according to different ensembles. The receiver operating characteristics, including the area under the curve (AUC), were used to assess the accuracy of the models. Results of validation of scenarios showed that AUC was varying from 0.668 to 0.749. Also, FR and seed cell area index indicators show a high correlation between the susceptibility classes with the landslide pixels and field observations in all scenarios except scenarios 10_RF and 10_SVM. The results of this study can be used for landslides management and mitigation and development activities such as construction of settlements and infrastructure in the future.  相似文献