影响上海市及邻近区域台风的灰色预测

本文利用台风年鉴１９８１￣１９９６年的资料,根据灰色灾变预测方法,建立了对上海市及其邻近区域产生严重影响的强台风出现时间的ＧＭ（１,１）预测模型,经过检验,精度达到优级,据此预测,下次人侵袭本地区的强台风出现时间为２００１年,同时,用灰色拓扑方法对未来几年上海市江苏、浙江沿海区域产生８级以上大风天气的台风个 数进行了逐年预测。     

Time variant analysis of geomagnetic signals describes the volcanic activity of Mt. Etna between early 2000 and late 2002

Volcanomagnetic anomalies have been mostly observed during strong eruptions. Our aim is to improve the geomagnetic data analysis to evidence the anomalies occurring in a larger time span, especially in the phases preceding the eruptive events. We developed a time variant statistical approach and applied it to the 2000–2002 Etna geomagnetic temporal series. It is based on an algorithm that statistically predicts the geomagnetic field at the station on the volcanic edifice by that recorded at the remote one. In such a way a number of significant changes in the time series (called statistical innovations), marking the local magnetic field change, were detected. The distribution of such statistical innovations accurately describes the Etna volcanic evolution: we note a progressive increase of the innovation occurrence as the eruptive cycles were approaching and only few and weak innovations at times between the various eruptive cycles. The significance of this analysis is further confirmed by the close agreement among the mean square prediction error, strain release and the volcanic activity behavior. On the contrary, the geomagnetic field at a single station or its difference at two stations do not have any clear correlation with other measured physical quantities. The complex pattern of the prediction error was also investigated by a multifractal analysis. We found that the Holder regularity increases with the intensification of the volcanic activity, implying that innovations tend to be less sporadic and correlated during the major volcanic phases.     

Semi‐active multi‐step predictive control of structures using MR dampers

A semi‐active multi‐step predictive control (SAMPC) system with magnetorheological (MR) dampers is developed to reduce the seismic responses of structures. This system can predict the next multi‐step responses of structure according to the current state and has a function of self‐compensation for time delay that occurred in real application. To study the performance of the proposed control algorithm for addressing time delay and reducing the seismic responses, a numerical example of an 11‐story structure with MR dampers is presented. Comparison with the uncontrolled structure indicates that both the peak and the norm values of structural responses are all clearly reduced when the predictive length l?10 and the delayed time step d?20 are selected, and the SAMPC strategy can guarantee the stability of the controlled structure and reduce the effects of time delay on controlled responses to a certain extent. A performance comparison is also made between the SAMPC strategy and the passive‐off and passive‐on methods; results indicate that this SAMPC system is more effective than the two passive methods in reducing structural responses subjected to earthquakes. Copyright © 2008 John Wiley & Sons, Ltd.     

中国金矿矿产预测评价模型及资源潜力分析

在全国金矿资源潜力评价基础上,将全国金矿矿产评价模型总结为12类：与中深成侵入岩有关的热液型、破碎蚀变岩型、斑岩型、矽卡岩型、海相火山岩型、陆相火山岩型、微细浸染型、变碎屑岩地层中热液型、绿岩建造型、砂金型、风化壳型和砾岩型。其中,以与中深成侵入岩有关的热液型、破碎蚀变岩型、微细浸染型为主,其预测资源量约占总预测资源量的38%,21%和14%。根据资源量的空间分布及成矿地质背景划分了55个金矿成矿区带,通过对不同成矿区带对预测资源量、累计查明资源储量统计分析,金矿主要集中分布于胶东、华北地台南缘、西秦岭、东秦岭、辽东、滇黔桂、哀牢山成矿带等。根据金矿的成矿地质背景,结合金矿资源潜力及近年来金矿勘查进展,对下一步的工作部署提出参考建议。     

Boundary layer dynamics and drag reduction in flows of high cohesive sediment suspensions

Drag reduction has been observed in suspension flows of low clay concentrations in previous studies. Here, velocity profiles and bed shear stresses, expressed as shear velocities, are measured using epoxy-coated hot-film sensors to evaluate drag reduction and controlling factors in suspension flows of high clay concentrations (4 and 8 g l^–1). The directly measured shear velocity in the viscous sublayer is found to be reduced by as much as 70% relative to the profile-derived shear velocity in the logarithmic layer. Drag reduction is found to increase with increasing clay concentration and decreasing flow strength. Density profile data indicate that the suspension flows were not stratified, and examinations of particle size distributions suggest that flocculation was not significant in causing the observed drag reduction. Measurements of the velocity profiles and of the shear velocity in the viscous sublayer indicate significant thickening of the inner wall layer and show turbulence damping in the viscous sublayer. These effects become stronger for higher concentrations and lower flow strength, suggesting that they are responsible for drag reduction in flows of clay suspension. Empirical relationships have been derived that can be used to predict the magnitude of drag reduction and the reduced shear stress in mud suspensions for both laboratory and field cohesive sediment transport studies.     

泥沙输移方程在地貌预测模型研究应用中的局限性

Sources of uncertainty or error that arise in attempting to scale up the results of laboratory-scale sediment transport studies for predictive modeling of geomorphic systems include: (i) model imperfection, (ii) omission of important processes, (iii) lack of knowledge of initial conditions, (iv) sensitivity to initial conditions, (v) unresolved heterogeneity, (vi) occurrence of external forcing, and (vii) inapplicability of the factor of safety concept. Sources of uncertainty that are unimportant or that can be controlled at small scales and over short time scales become important in large-scale applications and over long time scales. Control and repeatability, hallmarks of laboratory-scale experiments, are usually lacking at the large scales characteristic of geomorphology. Heterogeneity is an important concomitant of size, and tends to make large systems unique. Uniqueness implies that prediction cannot be based upon first-principles quantitative modeling alone, but must be a function of system history as well. Periodic data collection, feedback, and model updating are essential where site-specific prediction is required.     

地震震级预测的相关向量机模型

为了借助容易获取的地震相关因素间接预测地震震级,提出基于相关向量机（Relevance Vector Machine,RVM）方法的地震震级预测模型。通过样本学习建立地震震级与地震累积频度、累积释放能量、平均震级、b值、η值和相关区震级等6个主要影响因素之间的非线性映射关系,利用已知影响因素预测地震震级。结果表明:RVM模型预测结果均优于BP神经网络及SOM-BP神经网络预测结果;通过敏感因子分析比较各因素的敏感程度,b值和η值最为突出,在震级研究中应重点分析。综合分析,RVM模型具有精度高和离散性小等优点,对地震震级预测有较好的推广价值。     

基于PCA-DDA原理的砂土液化预测模型及应用

影响砂土液化的因素有很多,建立多指标的液化预测模型非常有必要。目前所有的多指标砂土液化预测模型,均默认选取的判别因子之间相互独立,不存在相关性,可能导致各判别因子之间存在信息叠加而发生误判。以唐山地震砂土液化的25个案例为样本,选取8个影响因素作为砂土液化预测的初始判别指标,首先采用主成分分析（PCA）对各判别指标进行分析,对存在相关性比较高的指标进行了降维处理。基于降维后的4个主成分换算得到新的样本数据,以18个案例为学习样本,建立主成分分析与距离判别分析（DDA）相结合的砂土液化预测模型。利用建立的预测模型对18个案例进行回判,结果全部正确。对其他7个案例的液化情况进行了预测,并与规范法、Seed方法、BP法、DDA法的判别结果进行分析比较,结果表明基于主成分分析与距离判别方法的砂土液化判别模型预测准确率为100%。将模型应用于工程实例,判别结果也与实际情况一致,表明该模型具有良好的预测功能,可在实际工程中应用。     

Predictive stability indicator: a novel approach to configuring a real‐time hybrid simulation

Real‐time hybrid simulation (RTHS) is an effective and versatile tool for the examination of complex structural systems with rate dependent behaviors. To meet the objectives of such a test, appropriate consideration must be given to the partitioning of the system into physical and computational portions (i.e., the configuration of the RTHS). Predictive stability and performance indicators (PSI and PPI) were initially established for use with only single degree‐of‐freedom systems. These indicators allow researchers to plan a RTHS, to quantitatively examine the impact of partitioning choices on stability and performance, and to assess the sensitivity of an RTHS configuration to de‐synchronization at the interface. In this study, PSI is extended to any linear multi‐degree‐of‐freedom (MDOF) system. The PSI is obtained analytically and it is independent of the transfer system and controller dynamics, providing a relatively easy and extremely useful method to examine many partitioning choices. A novel matrix method is adopted to convert a delay differential equation to a generalized eigenvalue problem using a set of vectorization mappings, and then to analytically solve the delay differential equations in a computationally efficient way. Through two illustrative examples, the PSI is demonstrated and validated. Validation of the MDOF PSI also includes comparisons to a MDOF dynamic model that includes realistic models of the hydraulic actuators and the control‐structure interaction effects. Results demonstrate that the proposed PSI can be used as an effective design tool for conducting successful RTHS. Copyright © 2016 John Wiley & Sons, Ltd     

基于多元逐步回归分析的煤储层含气量预测模型--以沁水盆地为例

以沁水盆地为例,运用多元逐步回归分析方法,建立了以Langmuir体积和含气饱和度为参数的含气量预测模型;复相关系数、F检验、t检验结果表明,该模型满足线性与方差齐性的假设,拟合效果较好。运用此模型,结合多因素权重分析确定的含气饱和度和实测的Langmuir体积数据,实现了沁水盆地山西组主煤层含气量预测。对比分析显示,该含气量预测模型有一定的可行性。