List of forthcoming papers     

A. K. Singh  Mohammad Yusuf 《Astrophysics and Space Science》1990,167(2):351-341

List of forthcoming papers  相似文献   

Exploring the applications of 3D proximity analysis in a 3D digital cadastre     

Saeid Emamgholian  Mohammad Taleai  Davood Shojaei 《地球空间信息科学学报》2021,24(2):201-214

Increasing population in urban areas and limitations of suitable lands for developing houses and urban infrastructure have led to the vertical development in cities. However, these developments are managed by a cadastral system which is mainly two-dimensional and cannot efficiently represent Rights, Restrictions, and Responsibilities (RRRs) in complex scenarios. In fact, a three-dimensional cadastre is required for efficiently registering and representing RRRs. In this paper, a 3D proximity analysis was proposed and implemented to determine RRRs and associated easement rights in non-topology-based data structures. This method can be used to investigate the surrounding spaces of a subject apartment unit or storage in a high-rise. The performance of the developed method was evaluated in a large complex high-rise in Tehran, Iran. The results confirmed that the proposed method can correctly identify the neighbor spaces in complex scenarios.  相似文献   

Efficacy of a multi-metric fish index as an analysis tool for the transitional fish component of the Water Framework Directive     

Coates S  Waugh A  Anwar A  Robson M 《Marine pollution bulletin》2007,55(1-6):225-240

The WFD has introduced an international commitment to assess the ecological status of transitional waters (TWs), within which fish communities are a key biological monitoring component. The Transitional Fish Classification Index (TFCI) outlined in this paper uses 10 ecological measures to analyse fish populations caught from various ecological niches using a variety of gear types within the Thames estuary. These reach and method-specific communities are then compared to a reference population created from a 'healthy' population from TWs of a similar type. The results indicate a progressive downstream increase the quality of fish communities, consistent with previous work; variation between methods can be accounted for by gear selectivity. Overall, the TFCI is an effective communication tool for converting ecological information into an easily understood format for managers, policy makers and the general public.  相似文献   

Prediction of Land Subsidence Under Cyclic Pumping Based on Laboratory and Numerical Simulations     

Ahad Ouria  Mohammad M. Toufigh 《Geotechnical and Geological Engineering》2010,28(2):165-175

In this study subsidence due to groundwater withdrawal was investigated. Kerman Province in Iran is struggling with land subsidence problem due to extensive groundwater withdrawal mainly for farming. The rate and type of groundwater withdrawal has very important impact on settlement rate. In this research, effective parameters on land subsidence caused by groundwater withdrawal were determined by laboratory tests. Sampling had done up to depth of 300 m mainly with remolded specimens from Shams-abad, Nouq plain in Kerman province. Similar to the field preconsolidation pressure was applied on specimens in the laboratory. Rate of applied stress on prepared specimens was similar to effect of oscillation of groundwater level. In order to model the actual soil behavior in the laboratory, one-dimensional consolidation device (odometer) was adopted for testing. In these tests, the effect of loading caused by seasonal oscillation of groundwater table is considered by means of cyclic loading in the testing which has great effect on rate of settlements. The results of tests show that when the water table level periodically increases and decreases the amount of settlement decrease, comparing with the case when the groundwater table drop to a constant level. In order to predict the further effects of groundwater level oscillation and actual field condition on land subsidence, a finite element model based on Biots’ three-dimensional consolidation theory was developed. After calibration of finite element model with laboratory tests, this model was used for prediction the effect of groundwater level oscillation on actual field conditions.  相似文献   

Impact of future climate change on wheat production in relation to plant-available water capacity in a semiaridenvironment     

Yanmin Yang  De Li Liu  Muhuddin Rajin Anwar  Heping Zuo  Yonghui Yang 《Theoretical and Applied Climatology》2014,115(3-4):391-410

Conceptions encompassing climate change are irreversible rise of atmospheric carbon dioxide (CO₂) concentration, increased temperature, and changes in rainfall both in spatial- and temporal-scales worldwide. This will have a major impact on wheat production, particularly if crops are frequently exposed to a sequence, frequency, and intensity of specific weather events like high temperature during growth period. However, the process of wheat response to climate change is complex and compounded by interactions among atmospheric CO₂ concentration_, climate variables, soil, nutrition, and agronomic management. In this study, we use the Agricultural Production Systems sIMulator (APSIM)-wheat model, driven by statistically downscaled climate projections of 18 global circulation models (GCMs) under the 2007 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 CO₂ emission scenario to examine impact on future wheat yields across key wheat growing regions considering different soil types in New South Wales (NSW) of Australia. The response of wheat yield, yield components, and phenology vary across sites and soil types, but yield is closely related to plant available water capacity (PAWC). Results show a decreasing yield trend during the period of 2021–2040 compared to the baseline period of 1961–1990. Across different wheat-growing regions in NSW, grain yield difference in the future period (2021–2040) over the baseline (1961–1990) varies from +3.4 to ?14.7 %, and in most sites, grain number is decreased, while grain size is increased in future climate. Reduction of wheat yield is mainly due to shorter growth duration, where average flowering and maturing time are advanced by an average of 11 and 12 days, respectively. In general, larger negative impacts of climate change are exhibited in those sites with higher PAWC. Current wheat cultivars with shorter growing season properties are viable in the future climate, but breading for early sowing wheat varieties with longer growing duration will be a desirable adaptation strategy for mitigating the impact of changing climate on wheat yield.  相似文献   

Geochemical Characteristics,Origin, and Evolution of Ore‐Forming Fluids of the Khut Copper Skarn Deposit,West of Yazd in Central Iran     

Azam Zahedi  Mohammad Boomeri  Kazuo Nakashima  Mohammad Ali Mackizadeh  Masao Ban  David R. Lentz 《Resource Geology》2014,64(3):209-232

The Khut copper skarn deposit is located at about 50 km northwest of Taft City in Yazd province in the middle part of the Urumieh‐Dokhtar magmatic arc. Intrusion of granitoid of Oligocene–Miocene age into carbonate rocks of the Triassic Nayband Formation led to the formation of marble and a calcic skarn. The marble contains high grade Cu mineralization that occurs mainly as open space filling and replacement. Cu‐rich sulfide samples from the mineralized marble are also anomalous in Au, Zn, and Pb. In contrast, the calcic skarn is only weakly anomalous in Cu and W. The calcic skarn is divided into garnet skarn and garnet–pyroxene skarn zones. Paragenetic relationships and microthermometric data from fluid inclusions in garnet and calcite indicate that the compositional evolution of skarn minerals occurred in three main stages as follows. (i) The early prograde stage, which is characterized by Mg‐rich hedenbergite (Hd_53.7Di_42.3–Hd_86.1Di_9.5) with Al‐bearing andradite (69.8–99.5 mol% andradite). The temperature in the early prograde skarn varies from 400 to 500°C at 500 bar. (ii) The late prograde stage is manifested by almost pure andradite (96.2–98.4 mol% andradite). Based on the fluid inclusion data from garnet, fluid temperature and salinity in this stage is estimated to vary from 267 to 361°C and from 10.1 to 21.1 wt% NaCl equivalent, respectively. Pyrrhotite precipitation started during this stage. (iii) The retrograde stage occurs in an exoskarn, which consists of an assemblage of ferro‐actinolite, quartz, calcite, epidote, chlorite, sphalerite, pyrite, and chalcopyrite that partially replaces earlier mineral assemblages under hydrostatic conditions during fracturing of the early skarn. Fluids in calcite yielded lower temperatures (T < 260°C) and fluid salinity declined to ～8 wt% NaCl equivalent. The last stage mineralization in the deposit is supergene weathering/alteration represented by the formation of iron hydroxide, Cu‐carbonate, clay minerals, and calcite. Sulfur isotope data of chalcopyrite (δ³⁴S of +1.4 to +5.2‰) show an igneous sulfur source. Mineralogy and mineral compositions of the prograde assemblage of the Khut skarn are consistent with deposition under intermediately oxidized and slightly lower fS₂ conditions at shallow crustal levels compared with those of other typical Fe‐bearing Cu–Au skarn systems.  相似文献   

Mixed precision parallel preconditioner and linear solver for compositional reservoir simulation     

Ali Reza Khaz’ali  Mohammad Reza Rasaei  Jamshid Moghadasi 《Computational Geosciences》2014,18(5):729-746

Reservoir simulation role in value creation and strategic management decisions cannot be over emphasized. Simulation of complex challenging reservoirs with millions of grid blocks especially in compositional mode is very time-consuming even with fast modern computers. On the other hand, high price of cluster supercomputers prevents them for being commonly used for fast simulation of such reservoirs. In recent years, the development of many-core processors like cell processors, DSPs, and graphical processing units (GPUs) has provided a very cost-effective hardware platform for fast computational operations. However, programming for such processors is much more difficult than conventional CPUs, and new parallel algorithm design and special parallel implementation methods are needed. Using the computational power of CPUs, GPUs, and/or any other processing unit, Open Computing Language (OpenCL) provides a framework for programming for heterogeneous platforms. In this paper, OpenCL is used to employ the computational power of a GPU to build a preconditioner and solve the linear system arising from compositional formulation of multiphase flow in porous media. The proposed parallel preconditioner is proved to be quite effective, even in heterogeneous porous media. Using data-parallel modules on GPU, the preconditioner/solver runtime reduced at least 1 order of magnitude compared to their serial implementation on CPU.  相似文献   

Optimal water and waste load allocation in reservoir–river systems: a case study     

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   

Shigar valley gemstones,their chemical composition and origin,Skardu, Gilgit-Baltistan,Pakistan     

Muhammad Hassan Agheem  Mohammad Tahir Shah  Tahseenullah Khan  Mamoru Murata  Muhammad Arif  Humaira Dars 《Arabian Journal of Geosciences》2014,7(9):3801-3814

A variety of gemstones is being mined in the Shigar valley, Skardu, Pakistan. These include beryl (goshenite and aquamarine), tourmaline (schorl), garnet (almandine–spessartine), apatite, topaz, fluorite, zoisite, clinozoisite, and axinite, mostly occurring in complex or zoned pegmatites and metamorphic rocks. These have been analyzed using electron probe micro-analyzer and X-ray diffractometer. The mineral chemistry of each gemstone is similar to its respective typical gemstone variety with homogenous chemical composition. Field and chemical characteristics suggest that beryl, tourmaline, garnet, apatite, topaz, and fluorite are occurring in zoned pegmatites which are largely formed by magmatic hydrothermal fluids in the cavities and vugs within the intermediate zone. However, zoisite, clinozoisite, and axinite may have a metamorphic and/or metasomatic origin.  相似文献   

Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation   总被引：2，自引：0，他引：2  

Ebrahim Ghasemi  Hasel Amini  Mohammad Ataei  Reza Khalokakaei 《Arabian Journal of Geosciences》2014,7(1):193-202

Flyrock arising from blasting operations is one of the crucial and complex problems in mining industry and its prediction plays an important role in the minimization of related hazards. In past years, various empirical methods were developed for the prediction of flyrock distance using statistical analysis techniques, which have very low predictive capacity. Artificial intelligence (AI) techniques are now being used as alternate statistical techniques. In this paper, two predictive models were developed by using AI techniques to predict flyrock distance in Sungun copper mine of Iran. One of the models employed artificial neural network (ANN), and another, fuzzy logic. The results showed that both models were useful and efficient whereas the fuzzy model exhibited high performance than ANN model for predicting flyrock distance. The performance of the models showed that the AI is a good tool for minimizing the uncertainties in the blasting operations.  相似文献