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11.
Ali Moamen Abdelmaksoud Ahmed Essa M. A. Abdelhady A. Darwish M. 《Natural Resources Research》2020,29(4):2575-2597
Natural Resources Research - Two main reservoirs are producing in Komombo Basin: the first one belongs to the C Member of the Six Hills Formation, and the second belongs to the Albian/Cenomanian... 相似文献
12.
Yu Zhi Shi Xiuzhi Zhou Jian Chen Xin Miao Xiaohu Teng Bing Ipangelwa Timo 《Natural Resources Research》2020,29(2):843-865
Natural Resources Research - A large ore loss and dilution can be expected when using a pre-blast ore boundary for shovel guidance because of the movement and re-distribution of ore in the muck... 相似文献
13.
Ali Moamen Abdelhady A. Abdelmaksoud Ahmed Darwish M. Essa M. A. 《Natural Resources Research》2020,29(2):1259-1281
Natural Resources Research - The Albian/Cenomanian reservoir is one of the two main reservoirs composing the petroleum system in the Komombo Basin. However, these reservoirs have not previously... 相似文献
14.
Natural Resources Research - The northwest of Iran is considered as a promising geothermal zone owing to its geographical properties, tectonic features, and thermal activities, particularly in... 相似文献
15.
A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted. 相似文献
16.
Electrostatic solitary waves and double layers (DLs) formed by the coupled ion acoustic (IA) and drift waves have been investigated in non-uniform plasma using \(q\)-nonextensive distribution function for the electrons and assuming ions to be cold \(T_{i}< T_{e}\). It is found that both compressive and rarefactive nonlinear structures (solitary waves and DLs) are possible in such a system. The steeper gradients are supportive for compressive solitary (and double layers) and destructive for rarefactive ones. The \(q\)-nonextensivity parameter \(q\) and the magnitudes of gradient scale lengths of density and temperature have significant effects on the amplitude of the double layers (and double layers) as well as on the speed of these structures. This theoretical model is general which has been applied here to the \(F\)-region ionosphere for illustration. 相似文献
17.
Microbial communities in different gastrointestinal regions(stomach, foregut, midgut, and hindgut) of the northern snakehead C hanna argus(Cantor, 1842) were compared by polymerase chain reaction and partial 16 S r DNA sequencing. A total of 194, 140, 212, and 122 OTUs were detected in the stomach, foregut, midgut, and hindgut, respectively. Significant dif ferences were found in the Sobs, ACE, Shannon, and Simpson indices among samples(P 0.05). The gastrointestinal microbial community of C. argus consisted predominantly of Proteobacteria with either H alomonas, Shewanella, Plesiomonas, or Sphingomonas. Fusobacteria, Firmicutes, and Bacteroidetes also existed in the gastrointestinal tracts. However, significant diff erences were found in the compositions of microbial community among the four regions( P 0.05). Cyanobacteria and Spirochetes were significantly higher in the midgut and hindgut( P 0.05). Fusobacteria and Firmicutes were dominant in the hindgut and foregut, respectively(P 0.05). Proteobacteria was the lowest in the hindgut( P 0.05). At genus level, C etobacterium and Plesiomonas were significantly higher in the hindgut than in the other three samples( P 0.05). Clostridium and Prevotella were the highest in the midgut(P 0.05). Halomonas, Shewanella, and S phingomonas were the highest in the foregut( P 0.05). Paracoccus and Vibrio were the highest in the stomach. Several genera were only detected in certain regions, as follows: stomach, P aracoccus and Vibrio; foregut, Halomonas, Shewanella, and Sphingomonas; midgut, Clostridium and Prevotella; and hindgut, C etobacterium and Plesiomonas( P 0.05). At the species level, A cinetobacter rhizosphaerae was only detected in the stomach. P revotella copri and Clostridium perfring were not detected in the foregut and midgut, respectively, whereas Prevotella copri and Faecalibacterium pra were not detected in the hindgut. These findings provide valuable information on the microbial community in each gastrointestinal region of C. argus. Moreover, this study indicated that microbial community was not only related to rearing environment but also to the physico-chemical characteristics of each gastrointestinal region. 相似文献
18.
Understanding coastal wetland hydrology with a new regional‐scale,process‐based hydrological model 下载免费PDF全文
Yu Zhang Wenhong Li Ge Sun Guofang Miao Asko Noormets Ryan Emanuel John S. King 《水文研究》2018,32(20):3158-3173
Coastal wetlands represent an ecotone between ocean and terrestrial ecosystems, providing important services, including flood mitigation, fresh water supply, erosion control, carbon sequestration, and wildlife habitat. The environmental setting of a wetland and the hydrological connectivity between a wetland and adjacent terrestrial and aquatic systems together determine wetland hydrology. Yet little is known about regional‐scale hydrological interactions among uplands, coastal wetlands, and coastal processes, such as tides, sea level rise, and saltwater intrusion, which together control the dynamics of wetland hydrology. This study presents a new regional‐scale, physically based, distributed wetland hydrological model, PIHM‐Wetland, which integrates the surface and subsurface hydrology with coastal processes and accounts for the influence of wetland inundation on energy budgets and evapotranspiration (ET). The model was validated using in situ hydro‐meteorological measurements and Moderate Resolution Imaging Spectroradiometer (MODIS) ET data for a forested and herbaceous wetland in North Carolina, USA, which confirmed that the model accurately represents the major wetland hydrological behaviours. Modelling results indicate that topographic gradient is a primary control of groundwater flow direction in adjacent uplands. However, seasonal climate patterns become the dominant control of groundwater flow at lower coastal plain and land–ocean interface. We found that coastal processes largely influence groundwater table (GWT) dynamics in the coastal zone, 300 to 800 m from the coastline in our study area. Among all the coastal processes, tides are the dominant control on GWT variation. Because of inundation, forested and herbaceous wetlands absorb an additional 6% and 10%, respectively, of shortwave radiation annually, resulting in a significant increase in ET. Inundation alters ET partitioning through canopy evaporation, transpiration, and soil evaporation, the effect of which is stronger in cool seasons than in warm seasons. The PIHM‐Wetland model provides a new tool that improves the understanding of wetland hydrological processes on a regional scale. Insights from this modelling study provide benchmarks for future research on the effects of sea level rise and climate change on coastal wetland functions and services. 相似文献
19.
J. Ignacio López-Moreno Leena Leppänen Bartłomiej Luks Ladislav Holko Ghislain Picard Alba Sanmiguel-Vallelado Esteban Alonso-González David C. Finger Ali N. Arslan Katalin Gillemot Aynur Sensoy Arda Sorman M. Cansaran Ertaş Steven R. Fassnacht Charles Fierz Christoph Marty 《水文研究》2020,34(14):3120-3133
Manually collected snow data are often considered as ground truth for many applications such as climatological or hydrological studies. However, there are many sources of uncertainty that are not quantified in detail. For the determination of water equivalent of snow cover (SWE), different snow core samplers and scales are used, but they are all based on the same measurement principle. We conducted two field campaigns with 9 samplers commonly used in observational measurements and research in Europe and northern America to better quantify uncertainties when measuring depth, density and SWE with core samplers. During the first campaign, as a first approach to distinguish snow variability measured at the plot and at the point scale, repeated measurements were taken along two 20 m long snow pits. The results revealed a much higher variability of SWE at the plot scale (resulting from both natural variability and instrumental bias) compared to repeated measurements at the same spot (resulting mostly from error induced by observers or very small scale variability of snow depth). The exceptionally homogeneous snowpack found in the second campaign permitted to almost neglect the natural variability of the snowpack properties and focus on the separation between instrumental bias and error induced by observers. Reported uncertainties refer to a shallow, homogeneous tundra-taiga snowpack less than 1 m deep (loose, mostly recrystallised snow and no wind impact). Under such measurement conditions, the uncertainty in bulk snow density estimation is about 5% for an individual instrument and is close to 10% among different instruments. Results confirmed that instrumental bias exceeded both the natural variability and the error induced by observers, even in the case when observers were not familiar with a given snow core sampler. 相似文献
20.
针对国内海上风电基础设计没有统一的规范及标准,为提升海上风电基础设计建设的水平,通过对东南沿海某海域海上风电基础的设计进行了有限元计算分析论证,验证了群桩高承台结构设计方案的设计方法和设计参数。分析结果表明该设计的最大应力主要发生在塔筒底座与承台接触部位及钢管桩与承台连接段,应在连接部位加强措施处理;基础竖直位移较小,水平位移相对较大;分界部位应力较集中,刚度不能顺畅过渡,可考虑填充碎石土等方法加强。本研究对海上风电基础设计技术的研究与探索,可为将来制定中国海上风电行业标准提供可靠的依据,对中国未来大批量的海上风电能源的开发有着重要意义。 相似文献