应变能-莫尔准则及其在岩石材料中的应用

本文应用应变能密度与三向应力圆的等价关系,分析修正了莫尔准则,提出用任意确定静水压力下不同洛德参数的极限莫尔圆包络曲线簇作准则线,即谓之为应变能-莫尔准则线,并引用岩土真三轴试验资料进行验证;最后还得出应变能-莫尔屈服条件,分析了屈服曲面和屈服轨迹的形状等。     

Hazard rate estimation of a mixture model with censored lifetimes

This paper is intended to compare the hazard rate from the Bayesian approach with the hazard rate from the maximum likelihood estimate (MLE) method. The MLE of a parameter is appropriate as long as there are sufficient data. For various reasons, however, sufficient data may not be available, which may make the result of the MLE method unreliable. In order to resolve the problem, it is necessary to rely on judgment about unknown parameters. This is done by adopting the Bayesian approach. The hazard rate of a mixture model can be inferred from a method called Bayesian estimation. For eliciting a prior distribution which can be used in deriving a Bayesian estimate, a computerized-simulation method is introduced. Finally, a numerical example is given to illustrate the potential benefits of the Bayesian approach.     

A statistical model for foraminiferal paleobathymetry, with application to the middle Miocene of the Hokuroku district, Japan

A paleobathymetric Bayes estimator, based on a uniform prior distribution of foraminiferal species over the depth range from 0 to 5000 m, is developed and calibrated from the occurrence of 35 species of foraminifera from present day sites on the Pacific and Indian Ocean seafloors. The species are grouped into 12 clusters in order to more nearly satisfy the independence assumptions of the model. Objective depth-independent criteria are developed for ruling certain samples inadmissible for estimation. The accuracy of the estimator is assessed by comparing estimated and measured depths for the admissible calibration samples, yielding a mean absolute error of estimation of between 300 and 400 m. The depth estimator is applied to foraminifera-bearing Miocene samples from the Hokuroku district of Japan, where paleobathymetric depths of between 3000 and 4000 m are indicated at the time of massive sulfide ore formation.     

任意附加应力下竖井径竖向耦合固结等应变解

竖向排水体包括砂井和塑料排水板已广泛应用于加速软黏土地基的固结。不同形式的轴对称条件下含竖向排水体均质各向同性地基的固结解析解答也相继被提出,而各种解答均假定地基中附加应力在竖向排水体的深度范围内是均匀分布的。显然,当竖向排水体深度与地面堆载区宽度的比值相对较高,或竖向排水体的影响区域靠近地面堆载区的边缘时,这个假定并不适用。为此,在现有径竖向耦合固结等应变解的基础上,提出任意分布的地基附加应力条件下的解答,并分析附加应力分布形式和线性加载速率对地基固结的影响。结果表明,均匀分布的附加应力条件下的解答低估了地基的固结速率,而瞬时加载条件下的解答则高估了地基的固结速率。     

湘西碳酸岩山区页岩气地震勘探采集技术研究

湖南湘西碳酸盐岩山区不同时期灰岩出露,岩性变化较大,且受风化、淋滤、剥蚀作用,溶洞、裂缝十分发育,导致地震波能量衰减严重,且地震波传播路径和地震波场的复杂,地震原始资料信噪比较低。针对上述问题,采用单/双井微测井相结合的精细浅表层结构调查方法,结合药柱长度和爆炸理论计算出的爆炸半径,动态设计井深激发方式。通过室内模拟计算,研究低频检波器多串、线性等组合接收方式在区内压制面波、折射波、多次折射及侧面波等多波干扰的效果,最终选择2串24个检波器等灵敏度组合及小道距、高覆盖观测等关键采集技术。实践表明,该区选择的观测系统较好的克服了南方岩溶地区地震勘探信噪比低的问题,具有极强的推广价值。     

A geo-information system approach for forest fire likelihood based on causative and anti-causative factors

Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant.

The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time.     

一种利用扩展磁偏角数据自动计算磁偏角的方法

提出一种基于扫描磁偏角地磁图自动计算磁偏角的方法,把一维磁偏角数据扩展到二维数据,将有关图像校正的方法用在磁偏角的求取上,即在扫描磁偏角地磁图中以图上的地理坐标、扩展磁偏角等值线坐标以及扩展磁偏角等变线坐标所对应的像素坐标为媒介,通过非线性变换,最终建立起地理坐标、磁偏角等值线以及磁偏角等变线之间的相互对应关系,以解决...     

Using analysis state to construct a forecast error covariance matrix in ensemble Kalman filter assimilation

Correctly estimating the forecast error covariance matrix is a key step in any data assimilation scheme. If it is not correctly estimated, the assimilated states could be far from the true states. A popular method to address this problem is error covariance matrix inflation. That is, to multiply the forecast error covariance matrix by an appropriate factor. In this paper, analysis states are used to construct the forecast error covariance matrix and an adaptive estimation procedure associated with the error covariance matrix inflation technique is developed. The proposed assimilation scheme was tested on the Lorenz-96 model and 2D Shallow Water Equation model, both of which are associated with spatially correlated observational systems. The experiments showed that by introducing the proposed structure of the forecast error covariance matrix and applying its adaptive estimation procedure, the assimilation results were further improved.     

Statistical estimation of the apex of a sediment distribution system from paleocurrent data

Precise statistical models are proposed for the distribution of paleocurrent directions in distributary systems. These models are based on a von Mises distribution for directions of paleocurrents in a system. The method of maximum likelihood is used to obtain an estimated position and confidence regions for the apex of the system. Both axial data (where only the trend of the paleocurrent is known) and directional data (where the direction of paleoflow is known) can be used. These models have been applied to two fluvial distributary systems in flat-lying Miocene deposits in the Ebro Basin, northern Spain. The estimate of the position of the apex of one of these systems is in good agreement with the position at the basin margin predicted from sedimentary facies information. The estimate of the position of the apex of the second system lies outside of the sedimentary basin; this result is considered to indicate that the distributary system had several feeder points along the basin margin, a situation which is predicted also from facies distributions. This statistical procedure can be used successfully on small data sets of around a hundred paleocurrent readings provided that they are scattered evenly across the area or lie in a wide arc.     

Statistics of extremes in hydrology

The statistics of extremes have played an important role in engineering practice for water resources design and management. How recent developments in the statistical theory of extreme values can be applied to improve the rigor of hydrologic applications and to make such analyses more physically meaningful is the central theme of this paper. Such methodological developments primarily relate to maximum likelihood estimation in the presence of covariates, in combination with either the block maxima or peaks over threshold approaches. Topics that are treated include trends in hydrologic extremes, with the anticipated intensification of the hydrologic cycle as part of global climate change. In an attempt to link downscaling (i.e., relating large-scale atmosphere–ocean circulation to smaller-scale hydrologic variables) with the statistics of extremes, statistical downscaling of hydrologic extremes is considered. Future challenges are reviewed, such as the development of more rigorous statistical methodology for regional analysis of extremes, as well as the extension of Bayesian methods to more fully quantify uncertainty in extremal estimation. Examples include precipitation and streamflow extremes, as well as economic damage associated with such extreme events, with consideration of trends and dependence on patterns in atmosphere–ocean circulation (e.g., El Niño phenomenon).