Application of saddlepoint approximation in reliability analysis of dynamic systems

The application of the saddlepoint approximation to reliability analysis of dynamic systems is investigated. The failure event in reliability problems is formulated as the exceedance of a single performance variable over a prescribed threshold level. The saddlepoint approximation technique provides a choice to estimate the cumulative distribution function (CDF) of the performance variable. The failure probability is obtained as the value of the complement CDF at a specif ied threshold. The method requires computing the saddlepoint from a simple algebraic equation that depends on the cumulant generating function (CGF) of the performance variable. A method for calculating the saddlepoint using random samples of the performance variable is presented. The applicable region of the saddlepoint approximation is discussed in detail. A 10-story shear building model with white noise excitation illustrates the accuracy and effi ciency of the proposed methodology.     

Point-block covariance: A general solution for the two-dimensional stationary random functions

The application of the theory of random functions to problems of ore evaluation may involve computations of the covariance between the mean value of a given block and the functional value at a given point. However, an analytical solution for such a covariance does not exist for nonspherical blocks and for commonly applied models of covariance functions. Further, because this covariance is a function of the spatial arrangements of the block and the point, it has to be evaluated numerically each time for given point—block arrangements. This paper presents a readily available general solution to this problem in the form of a series of graduated curves which, together with some geometric manipulations, may be used to compute the covariance between a pointand a two-dimensional block for all possible point—block arrangements. The availability of the graph thus eliminates the necessity of using the time-absorbing programs on computers for such computations. Finally, many of the approximations that are made in order to avoid cumbersome covariance evaluations are no longer necessary due to the ease of such computations with the help of the graph provided.     

基于Matlab的断裂带温泉水地球化学特征及地震活动性研究

基于Matlab开发出地下流体分析软件,对比分析了甘肃西秦岭北缘的武山、街子和清水温泉水化学组分特征;初步分析了温泉水水质类型、补给来源、水-岩平衡状态以及循环深度,并讨论了温泉水深循环对地震活动性的影响.研究表明温泉水均为大气降水成因,其水化特征受围岩的控制作用;清水温泉水的成熟度没有武山和街子温泉水高.地下水循环深度较浅的武山温泉和街子温泉水化类型属于Na-HCO3·SO4·Cl,所处断裂的地震活动频繁;地下水循环深度较深的清水温泉水化类型属于Na-SO4·Cl,所处断裂的地震活动性弱.     

甘肃“5·5"黑风暴小波分析

用小波变换理论对１９９３年春季甘肃省河西走廊地区一场特大黑风暴进行了分析。结果表明，小波分析能比较客观地将时间序列中不同时间尺度的振动分离开，使我们能清楚地看到黑风暴中的中尺度扰动。     

非均质地基中平面应变隧道开挖面稳定上限分析

非均质是软黏土地基中比较普遍的现象,而目前隧道开挖面稳定研究中比较成熟的理论主要是针对均质土体。因此,从塑性极限分析上限法的基本原理出发,采用平面应变隧道刚体平动破坏模式(多块体上限法),考虑软黏土地基的非均质性,推导了平面应变隧道极限支护压力关于隧道埋深、土体重度及土体强度的上限公式。通过与其他方法的比较分析,证明了极限分析方法在隧道开挖面稳定性方面的可行性;利用该方法的计算结果详细探讨了隧道开挖面稳定的影响因素;而且由计算结果可知,地基土的非均质性在影响隧道开挖面极限支护压力的同时,也影响着隧道开挖破坏面的位置和形状,为工程实践提供重要的理论依据。     

泌阳断陷下第三系核三上段高频层序中米兰柯维奇天文旋回信息

古气候是影响陆相层序发育的一个重要因素,其周期性变化是源于天文旋回的驱动力（即米兰柯维奇假说）。米兰柯维奇天文旋回包括偏心率旋回、倾斜率旋回和岁差旋回,这几个轨道参数所驱动的古气候变迁,分别形成了周期为１０万年（或４０万年）、４万年及２万年的高频层序,即小层序组、小层序及小层单元,研究结果表明,泌阳断陷湖盆的高频层序是由地球轨道旋回所驱动的古气候周期性变迁所形成的。     

搅拌桩复合地基平面模拟的简化方法探讨

水泥土搅拌桩(DMM)在高速公路工程中得到广泛应用,人们也希望能对该复合地基在路堤荷载下的地基的变形深入了解,其数值分析是一种重要的方法。但是,采用三维有限元进行数值模拟在高速公路工程中容易造成数组过大,计算时间并且收敛性比较差,因此把三维问题简化为二维问题是众望所归。在把三维问题简化二维平面问题简化计算时,最重要的是参数的折减。基于水泥土搅拌桩复合地基的特性,结合理论分析提出了一种参数折减的方法。并依据连盐高速公路实测的数据验证了该参数简化方法的可行性。     

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．     

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.