Nonlinear Mechanical Behavior Analysis of Flexible Lateritic Pavements of Senegal (West Africa) by FEM for M.-E. Pavement Design

Pavement design in Senegal is based on a linear elastic behavior of pavement materials and the hypothesis of a static loading. However, previous works on the mechanical behavior of road materials showed that this one is reversible after several loading cycles and depends on the applied stress. The described behavior is from then on, purely nonlinear. One of the objectives of this research is to determine the parameters of response of lateritic pavement materials submitted to road traffic by using FEM. Therefore, experiments were made on gravel lateritic soils from Dougar, Sébikotane, Mont-Rolland, Pâ Lo and Ngoundiane. The Young’s modulus of the materials was defined in unconfined compression test while repeated load triaxial test was performed to determine the resilient modulus of the gravels and the appropriate model (Uzan model). An implementation was realized with Cast3M©. The importance of the nonlinearity was revealed in a very clear way and was crucial in the construction of the calculation algorithm. The observations for certain conditions showed that the values of the critical responses are more important for the linear model than for the nonlinear model. However, this trend should be validated by further studies.     

A new approach to minimize the loss of life after natural hazards by using Android operating system

Nowadays, the usage rates of smartphones are increasing rapidly. With the versatility of its features, smartphones have succeeded in attracting users. Performing this study has also affected the usage rate of smartphones every day. It is possible to determine the position with GPS (Global Positioning System) technology which is located in smartphones. In this study, smartphone location notification was used to detect the locations of the people who were under debris after the earthquake by means of the phones on them. People who cannot be reached for any reason will be immediately identified, and emergency interventions will be possible. Thus, the survival rate of the injured will be high with early intervention. In this study, it was aimed to minimize the loss of life after the earthquake and all the negativities that would be experienced in society due to this loss. The developed application has been tested in the external world, and the obtained data are given in results section.

     

北衙金矿多期热液成矿作用识别:来自地质、岩相学、流体包裹体和H-O-S同位素证据

北衙超大型金矿床是三江特提斯成矿域中喜山期斑岩-矽卡岩型矿床的典型代表,长期以来大量研究均围绕斑岩-矽卡岩成矿作用开展并取得了丰硕成果,然而对于北衙金矿是否存在多期热液成矿作用尚不明确。本次研究基于详细野外调查、岩相学与矿相学研究,流体包裹体显微测温及成分分析、H-O-S同位素分析等多种手段,识别了北衙金矿成矿晚期存在新一期热液成矿事件。主要证据如下:(1)野外调查发现北衙金矿发育NW向陡倾断裂控制的石英多金属硫化物脉,其切割矽卡岩矿体与矽卡岩晚期石英硫化物矿脉;(2)本次研究矿脉中原生流体包裹体类型主要为富CO_2三相水溶液包裹体、含CO_2三相水溶液包裹体及气液两相水溶液包裹体,而矽卡岩晚期硫化物脉中除上述三种类型外还发育含子晶三相水溶液包裹体;(3)成矿流体均一温度分布范围为204～426℃,盐度为1.0%～14.2%NaCleqv,整体表现为中高温、中低盐度的NaCl-CO_2-H_2O流体体系,而矽卡岩晚期硫化物脉成矿流体体系具有中温、中高盐度的特征;(4)该矿脉中石英的δ~(18)O、δD范围分别为7.5‰～9.4‰与-102.0‰～-75.0‰,指示岩浆水来源,而矽卡岩晚期硫化物脉具有岩浆水和大气水混合来源。本次研究的多金属硫化物矿脉δ~(34)S值范围为-0.97‰～1.40‰,与矽卡岩期和矽卡岩晚期硫化物脉中黄铁矿S同位素一致,表明多期矿化成矿物质均具有幔源贡献。结合北衙矿集区成岩成矿动力学背景,推测始新世大规模地壳拆沉、软流圈上涌导致的强烈的壳幔相互作用可能是北衙金矿多期成矿作用的诱因。     

Simplified formulae for designing coastal forest against tsunami run-up: one-dimensional approach

In the present study, laboratory experiments were conducted to validate the applicability of a numerical model based on one-dimensional nonlinear long-wave equations. The model includes drag and inertia resistance of trees to tsunami flow and porosity between trees and a simplified forest in a wave channel. It was confirmed that the water surface elevation and flow velocity by the numerical simulations agree well with the experimental results for various forest conditions of width and tree density. Further, the numerical model was applied to prototype conditions of a coastal forest of Pandanus odoratissimus to investigate the effects of forest conditions (width and tree density) and incident tsunami conditions (period and height) on run-up height and potential tsunami force. The modeling results were represented in curve-fit equations with the aim of providing simplified formulae for designing coastal forest against tsunamis. The run-up height and potential tsunami forces calculated by the curve-fit formulae and the numerical model agreed within ± 10% error.     

面向矿产资源信息的空间关联性分析

关联性分析是综合多源、多类数据,发现和挖掘数据中潜在的相关关系,提取和挖掘数据之间的关联性。该方法对于充分利用地质大数据、发现地质要素之间的共生组合规律具有重要的意义。本文首先基于数据的空间位置,将不同类型的地质空间数据建立联系,形成空间属性数据库;其次应用统计方法,对不同来源数据中的属性特征进行分析,发现热液型金矿的形成与火山作用存在明显相关性;最后基于Apriori算法提取热液型金矿的伴生矿与侵入岩的频繁项集,发现伴生矿与侵入岩酸碱性二者密切相关。因此,在今后的工作中,有望应用空间关联性的方法对地球物理、地球化学、遥感等多源地质数据开展深入的研究分析。     

Intraseasonal oscillation of the rainfall variability over Rwanda and evaluation of its subseasonal forecasting skill

非洲中东部地区的经济主要依靠自给农业支撑,该地区农业经济对降水的变化尤为敏感.本文以卢旺达为例,观测分析指出卢旺达的次季节降雨主要集中在10-25天;根据次季节尺度降水变率的单点相关方法,发现卢旺达的次季节降水变率和周围区域变化一致;进一步合成结果显示该地区次季节降水变率与异常西风有关,这可追溯到赤道地区西传的赤道Rossby波.最后,本文评估了当前动力模式ECMWF对 卢旺达地区(即非洲中东部)次季节降水变率的预报能力,发现EC模式在对该区域降水和相关风场指数的预报技巧都在18天左右,且预报技巧表现出一定的年际差异,这可能与热带太平洋的背景海温信号有关.该工作增进了当 前对非洲中东部地区的次季节降水变率和预测水平的认知,并且对该地区国家粮食安全和防灾减灾具有启示性意义.     

Intraseasonal oscillation of the southwest monsoon over Sri Lanka and evaluation of its subseasonal forecast skill

斯里兰卡的雨季发生于5-9月间,主要受西南季风的控制.本文发现该地区的西南季风降水存在很强的次季节变率,主导周期为10-35天.降水的季节内变化与西传的异常气旋有关.进一步,利用S2S比较计划中欧洲中心的数值预报模式(ECMWF)提供的回报试验数据,评估了当今动力模式对斯里兰卡西南季风次季节变化的预报技巧.结果显示,对季风指数的预测技巧超过30天,而对降水指数的预测技巧大约两周,且模式的预报技巧具有明显的年际差异.分析表明,能否正确模拟出大尺度环流对热带对流的响应是影响斯里兰卡降水预测的重要因子.     

基于多尺度特征融合网络的云和云阴影检测试验

基于深度学习的高分辨率光学影像云检测过程中,云和云阴影及其边缘细节丢失较为严重,主要原因在于不同尺度空间语义信息特征融合存在不足。针对该问题,本文构建一种基于深度学习的多尺度特征融合网络（Multi-scale Feature Fusion Network, MFFN）的云和云阴影检测方法,该算法结合防止网络退化的残差神经网络模块（Res.block）、扩大网络感受野的多尺度卷积模块（MCM）和提取并融合不同尺度信息的多尺度特征模块（MFM）。试验表明,本算法能提取丰富的空间信息与语义信息,可取得较为精细的云与云阴影掩模,具有较高检测精度,其中云检测准确率达0.9796,云阴影检测准确率达0.8307。同时,该工作可为深度学习技术应用于业务云检测提供理论支持及技术储备。     

An improved ionosphere interpolation algorithm for network RTK in low-latitude regions

A traditional interpolation algorithm with the linear interpolation method (LIM) using a fixed number of reference stations is widely used in network RTK to obtain the ionospheric delays for the users. In low-latitude regions, where the ionosphere is relatively active, however, large interpolation errors exist, especially for satellites at low elevation angles. Considering the characteristics of “coinciding ionospheric pierce points (CIPPs)” with a similar nature of ionospheric delays, an improved interpolation algorithm is proposed. In this algorithm, all stations with CIPPs are used to establish the interpolation model; thus, more precise interpolation model is achieved. To validate the performance of the proposed algorithm, data from some reference stations in Guangdong Province of China were used, and the results are compared with those with the traditional interpolation algorithm. Numerical analysis shows that the interpolation accuracy of the proposed algorithm increases by 10–30% compared with the traditional one. Since the number of reference stations is flexible, the proposed algorithm can also balance the model accuracy with the computation burdens. In addition, the proposed algorithm is less affected by the selection of master reference station. In terms of network RTK on-the-fly positioning, the time-to-first-fix is reduced when replacing the traditional interpolation algorithm with the proposed one.     

Automatic detection of earthquake-induced ground failure effects through Faster R-CNN deep learning-based object detection using satellite images

Natural Hazards - The seismically induced ground failure is defined as any earthquake-generated process that leads to deformations within a soil medium, which in turn results in permanent...