强矿震地球物理过程及短临阶段预测的研究

用区域强震震源机制解、现场地应力测量、三维有限差分数值模拟方法分析强矿震的孕震环境；通过定量观察采矿与矿震活动的相关性，分析强矿震的诱发原因；基于中尺度地震实验场高密度数字地震和前兆台网的现场观测，用地震学方法和小波工具分析强矿震孕震过程采集到的数据，提取短临阶段的异常信息；通过强矿震的震源机制解判断震源处的应力释放状态。提出地质构造环境、地应力场和采矿活动共同作用诱发强矿震的机理和次生应力场在孕育该震过程起主导作用的观点．发现震前短临阶段存在可信的b值、η值、频次、波速比等地震学异常和定点潮汐形变前兆异常，时异常信息的提取方法和强矿震短临阶段的预测进行了探讨。     

Missing precipitation data estimation using optimal proximity metric-based imputation,nearest-neighbour classification and cluster-based interpolation methods

Abstract

New optimal proximity-based imputation, K-nearest neighbour (K-NN) classification and K-means clustering methods are proposed and developed for estimation of missing daily precipitation records. Mathematical programming formulations are developed to optimize the weighting, classification and clustering schemes used in these methods. Ten different binary and real-valued distance metrics are used as proximity measures. Two climatic regions, Kentucky and Florida, (temperate and tropical) in the USA, with different gauge density and network structure, are used as case studies to evaluate the new methods. A comprehensive exercise is undertaken to compare the performances of the new methods with those of several deterministic and stochastic spatial interpolation methods. The results from these comparisons indicate that the proposed methods performed better than existing methods. Use of optimal proximity metrics as weights, spatial clustering of observation sites and classification of precipitation data resulted in improvement of missing data estimates.

Editor D. Koutsoyiannis; Associate editor C. Onof     

Beerkan multi-runs for characterizing water infiltration and spatial variability of soil hydraulic properties across scales

A method is presented for characterizing the spatial variability of water infiltration and soil hydraulic properties at the transect and field scales. The method involves monitoring a set of 10 Beerkan runs distributed over a 1-m length of soil, and running BEST (Beerkan estimation of soil transfer parameters) methods to derive hydraulic parameters. The Beerkan multi-runs (BMR) method provides a significant amount of data at the transect scale, allowing the determination of correlations between water infiltration variables and hydraulic parameters, and the detection of specific runs affected by preferential flow or water repellence. The realization of several BMRs at several transects on the same site allows comparison of the variation between locations (spatial variability at the field scale) and at the transect scale (spatial variability at the metre scale), using analysis of variance. From the results, we determined the spatial variability of water infiltration and hydraulic parameters as well as its characteristic scale (transect versus field).     

Statistical facies classification from multiple seismic attributes: comparison between Bayesian classification and expectation–maximization method and application in petrophysical inversion

We present here a comparison between two statistical methods for facies classifications: Bayesian classification and expectation–maximization method. The classification can be performed using multiple seismic attributes and can be extended from well logs to three‐dimensional volumes. In this work, we propose, for both methods, a sensitivity study to investigate the impact of the choice of seismic attributes used to condition the classification. In the second part, we integrate the facies classification in a Bayesian inversion setting for the estimation of continuous rock properties, such as porosity and lithological fractions, from the same set of seismic attributes. The advantage of the expectation–maximization method is that this algorithm does not require a training dataset, which is instead required in a traditional Bayesian classifier and still provides similar results. We show the application, comparison, and analysis of these methods in a real case study in the North Sea, where eight sedimentological facies have been defined. The facies classification is computed at the well location and compared with the sedimentological profile and then extended to the 3D reservoir model using up to 14 seismic attributes.     

设计反应谱标定方法的研究现状与讨论

设计反应谱及其标定方法的研究是工程抗震研究领域的基本问题之一。在现有研究成果的基础上,归纳和总结了设计反应谱及其标定方法的研究历史和现状;评述了研究进程中的若干节点问题;介绍了设计反应谱的标定原理和当前几种有代表性的设计反应谱的标定方法;分析了设计反应谱标定参数的影响因素。在此基础上,对设计反应谱及其标定方法研究中的强震资料积累问题、谱形状问题、标定参数的确定问题以及标定方法等问题进行了讨论并提出了改进和进一步研究的建议。     

Permanent earthquake‐induced actions in buried pipelines: Numerical modeling and experimental verification

Buried pipelines are often constructed in seismic and other geohazard areas, where severe ground deformations may induce severe strains in the pipeline. Calculation of those strains is essential for assessing pipeline integrity, and therefore, the development of efficient models accounting for soil‐pipe interaction is required. The present paper is aiming at developing efficient tools for calculating ground‐induced deformation on buried pipelines, often triggered by earthquake action, in the form of fault rupture, liquefaction‐induced lateral spreading, soil subsidence, or landslide. Soil‐pipe interaction is investigated by using advanced numerical tools, which employ solid elements for the soil, shell elements for the pipe, and account for soil‐pipe interaction, supported by large‐scale experiments. Soil‐pipe interaction in axial and transverse directions is evaluated first, using results from special‐purpose experiments and finite element simulations. The comparison between experimental and numerical results offers valuable information on key material parameters, necessary for accurate simulation of soil‐pipe interaction. Furthermore, reference is made to relevant provisions of design recommendations. Using the finite element models, calibrated from these experiments, pipeline performance at seismic‐fault crossings is analyzed, emphasizing on soil‐pipe interaction effects in the axial direction. The second part refers to full‐scale experiments, performed on a unique testing device. These experiments are modeled with the finite element tools to verify their efficiency in simulating soil‐pipe response under landslide or strike‐slip fault movement. The large‐scale experimental results compare very well with the numerical predictions, verifying the capability of the finite element models for accurate prediction of pipeline response under permanent earthquake‐induced ground deformations.     

基于贝叶斯方法的深层充电效应风险模型评估

高能电子穿透航天器并在其内部沉积电荷从而引发深层充电效应,是导致卫星故障的重要因素之一.为了评估深层充电效应诱发卫星异常的风险,本文基于贝叶斯方法,使用一颗地球同步轨道卫星的异常数据和GOES-8卫星的电子通量探测数据,计算了不同能量阈值及累积时间的电子注量、不同卫星配置下模拟仿真的沉积电荷,并分别与卫星异常建立一系列概率风险模型.本文从模型中随机抽样得到模拟异常,并与实测异常构造混淆矩阵以评估模型拟合优度,结果表明>1.0 MeV电子3日累积注量-卫星异常概率风险模型为该卫星最优模型.本文利用最优模型对该卫星深层充电效应风险进行了计算,在>1.0 MeV电子3日累积注量达到2.0×10¹⁰cm^-2·sr^-1时,该卫星发生深层充电异常的平均后验概率为27%,且95%最小可信值为22%.根据最优模型,我们对该卫星最可能导致异常的部件的材料和结构等特征做出了推断.

     

Inverse reconstructions of ecosystem flows in investigating regime shifts: impact of the choice of objective function

Inverse analysis is increasingly used in ecosystem modelling to objectively reconstruct a large number of unknown flows or interactions from a small number of observations. This type of analysis may be useful in relating observed regime shifts in ecosystem structure to underlying processes. Inversions of ecosystem flow networks currently use a constrained least-squares solution which at the same time minimizes the squared norm (the sum of squares) of the reconstructed flows. This minimum norm (MN) inversion is thought to be a parsimonious solution to the ecosystem flow inverse problem, but it may well not reflect how ecosystems are organised. It has been proposed instead that ecosystems evolve to maximize energy/mass flows or that they maximize the information content of the network weighted by ecosystem flows (ascendancy). We used simulated inverse experiments, where inverse analyses are applied to simulations of flow networks, to explore objective functions different than the MN generally used. We could not compute inverse solutions that maximize ascendancy because the objective function is unbounded. We could calculate inversions that maximize flows; however, these generally overestimated the simulated flows, even though the simulations were designed to maximize flows. It appears that the ecosystem flow inverse problem is too under-determined (too few data relative to the number of unknowns) to allow the use of these maximizing goal functions. We introduce a new minimization that simultaneously minimizes the squared flows and the squared differences between flows. This smoothing minimization makes the inverse flows as even as possible and it helps with some technical issues with MN inversions. The simulated inverse experiments indicated that this smoothed norm (SM) is the most robust in comparative analyses of contrasting ecosystem states, such as those that can be associated with regime shifts. Like the MN inversion, the SM inversion has no ecological basis. However, it is a conservative norm that is less likely to produce false differences between the dynamics of regimes.