Parallelization of the flow-path network model using a particle-set strategy

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS).     

基于圆柱多段拟合的隧道中轴线提取方法研究

提出基于圆柱多段拟合的隧道中轴线提取方法。首先对隧道点云数据进行预处理，并将点云按隧道走向分成不同区段；然后对各区段依据轴线与表面点云法线垂直关系，提取精度较低的中轴线；最后对各区段利用圆柱多段拟合，提取精度较高的中轴线。实验表明，隧道中轴线的提取在一定的采样区间具有较高的稳定性，对直线和弯曲的圆形隧道有良好的适用性，算法可靠，精度较高。     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

一种有发展前景的隧道及井巷超前预报技术——电磁导弹探测技术

对于隧道和煤矿井巷的安全掘进 ,超前预报显得特别重要。但由于掌子面前的特殊环境限制及多种干扰的严重影响 ,给隧道及井巷超前预报技术的研究带来许多困难。在瞬变电磁理论的基础上 ,引入新的电磁传播理论———电磁导弹技术 ,作为对该技术的初步探索 ,文章论证了该技术在隧道超前预报中应用的可能性 ,并提出了研究的主要内容和发展方向以及可能取得的新的技术突破和技术支撑     

隧道工程地质评价的内容和方法

结合工程隧道实际,首先阐述了隧道工程的基本地质环境和工程地质条件,然后针对隧道工程可能出现的不良地质现象和可采取的工程措施,从大气降水、围岩稳定、围岩压力、洞口稳定、隧道比选等角度探讨隧道工程地质评价的主要方法和一般内容,进行隧道工程地质评价,为隧道施工、支护提供了依据.     

Radiation exposure and Mission Strategies for Interplanetary Manned Missions (REMSIM)

Cosmic radiation is an important problem for human interplanetary missions. The “Radiation Exposure and Mission Strategies for Interplanetary Manned Missions–REMSIM” study is summarised here. They are related to current strategies and countermeasures to ensure the protection of astronauts from radiation during interplanetary missions, with specific reference to: radiation environment and its variability; radiation effects on the crew; transfer trajectories and associated fluences; vehicle and surface habitat concepts; passive and active shielding concepts; space weather monitoring and warning systems.     

1999年8月11日日全食期间的重力吸引效应研究

对1999年8月11日日全食阴影扫过欧洲期间,设在Annelles,Uccle,Walferdange和Bondy弹簧和超导重力仪的记录进行了分析.为了确定月亮对太阳万有引力可能的遮挡效应的极限,对超导和弹簧重力仪记录进行了比较.同时也对LCR和阿斯卡尼亚重力仪观测结果进行了讨论.结论是如果日食重力吸引效应存在,它应在超导重力仪±1 nm/s2(0.1×10-8ms-2)的观测精度范围之内.研究发现在以上情形下,弹簧和超导重力仪都在它们的精度范围内工作,并且日食引起的异常环境干扰可能使重力信号有重大的改变.     

Interpretation of aeromagnetic data across the central crystalline shield area of Nigeria

Summary. A residual map of the total magnetic field (above 25 000 nT base) is presented for a portion of the central crystalline shield area of Nigeria and overlapping small portions of the Chad basin and the Benue rift (8°30'−12° 00'lat, and 7°−10°30' long). The map (based on a dataset digitized from recently released aeromagnetic sheets of Nigeria) leads to four results. (1) A magnetic boundary, evident on the map, separates the Younger Granite complexes into two groups. The groups are petrologically different, and the boundary may be a fault line with uplift to the south. (2) South of the boundary the map is dominated by a system of sub-parallel anomalies striking NE–SW, possibly representing major tectonic trends, and a set of fractures through which the Younger Granite complexes were intruded. The trend of the system parallels the Benue rift and lineaments in the oceanic crust off West Africa. (3) Negative magnetic anomalies lie over most of the known ring complexes, and over some suspected buried ring complexes and other intrusions. (4) 2½-and 3-D modelling shows that the larger complexes extend to 12 km depth, and the smaller ones to 6 km. They have nearly vertical sides, and magnetization contrasts range from 0.3 to 0.5 A m⁻¹.     

武汉区域气象中心数值预报业务并行计算机系统

对武汉区域气象中心并行计算机系统进行了详细地介绍，分析了并行计算机体系结构、网络和存储系统特点；给出了在并行计算机SP上实现数值预报业务并行化的部分结果；对数值预报模式在串、并行编程环境下的结果进行了分析比较。