基于拉格朗日拟序结构的黑潮区域海流运输结构提取和分析

海流的拉格朗日运动对于研究物质输送有着重要意义，拉格朗日拟序结构(LCSs)作为研究海流结构的新型方法，相比于传统欧拉方法更为客观。本文提出了一种新的计算LCSs束的方法，基于25年的平均速度场，利用变分方法计算得到黑潮区域的气候态LCSs，并通过简化合并的方法得到了气候态LCSs束，该LCSs束能够突出地显示出海流特性和运输模式，其代表的平均拉格朗日环流有很强的约束作用，且具有鲁棒性。最终我们获得了气候态下12个月份的流场结构图，揭示了月周期性拉格朗日环流规律。本文还利用虚拟粒子输运、多年浮标轨迹以及气候态温盐异常3种方法进行了验证，与拉格朗日运输模式相吻合，证明了海流拉格朗日拟序结构的准确性和可靠性。     

Tracing the settlement region of massive floating green algae in the Yellow Sea

Outbreaks of large-scale green tides formed by Ulva prolifera in the Yellow Sea(YS)cause heavy ecological damages and huge economic losses.However,the ecological consequences of green tides remain poorly understood due to the lack of knowledge on the settlement region of massive green algae floating in the YS.In this study,we established a method to trace the settlement region of floating green algae,using 28-isofucosterol preserved in sediment as the specific biomarker for green algae.Sterols including 28-isofucosterol in surface sediment samples collected during an investigation in the YS and the Bohai Sea(BS)in August 2015 were analyzed using gas chromatography coupled with a mass spectrometer(GC-MS).Based on the content of 28-isofucosterol in sediment samples,the potential settlement region of loating green algae was identified in the sea area southeast to the Shandong Peninsula around the sampling site H06(122.66°E,36.00°N).This paper presents a first result on the settlement region of floating green algae in the YS for providing a solid basis to elucidate the ecological consequences of green tides in the area.     

One-dimensional consolidation of soil under multistage load based on continuous drainage boundary

In engineering practice, a rapid loading rate can result in ground failure when the strength of soft soils is relatively low, and a multistage loading scheme is always utilized to deal with this situation. Firstly, under a multistage load and the continuous drainage boundary, an analytical solution of excess pore-water pressure and consolidation degree is obtained by virtue of the superposition formula of excess pore-water pressure, and a more general continuous drainage boundary under arbitrary time-dependent load is developed. Then, a comparison with existing analytical solutions is conducted to verify the present solution. A preliminary attempt on applying the continuous drainage boundary into the finite element model is made, and the feasibility of the numerical model for the one-dimensional consolidation under the continuous drainage boundary is verified by comparing the results calculated by FEM with that from present analytical solution. Finally, the consolidation behavior of soil is investigated in detail for different int erface parameters or loading scheme. The results show that, in land reclamation projects, a horizontal drain should be placed close to the boundary with a smaller interface parameter to improve the consolidation efficiency. The degree of consolidation is also related to the applied time-dependent load and interface parameters.     

Hydrological cycle and water balance estimates for the megadune–lake region of the Badain Jaran Desert,China

The hydrology and water balance of megadunes and lakes have been investigated in the Badain Jaran Desert of China. Field observations and analyses of sand layer water content, field capacity, secondary salt content, and grain size reveal 3 types of important natural phenomenon: (a) vegetation bands on the leeward slope of the megadunes reflect the hydrological regime within the sandy vadose zone; (b) seepage, wet sand deposits, and secondary salt deposits indicate the pattern of water movement within the sandy vadose zone; (c) zones of groundwater seeps and descending springs around the lakes reflect the influence of the local topography on the hydrological regime of the megadunes. The seepage exposed on the sloping surface of the megadunes and gravity water contained within the sand layer confirm the occurrence of preferential flow within the vadose zone of the megadunes. Alternating layers of coarse and fine sand create the conditions for the formation of preferential flows. The preferential flows promote movement of water within the sand layer water that leads to deep penetration of water within the megadunes and ultimately to the recharging of groundwater and lake water. Our results indicate that a positive water balance promotes recharge of the megadunes, which depends on the high permeability of the megadune material, the shallow depth of the surface sand layer affected by evaporation, the occurrence of rainfall events exceeding 15 mm, and the sparse vegetation cover. Water balance estimates indicate that the annual water storage of the megadunes is about 7.5 mm, accounting for only 8% of annual precipitation; however, the shallow groundwater per unit area under the megadunes receives only 3.6% of annual precipitation, but it is still able to maintain a dynamic balance of the lake water. From a water budget perspective, the annual water storage in the megadunes is sufficient to serve as a recharge source for lake water, thereby enabling the long‐term persistence of the lakes. Overall, our findings demonstrate that precipitation is a significant component of the hydrological cycle in arid deserts.     

胶东型金矿：与壳源重熔层状花岗岩和壳幔混合花岗闪长岩有关的金矿

胶东型金矿是与壳源重熔形成的层状岩浆活动和壳幔混合岩浆活动有关的金矿床,由于成矿时所处构造位置和容矿构造不同而表现为不同的类型,涵盖破碎带蚀变岩型、石英脉型等胶东地区所有金矿床类型。玲珑花岗岩是壳源物质长期处于高温高压下且熔融形成的多物质来源层状岩体,其析出的高温碱性热液溶解金等成矿物质形成初始含矿热液。岩体抬升过程中在其边部往往容易形成拆离带,在岩体中形成脆性断裂构造,均为成矿结构面。后期壳幔混合成因的郭家岭花岗闪长岩,侵入于玲珑层状花岗岩中并一起隆升,使郭家岭花岗闪长岩附近区域的成矿结构面进一步扩大,矿液浓度进一步增大,当上升到特定深度时形成金矿体。玲珑花岗岩和郭家岭花岗闪长岩共同构成成矿地质体,重熔的玲珑层状岩体是成矿基础地质体,郭家岭花岗闪长岩加强了金矿的成矿作用。该认识对开辟胶东新的找矿思路和找矿靶区有很好的指导作用,据此初步预测新的大型拆离带是金矿集中成矿区域,可能成为将来有望取得重大突破的矿集区。     

自适应联邦滤波器在GPS-INS-Odometer组合导航的应用

针对多传感器观测信息较多、计算效率较低、对动力学模型误差稳键性不佳的问题,提出了一种自适应联邦滤波器并应用于GPS-INS-Odometer组合导航。首先介绍GPS-INS-Odometer组合导航的动力学模型和观测模型,比较分析了信息分配因子和自适应因子的共同特性,论证了联邦滤波器和自适应滤波器的等价性及其等价成立条件,提出了自适应联邦滤波器的信息分配因子构造方法。最后利用实测数据验证了算法的有效性。结果表明,相比于基于GPS和Odometer(里程计)初始方差构造信息分配因子的联邦滤波器,本文提出的自适应联邦滤波器兼容了联邦滤波器高效计算效率,且具有较好的抵抗动力学模型误差效果,能够有效削弱多传感器动力学模型误差对于导航解算的影响,对直接可测参数和间接可测参数的精度提高均起到了积极的作用。     

Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.