Incremental elastoplastic FEM for simulating the deformation process of suction caissons subjected to cyclic loads in soft clays

This paper presents an incremental elastoplastic finite element method (FEM) to simulate the undrained deformation process of suction caisson foundations subjected to cyclic loads in soft clays. The method is developed by encoding the total-stress-based bounding surface model proposed by the authors in the ABAQUS software package. According to the model characteristics, elastoplastic stress states associated with the incremental strains of each iteration are determined using the sub-incremental explicit Euler algorithm, and the state parameters describing the cyclic accumulative rates of strains are updated by setting state variables during the calculations. The radial fallback method is also proposed to modify the stress states outside the bounding surface to the surface during determination of the elastoplastic stress states. The stress reversals of soil elements are judged by the angle between the incremental deviatoric stress and the exterior normal vector at the image stress point on the bounding surface to update the mapping centre and state variables during cyclic loading. To assess the general validity of the method, the reduced scale model tests and centrifuge tests of suction caissons subjected to cyclic loads are simulated using the method. Predictions are in relative good agreement with test results. Compared with the limit equilibrium and quasi-static methods, the method can not only determine the cyclic bearing capacity, but can also analyse the deformation process and the failure mechanisms of suction caisson under cyclic loads in soft clays.     

APG:A novel python-based ArcGIS toolbox to generate absence-datasets for geospatial studies

One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of outputs.To solve this problem,this study develops the Absence Point Generation(APG)toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial studies.The APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude,slope degree,topographic wetness index,and distance from rivers,and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are gener-ated.To test the APG toolbox,we applied two benchmark algorithms of random forest(RF)and boosted regression trees(BRT)in a case study to investigate groundwater potential using three absence datasets i.e.,the APG,random,and selection of absence samples(SAS)toolbox.The BRT-APG and RF-APG had the area under receiver operating curve(AUC)values of 0.947 and 0.942,while BRT and RF had weaker per-formances with the SAS and Random datasets.This effect resulted in AUC improvements for BRT and RF by 7.2,and 9.7％from the Random dataset,and AUC improvements for BRT and RF by 6.1,and 5.4％from the SAS dataset,respectively.The APG also impacted the importance of the input factors and the pattern of the groundwater potential maps,which proves the importance of absence points in environmental bin-ary issues.The proposed APG toolbox could be easily applied in other environmental hazards such as landslides,floods,and gully erosion,and land subsidence.     

区块链技术在教育领域的应用现状与展望

区块链本质上的去中心化和安全特性,使得其很适合于解决目前教育领域面临的困难.本文首先介绍了区块链的基本技术原理,包括区块的结构和区块链的构成、区块链技术平台的体系结构、区块链的分类、共识算法、智能合约.接着分析了目前教育领域发展的终身教育和跨地区教育的新形势,以及传统数字化教育系统面临的主要问题.然后从教育相关信息的多方共享和验证、学习过程跟踪、激励和学习路径塑造、学习评估、教育管理与决策辅助等几个方面对区块链技术在教育领域的应用现状进行了介绍和分析.最后总结了目前区块链技术应用到教育领域的主要问题,并展望了未来的发展方向.     

飞机积冰预报算法对比及其集成预报模型研究

以人工增雨作业获取的飞机积冰实例资料为基础,利用WRF模式对51次飞机积冰过程进行数值模拟,对比分析了常用七种积冰预报算法对积冰潜势区和强度的预报效果,进而采用评分权重集成法建立了飞机积冰强度集成预报模型,并检验了其预报效果。结果表明:(1)假霜点温度经验法对2002年4月4日积冰个例的预报效果与实况一致,而其他积冰算法预报效果均与实况相差较大;(2)对51次飞机积冰预报效果进行统计检验发现,假霜点温度经验法的预报效果最好,积冰强度预报准确率为72.55%,其次是RAOB法,IC指数法和I积冰指数法次之,改进的IC指数法预报准确率最差,只有19.61%;(3)对比不同积冰算法建立的集成预报模型的预报效果发现,选用IC指数法、假霜点温度经验法、RAOB法进行集成预报时,预报准确率最高,且漏报率、偏弱率及偏强率均能控制在10%以内,比单一预报算法中的最高预报准确率提高了8%,且漏报率降低了4%,偏强率降低了8%。     

基于MATLAB的基本矩阵随机采样鲁棒估计

基本矩阵的估算可以分为线性算法、非线性优化迭代算法、鲁棒估计算法三大类,而以鲁棒估计效率、效果最为突出,但是实现比较复杂。本文通过数码相机获取的两张未标定照片,采样互相关系数法和RANSAC算法,在MATLAB中实现了基本矩阵的自动拟合,实验表明拟合精度较高、速度快,为下一步三维场景的自动重建和量测奠定了基础。     

GA-BP网络模型在GPS似大地水准面精化中的应用

针对误差反向传播（BP）算法训练速度慢和易于陷入局部最小值的缺点,提出了利用遗传算法（GA）的全局寻优性,结合GA和BP的各自优点,分析和建立了进化神经网络（GA-BP）模型,并将该模型应用于似大地水准面模型精化。最后以南方某市E级GPS控制网高程数据为例,进行BP和GA-BP模型的对比实验,通过对内、外符合精度及MAPE（平均绝对误差百分比）指标分析,验证了该方法的可行性。     

Evaluation of ENVISAT ASAR data for sea surface wind retrieval in Hong Kong coastal waters of China

The C-band wind speed retrieval models, CMOD4, CMOD - IFR2, and CMOD5 were applied to retrieval of sea surface wind speeds from ENVISAT （European environmental satellite） ASAR （advanced synthetic aperture radar） data in the coastal waters near Hong Kong during a period from October 2005 to July 2007. The retrieved wind speeds are evaluated by comparing with buoy measurements and the QuikSCAT （quick scatterometer） wind products. The results show that the CMOD4 model gives the best performance at wind speeds lower than 15 m/s. The correlation coefficients with buoy and QuikSCAT winds are 0.781 and 0.896, respectively. The root mean square errors are the same 1.74 m/s. Namely, the CMOD4 model is the best one for sea surface wind speed retrieval from ASAR data in the coastal waters near Hong Kong.     

基于遗传算法的浮式防波结构物形状最优化设计

采用遗传算法作为优化手段,以透射系数为目标函数,对给定横剖面面积的浮式防波结构物在规则波中的消波性能及剖面形状进行了最优化计算研究,探讨了透射系数最小的剖面形状与波浪周期之间的关系,为浮式防波结构物的设计提供了一定的理论依据     

计算数据域特征值的两种算法

设计两种计算数据域特征值的算法。此特征值通常是用线性反馈移位寄存器（ＬＦ－ＳＲ）组成的特征分析器得到的．在数据已按字节存放和速度要求不高的场合下，本算法将是十分方便和有用的．     

全球百年海表面温度年际和年代际变化特征分析

利用100 a(1903—2002年)HadiSST的逐月资料,将全球海表面温度异常(SSTA)作为整体进行经验正交函数分解(EOF分解),提取了控制各大洋SSTA的主导模态和各大洋之间的联合模态,分析了相应的空间分布和时间序列。研究结果表明:SSTA变化最剧烈的海区是赤道中东太平洋、西北大西洋湾流海区和北太平洋黑潮延伸体海区。热带太平洋厄尔尼诺和南方涛动是主导模态并具有2~7 a周期的年际变化;SSTA变化第二主模态和第三主模态都是以大约70 a为周期的年代际变化为主的跨大洋联合模态。第二主模态的空间分布主要表现为中纬度北太平洋和北大西洋反位相、热带太平洋与大西洋反位相的太平洋-大西洋双偶极子型分布。SSTA变化的第三模态主要呈现南北半球海洋反位相的特征,为北太平洋-北大西洋-南大洋联合模态。第四模态基本上是反映各个不同海域特有的局地海洋-大气相互作用模态,该模态的时间序列具有1~4 a周期的年际变化和约9 a周期的年代际变化。