水下航行体双空泡相互作用数值模拟研究

高速水下航行体头肩部和表面突起等位置很容易产生空泡,不失一般性,将表面突起结构简化为一定高度的台阶.针对简化的航行体模型,基于数值模拟方法研究了头肩部空泡与台阶处空泡、头肩部空泡与尾空泡2种类型的双空泡相互作用问题.不同的来流攻角下,头肩部空泡与台阶处空泡的作用过程存在区别,可以分为大攻角和小攻角2种类型.当尾空泡内有...     

利用光变曲线估计猎鹰九号火箭末级的旋转状态研究

光度观测是地基观测空间目标的主要手段之一,利用光度信息能够估计空间目标的相关特征信息.为了更好地了解空间目标的旋转状态,选取具有代表性的猎鹰九号火箭末级作为研究对象,由其光变信息研究旋转状态.首先利用云南天文台1.2 m光学望远镜获取猎鹰九号火箭末级的光度数据,再对目标星等进行斜距归一化,得到目标光变信息并分析目标星等...     

藏、汉对比视角下的城市空间环境认知研究——以中国西藏日喀则市为例

以分布式认知理论为基础,采用质性研究法、数量分析法以及GIS空间分析技术,探讨日喀则市藏族、汉族居民对城市空间环境认知的异同性。研究表明,藏族对城市空间环境的认知得分高于汉族对城市空间环境的认知得分。藏族、汉族对城市空间环境的认知水平可分为高、中、低3类。认知空间呈现圈层结构与混合结构模式,可分为藏汉一致性、藏族独立以及汉族独立3种认知空间类型。影响居民对城市空间环境的认知因素有共性因素和差异性因素。景观走廊质量、宜居性、基础设施两项是藏族居民关注的主要影响因素,汉族居民更关注公共服务设施的服务能力以及对当地文化的融入感。     

The Characteristics and Related Problems of the Orbits Around the Earth-Moon Libration Points

Due to the specific dynamics, the probes located at the halo orbits or Lissajous orbits around the Earth-Moon collinear libration point L₁ or L₂ are always studied in the synodic system to understand their trajectories. In fact, they are also orbiting the Earth in a distant Keplerian ellipse. Because of their intrinsic orbital instability, in the orbit prediction the initial errors propagate more prominently than those of the normal orbiting satellites, this requires special attention in the orbit design, maneuver, and control. Despite of all this, they are similar to the normal orbiting satellites in orbit determination and hardly require other special attentions. In this paper, the quantitative results of error propagation under the unstable dynamics, together with the theoretical analysis are presented. The results of precise orbit determination and short-arc orbit predictions are also shown, and compared with the results from the Beijing Aerospace Control Center.     

Estimating areal carbon fixation of intertidal macroalgal community based on composition dynamics and laboratory measurements

The community dynamics and potential carbon ?xation of intertidal macroalgae were investigated monthly from April 2014 to April 2015 in the northwest coast of Yellow Sea. Seasonal variations in biomass and carbon ?xation were presented and showed close relationship with community structure.The carbon ?xation rate ranged from 0.48±0.13 mg C/(g FW ·d) to 4.35±0.12 mg C/(g FW ·d). Sargassum thunbergii, Chondrus ocellatus and Ulva intestinalis were three most in?uential species which contributed27%, 21.9% and 18.5% variation of carbon ?xation rate, respectively. Standing carbon stocks ranged from7.52 g C/m~2 to 41.31 g C/m~2, and estimated carbon stocks varied from 11.77 g C/m 2 to 96.49 g C/m~2. The larger dif ference between estimated and standing carbon stocks implied that more ?xed carbon was exported from the community in summer and autumn than in winter. This study suggested that intertidal macroalgal community could provide a potential function in carbon ?xation of coastal ecosystem.     

南海海洋地磁固定观测站建设初步研究

为填补我国海洋地磁固定观测的空白,支撑科学研究、防灾减灾、海洋资源开发,维护国家的海洋权益和履行我国在南海海域负有的国际责任,急需在南海建设岛礁和海底地磁固定观测站。通过初步分析国外海洋地磁观测站案例、南海岛礁基础设施现状以及海底观测网计划实施情况,认为南海海洋地磁固定观测站建设的条件已经成熟。文中给出了合理空间布局、分步实施、因地制宜及智能化观测的建议。     

Improved Priority‐Flood method for depression filling by redundant calculation optimization in local micro‐relief areas

Depression filling is a critical step in distributed hydrological modeling using digital elevation models (DEMs). The traditional Priority‐Flood (PF) approach is widely used due to its relatively high efficiency when dealing with a small‐sized DEM. However, it seems inadequate and inefficient when dealing with large high‐resolution DEMs. In this work, we examined the relationship between the PF algorithm calculation process and the topographical characteristics of depressions, and found significant redundant calculations in the local micro‐relief areas in the conventional PF algorithm. As such calculations require more time when dealing with large DEMs, we thus propose a new variant of the PF algorithm, wherein redundant points and calculations are recognized and eliminated based on the local micro‐relief water‐flow characteristics of the depression‐filling process. In addition, depressions and flatlands were optimally processed by a quick queue to improve the efficiency of the process. The proposed method was applied and validated in eight case areas using the Shuttle Radar Topography Mission digital elevation model (SRTM‐DEM) with 1 arc‐second resolution. These selected areas have different data sizes. A comparative analysis among the proposed method, the Wang and Liu‐based PF, the improved Barnes‐based PF, the improved Zhou‐based PF, and the Planchon and Darboux (P&D) algorithms was conducted to evaluate the accuracy and efficiency of the proposed algorithm. The results showed that the proposed algorithm is 43.2% (maximum) faster than Wang and Liu's variant of the PF method, with an average of 31.8%. In addition, the proposed algorithm achieved similar performance to the improved Zhou‐based PF algorithm, though our algorithm has the advantage of being simpler. The optimal strategies using the proposed algorithm can be employed in various landforms with high efficiency. The proposed method can also achieve good depression filling, even with large amounts of DEM data.     

SAR image despeckling with a multilayer perceptron neural network

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.     

Ingestion of <Emphasis Type="Italic">Brachionus plicatilis</Emphasis> under different microalgae conditions

The effects of four microalgae,Chlorella vulgaris,Platymonas helgolandicavar,Isochrysis galbana,and Nitzschia closterium on the grazing and filtering rates of the marine rotifer,Brachionus plicatilis,were evaluated under laboratory conditions.The grazing rates in separate cultures of the four microalga were as follows:C.vulgaris > P.helgolandicavar > I.galbana > N.closterium.However,the filtering rates occurred in the following order:P.helgolandicavar > N.closterium > C.vulgaris > I.galbana.A mixed diets ex...     

HPABM: A Hierarchical Parallel Simulation Framework for Spatially-explicit Agent-based Models

A Hierarchical Parallel simulation framework for spatially-explicit Agent-Based Models (HPABM) is developed to enable computationally intensive agent-based models for the investigation of large-scale geospatial problems. HPABM allows for the utilization of high-performance and parallel computing resources to address computational challenges in agent-based models. Within HPABM, an agent-based model is decomposed into a set of sub-models that function as computational units for parallel computing. Each sub-model is comprised of a sub-set of agents and their spatially-explicit environments. Sub-models are aggregated into a group of super-models that represent computing tasks. HPABM based on the design of super- and sub-models leads to the loose coupling of agent-based models and underlying parallel computing architectures. The utility of HPABM in enabling the development of parallel agent-based models was examined in a case study. Results of computational experiments indicate that HPABM is scalable for developing large-scale agent-based models and, thus, demonstrates efficient support for enhancing the capability of agent-based modeling for large-scale geospatial simulation.