Scaling of response spectrum and duration for aftershocks

Aftershocks have the potential to cause collapse of a structure that has been already damaged by the preceding main shock. Seismic safety of a structure should therefore be ascertained through a damage analysis using the anticipated main shock and few larger-aftershock motions. Simulation of aftershock motions needs characterization of the seismic hazard due to aftershocks, and therefore it will be useful to develop a conditional scaling model that can predict the response spectrum of an anticipated aftershock motion consistent with the design spectrum of the main shock motion anticipated at the same station. In this study an attempt is made to develop a conditional scaling model for the pseudo spectral velocity spectrum via linear regression analysis on the aftershock and main shock recordings for the 1999 Chi–Chi earthquake. It is shown that it may be possible to obtain a simpler and approximate version of the conditional model from an unconditional model. Damage-causing potential of a ground motion also depends on its strong motion duration (SMD) and therefore a conditional scaling model is developed for SMD of the aftershock motion in several narrow frequency-bands. The model is developed for the larger-aftershock motions and it is shown that a reasonable replacement of such a model may be obtainable directly from an unconditional model. Finally, a simple weighted averaging scheme is proposed to obtain the composite SMD from the SMDs for different frequency bands by using the pseudo spectral acceleration spectrum of the motion.     

A hybrid discrete–finite element model for numerical simulation of geomaterials

A hybrid discrete–finite element model is introduced for simulation of mechanical behavior of geomaterials. The soil or rock is modeled as a system of discrete balls that interact through normal and shear springs. The balls can be bonded at the contact points to withstand the applied deviatoric stresses. The important feature of this model is that the confining walls that can be imagined for example as the surrounding membrane or the mold in a physical test are modeled by deformable finite elements. This allows simulation of laboratory test features more realistically compared to the situations where the surrounding walls are rigid. The relationships between micro- and macro-properties are investigated in this paper as well. These relationships and the corresponding curves are helpful tools in calibration of the numerical model for the macroscopic elastic properties.     

Crustal Growth by Magmatic Accretion Constrained by Metamorphic P-T Paths and Thermal Models of the Kohistan Arc, NW Himalayas

Magmatic accretion is potentially an important mechanism inthe growth of the continental crust and the formation of granulites.In this study, the thermal evolution of a magmatic arc in responseto magmatic accretion is modeled using numerical solutions ofthe one-dimensional heat conduction equation. The initial andboundary conditions used in the model are constrained by geologicalobservations made in the Kohistan area, NW Himalayas. Takingconsideration of the preferred intrusion locations for basalticmagmas, we consider two plausible modes of magmatic accretion:the first involves the repeated intrusion of basalt at mid-crustaldepths (‘intraplate model’), and the second evaluatesthe simultaneous intrusion of basalt and picrite at mid-crustaldepths and the base of the crust respectively (‘double-platemodel’). The results of the double-plate model accountfor both the inferred metamorphic P–T paths of the Kohistanmafic granulites and the continental geotherm determined frompeak P–T conditions observed for granulite terranes. Thedouble-plate model may be applicable as a key growth processfor the production of thick mafic lower crust in magmatic arcs. KEY WORDS: thermal model; magmatic underplating; P–T path; granulite; lower crust     

基于地质记录用时域组合模型预测气候变化趋势的初步研究

用时域分析组合模型建立了１００万年来６０°Ｎ６月份太阳辐射量时间序列、宝鸡黄土粒度时间序列、渭南夏季风指数时间序列的动态模型．研究结果表明,时域分析组合模型较好地提取了时间序列的信息,得到的几个显著周期Ｔ＝１３３,１００,８９,４１,２３,１９ｋａ,与地球轨道三要素的变化周期接近．用组合模型拟合实测数据,精度是高的;用其预测未来气候替代性指标时间序列的变化情况,发现未来气候有向干冷方向发展的趋势．时域分析组合模型为研究气候变化趋势提供了一种定量分析、预测的方法．     

基于准三维有限元方法建立的地震活动模型

基于有限元方法,参照细胞自动机模型,建立了一个地震活动演化的动力学模型.在这个模型中,根据边界条件和单元介质参数的分布,利用有限元方法确定各单元的应力增长速率.每个单元设定初始应力和摩擦因数,利用破裂准则可得到单元破裂所需时间.当单元破裂后,将破裂单元作为内部边界,利用有限元方法计算由于这个单元破裂对系统其他单元造成的应力调整.根据上述规则,建立一个由30×40个节点组成,在定常位移速率边界条件作用下的地震活动模型,探讨了区域应力场的动态演化、地震活动图像和各种参数变化对地震活动的影响.结果表明该模型在研究地震活动方面有一定优势并具有实用价值.     

The Coral Triangle Initiative and regional exchanges: Strengthening capacity through a regional learning network

Natural resource management and conservation programs that promote building capacity and social learning among participants often lead to the formation of learning networks: a type of social network where learning is both a goal and potential outcome of the network. Through forming relationships and sharing information, participants in a learning network build social capital that can help a network achieve social and environmental goals. In this study, we explored social capital in a learning network that emerged through a large-scale marine governance effort, the Coral Triangle Initiative on Coral Reefs, Fisheries, and Food Security. Through a mixture of social network analysis and key informant interviews, we examined the major patterns of information exchange among individuals who had participated in regional learning exchanges; evaluated whether the network's structure resulted in information sharing; and considered implications for strengthening network sustainability, capacity building, and learning. We found that the Regional Exchange network fostered information sharing among participants across national and organizational boundaries. While the network had individuals who were more central to information sharing, the network structure was generally decentralized, indicating potential resilience to changes in leadership and membership. Participants stressed the importance of the knowledge and connections they had acquired through the learning network; however, they expressed doubts regarding its sustainability and stressed the need for a strong coordinating entity. Our findings suggest that conservation learning networks have the ability to bridge cultural divides and promote social learning; however, a strong network coordinator and continuing efforts to support information sharing and learning are crucial to the network's strength and sustainability. The tangible learning and capacity development outcomes cultivated through Regional Exchange network underscore the value of and need to invest in conservation networks that support peer-to-peer learning.     

Assimilating data into open ocean tidal models

The problem of deriving tidal fields from observations by reason of incompleteness and imperfectness of every data set practically available has an infinitely large number of allowable solutions fitting the data within measurement errors and hence can be treated as ill-posed. Therefore, interpolating the data always relies on some a priori assumptions concerning the tides, which provide a rule of sampling or, in other words, a regularization of the ill-posed problem. Data assimilation procedures used in large scale tide modeling are viewed in a common mathematical framework as such regularizations. It is shown that they all (basis functions expansion, parameter estimation, nudging, objective analysis, general inversion, and extended general inversion), including those (objective analysis and general inversion) originally formulated in stochastic terms, may be considered as utilizations of one of the three general methods suggested by the theory of ill-posed problems. The problem of grid refinement critical for inverse methods and nudging is discussed.     

雷暴探测研究的进展

基于达州市2015年10月-2016年9月的闪电定位和探空观测资料,以850 hPa与500 hPa温差、大气可降水量、K指数、对流有效位能、对流抑制和抬升指数作为雷暴预警因子,利用投影寻踪动态聚类方法对该时段内的雷暴个例构建了预警模型。结果表明：（1）模型预报结果定量评估的临界成功指数为72.00%,该模型对个例达到了识别和预警效果;（2）该预警模型与常规预警方法相比,具有识别率高,计算简便,客观性强等特点,可为雷暴预警提供了一种新的客观预报方法。

     

建立特殊条件下导向钻孔轨迹跟踪和控制的数学模型

建立了在特殊场地条件下,利用雷达探测仪对非开挖钻孔轨迹跟踪和控制的数学模型。在工程实践中,结合计算机技术,利用这个数学模型提供的方法,可以更有效地对非开挖导向钻孔轨迹进行跟踪和控制。     

轨迹大数据: 数据处理关键技术研究综述

针对轨迹大数据的高效点-轨迹k近邻（point to trajectory k nearest neighbor, P2T_kNN）查询处理需求,提出了一种融合时空剖分和轨迹分段的轨迹组织方法,其核心思想是在对轨迹作时间剖分的基础上,利用离散全球网格系统（discrete global grid system, DGGS）在空间上进行再次剖分,从而利用两次剖分得到的时空单元编码来索引落入其中的轨迹片段。在此基础上利用分布式列式存储技术设计了面向轨迹大数据的P2T_kNN查询处理框架,提出了一种顾及轨迹数据空间分布的自适应空间单元搜索算法,即通过分析轨迹数据在给定时间约束下的空间分异特征,动态调整空间单元的搜索步长,从而提升了轨迹稀疏区域的处理效率。针对亿级轨迹的实验结果表明,该方法适用于轨迹大数据的P2T_kNN查询处理,在轨迹稠密与稀疏区域的平均查询响应时间均小于1 s。