材料三维显微组织形态研究：进展与展望

材料三维显微组织形态的实验观测和科学定量表征是材料学科的核心问题,是材料科学研究中一个无法回避的且又相当具有挑战性的难题。本文就材料三维显微组织几何形态观测和表征中的一些基本概念、研究方法及其应用进展、存在问题与可能解决途径进行了讨论,就我国在该领域中的下一步发展战略提出了若干意见。     

地震预报新途径的探索

为了探索地震预报的新途径，本文分析了各种现有主要地震前兆。尽管它们在地震预报工作中曾经起过并且今后还将继续起着重要作用，但是，这些前兆与地震的发生都不存在唯一性的对应关系。这表明，到目前为止，还没有找出这些地震前兆和地震孕育过程之间真正内在的本质联系。本文从震源介质的固有特征及非线性系统不稳定性问题的本质出发，借鉴经典力学中的量纲分析与现代信息论的概念，提出了一个表征孕震系统不稳定性逼近程度的新的无量纲参数Ｙ，称之为ＬＵＲＲ（加载／卸载响应比）。ＬＵＲＲ定义为式中，Ｘ＋和Ｘ－分别是孕震系统在加载和卸载时的响应率。     

Investigating dynamic mechanisms of geological phenomena using methodology of computational geosciences: An example of equal-distant mineralization in a fault

This paper presents a research methodology associated with approximately a decade old computa- tional geosciences. To demonstrate how it can be used to investigate the dynamic mechanisms of geological phenomenon, we use as an example the equal-distant distribution of gold deposits in a three-dimensional permeable fault within the Yilgarn Craton, Western Australia. The related numerical results demonstrate that: (1) convective pore-fluid flow in fluid-saturated porous media is the control- ling dynamic mechanism leading to the equal-distant distribution of gold deposits along the fault; (2) the main characteristic of the new methodology is to change the traditionally used empirical, descrip- tive and qualitative methodology into the fundamentally scientific principles based predictive and quantitative methodology. Thus, this new methodology provides a modern scientific research tool for investigating the dynamic mechanisms associated with observed geological phenomena in nature.     

A methodology for quantifying the value of spatial information for dynamic Earth problems

We develop a methodology for assessing the value of information (VOI) from spatial data for groundwater decisions. Two sources of uncertainty are the focus of this VOI methodology: the spatial heterogeneity (how it influences the hydrogeologic response of interest) and the reliability of geophysical data (how they provide information about the spatial heterogeneity). An existing groundwater situation motivates and in turn determines the scope of this research. The objectives of this work are to (1) represent the uncertainty of the dynamic hydrogeologic response due to spatial heterogeneity, (2) provide a quantitative measure for how well a particular information reveals this heterogeneity (the uncertainty of the information) and (3) use both of these to propose a VOI workflow for spatial decisions and spatial data. The uncertainty of the hydraulic response is calculated using many Earth models that are consistent with the a priori geologic information. The information uncertainty is achieved quantitatively through Monte Carlo integration and geostatistical simulation. Two VOI results are calculated which demonstrate that a higher VOI occurs when the geophysical attribute (the data) better discriminates between geological indicators. Although geophysical data can only indirectly measure static properties that may influence the dynamic response, this transferable methodology provides a framework to estimate the value of spatial data given a particular decision scenario.     

An assessment of using subsampling method in selection of a flood frequency distribution

In flood frequency analysis, a suitable probability distribution function is required in order to establish the flood magnitude-return period relationship. Goodness of fit (GOF) techniques are often employed to select a suitable distribution function in this context. But they have been often criticized for their inability to discriminate between statistical distributions for the same application. This paper investigates the potential utility of subsampling, a resampling technique with the aid of a GOF test to select the best distribution for frequency analysis. The performance of the methodology is assessed by applying the methodology to observed and simulated annual maximum (AM) discharge data series. Several AM series of different record lengths are used as case studies to determine the performance. Numerical analyses are carried out to assess the performance in terms of sample size, subsample size and statistical properties inherent in the AM data series. The proposed methodology is also compared with the standard Anderson–Darling (AD) test. It is found that the methodology is suitable for a longer data series. A better performance is obtained when the subsample size is taken around half of the underlying data sample. The methodology has also outperformed the standard AD test in terms of effectively discriminating between distributions. Overall, all results point that the subsampling technique can be a promising tool in discriminating between distributions.     

Integration of remote sensing data into hydrological models for reservoir management

Abstract

The purpose of this paper is to present the methodology set up to derive catchment soil moisture from Earth Observation (EO) data using microwave spaceborne Synthetic Aperture Radar (SAR) images from ERS satellites and to study the improvements brought about by an assimilation of this information into hydrological models. The methodology used to derive EO data is based on the appropriate selection of land cover types for which the radar signal is mainly sensitive to soil moisture variations. Then a hydrological model is chosen, which can take advantage of the new information brought by remote sensing. The assimilation of soil moisture deduced from EO data into hydrological models is based principally on model parameter updating. The main assumption of this method is that the better the model simulates the current hydrological system, the better the following forecast will be. Another methodology used is a sequential one based on Kalman filtering. These methods have been put forward for use in the European AIMWATER project on the Seine catchment upstream of Paris (France) where dams are operated to alleviate floods in the Paris area.     

A performance-based adaptive methodology for the seismic evaluation of multi-span simply supported deck bridges

A performance-based adaptive methodology for the seismic assessment of highway bridges is proposed. The proposed methodology is based on an Inverse (I), Adaptive (A) application of the Capacity Spectrum Method (CSM), with the capacity curve of the bridge derived through a Displacement-based Adaptive Pushover (DAP) analysis. For this reason, the acronym IACSM is used to identify the proposed methodology. A number of Performance Levels (PLs), for which the seismic vulnerability and seismic risk of the bridge shall be evaluated, are identified. Each PL is associated to a number of Damage States (DSs) of the critical members of the bridge (piers, abutments, joints and bearing devices). The IACSM provides the earthquake intensity level (PGA) corresponding to the attainment of the selected DSs, using over-damped elastic response spectra as demand curves. The seismic vulnerability of the bridge is described by means of fragility curves, derived based on the PGA values associated to each DS. The seismic risk of the bridge is evaluated as convolution integral of the product between the fragility curves and the seismic hazard curve of the bridge site. In this paper, the key aspects and basic assumptions of the proposed methodology are presented first. The IACSM is then applied to nine existing simply supported deck bridges, characterized by different types of piers and bearing devices. Finally, the IACSM predictions are compared with the results of nonlinear response time-history analysis, carried out using a set of seven ground motions scaled to the expected PGA values.     

Large-Scale Mapping of Hard-Rock Aquifer Properties Applied to Burkina Faso

A country-scale (1:1,000,000) methodology has been developed for hydrogeologic mapping of hard-rock aquifers (granitic and metamorphic rocks) of the type that underlie a large part of the African continent. The method is based on quantifying the “useful thickness” and hydrodynamic properties of such aquifers and uses a recent conceptual model developed for this hydrogeologic context. This model links hydrodynamic parameters (transmissivity, storativity) to lithology and the geometry of the various layers constituting a weathering profile. The country-scale hydrogeological mapping was implemented in Burkina Faso, where a recent 1:1,000,000-scale digital geological map and a database of some 16,000 water wells were used to evaluate the methodology.     

The Kozeny‐Carman Equation with a Percolation Threshold

A procedure has been developed for calculating permeability (k) from the Kozeny‐Carman equation, a procedure that links ideas from percolation theory with the ideas of Koltermann and Gorelick (1995) and Esselburn et al. (2011) . The approach focuses on the proportion of coarser pores that are occupied by finer sediments relative to a percolation threshold proportion (ω_c). If the proportion occupied is below ω_c, then the unoccupied coarser pores percolate. Otherwise they do not percolate. Following the ideas of Koltermann and Gorelick (1995) , the effective grain‐size term in the Kozeny‐Carman equation is calculated using the geometric mean if the unoccupied coarse pores percolate, and using the harmonic mean if otherwise. Following ideas of Esselburn et al. (2011) , this approach is implemented by evaluating the potential for grains in each size category to occupy pores among sediment of each larger‐size category. Application of these ideas to physical sediment models for sands and gravels, which have known k, indicates that a threshold does indeed exist. Results also suggest that the Kozeny‐Carman equation is robust and gives representative values for k, even though ω_c is not precisely known.     

Earthquake risk assessment of lifelines

This paper presents the RISK-UE methodology for the seismic risk assessment of utility systems (potable water, waste-water, gas system, telecommunication, electric power) and transportation infrastructures (port, airport, road and railway system). The proposed methodology provides a uniform basis for the reduction of the consequences of lifeline damages in urban areas and an efficient mitigation strategy and prioritization policies for pre-earthquake and post earthquake actions. A detailed inventory for every element at risk together with a reliable seismic hazard assessment, appropriate selection of fragility models, estimation of the “global value” and economical impact of lifeline damages and losses are the main steps of the proposed methodology. The consideration of European distinctive features of lifelines and utility systems in the construction of seismic scenarios and the proposition of fragility curves are among the basic aims of the proposed methodology. Different modules of the methodology were applied in seven pilot cities (Thessaloniki, Catania, Nice, Bucharest, Sofia, Barcelona, Bitola). We present herein few representative examples (case studies) in order to illustrate the methodology and to prove its efficiency.     

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational ℓ1-Norm Regularization in the Derivative Domain

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall), and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients (called ?₁-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a data base of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.     

Incorporating the spatio-temporal distribution of rainfall and basin geomorphology into nonlinear analyses of streamflow dynamics

Many recent studies have been devoted to the investigation of the nonlinear dynamics of rainfall or streamflow series based on methods of dynamical systems theory. Although finding evidence for the existence of a low-dimensional deterministic component in rainfall or streamflow is of much interest, not much attention has been given to the nonlinear dependencies of the two and especially on how the spatio-temporal distribution of rainfall affects the nonlinear dynamics of streamflow at flood time scales. In this paper, a methodology is presented which simultaneously considers streamflow series, spatio-temporal structure of precipitation and catchment geomorphology into a nonlinear analysis of streamflow dynamics. The proposed framework is based on “hydrologically-relevant” rainfall-runoff phase-space reconstruction acknowledging the fact that rainfall-runoff is a stochastic spatially extended system rather than a deterministic multivariate one. The methodology is applied to two basins in Central North America using 6-hour streamflow data and radar images for a period of 5 years. The proposed methodology is used to: (a) quantify the nonlinear dependencies between streamflow dynamics and the spatio-temporal dynamics of precipitation; (b) study how streamflow predictability is affected by the trade-offs between the level of detail necessary to explain the spatial variability of rainfall and the reduction of complexity due to the smoothing effect of the basin; and (c) explore the possibility of incorporating process-specific information (in terms of catchment geomorphology and an a priori chosen uncertainty model) into nonlinear prediction. Preliminary results are encouraging and indicate the potential of using the proposed methodology to understand via nonlinear analysis of observations (i.e., not based on a particular rainfall-runoff model) streamflow predictability and limits to prediction as a function of the complexity of spatio-temporal forcing relative to basin geomorphology.     

Model updating of a bridge structure using vibration test data based on GMPSO and BPNN: case study

Model updating issues with high-dimensional and strong-nonlinear optimization processes are still unsolved by most optimization methods.In this study,a hybrid methodology that combines the Gaussian-white-noise-mutation particle swarm optimization(GMPSO),back-propagation neural network(BPNN)and Latin hypercube sampling(LHS)technique is proposed.In this approach,as a meta-heuristic algorithm with the least modification to the standard PSO,GMPSO simultaneously offers convenient programming and good performance in optimization.The BPNN with LHS establishes the meta-models for FEM to accelerate efficiency during the updating process.A case study of the model updating of an actual bridge with no distribution but bounded parameters was carried out using this methodology with two different objective functions.One considers only the frequencies of the main girder and the other considers both the frequencies and vertical displacements of typical points.The updating results show that the methodology is a sound approach to solve an actual complex bridge structure and offers good agreement in the frequencies and mode shapes of the updated model and test data.Based on the shape comparison of the main girder at the finished state with different objective functions,it is emphasized that both the dynamic and static responses should be taken into consideration during the model updating process.     

Modeling locally varying anisotropy of CO2 emissions in the United States

In a spatial property modeling context, the variables of interest to be modeled often display complex nonlinear features. Techniques to incorporate these nonlinear features, such as multiple point statistics or cummulants, are often complex with input parameters that are difficult to infer. The methodology proposed in this paper uses a classical vector-based definition of locally varying anisotropy to characterize nonlinear features and incorporate locally varying anisotropy into numerical property models. The required input is an exhaustive field of anisotropy orientation and magnitude. The methodology consists of (1) using the shortest path distance between locations to define the covariance between points in space (2) multidimensional scaling of the domain to ensure positive definite kriging equations and (3) estimation or simulation with kriging or sequential Gaussian simulation. The only additional parameter required when kriging or simulating with locally varying anisotropy is the number of dimensions to retain in multidimensional scaling. The methodology is demonstrated on a CO₂ emissions data set for the United States in 2002 and shows an improvement in cross validation results as well as a visual reproduction of nonlinear features.     

第13届世界地震工程大会概述

介绍了第13届世界地震工程大会的概况。内容涉及大会报告和6个专题(工程地震、岩土地震工程、结构工程、生命线工程、综合减灾与社会经济问题以及近期地震的经验教训与地震工程实践)。作者还对目前国际范围内的地震工程最新进展及其发展趋势作以论述。最后，根据对本届世界地震工程大会的认识，作者对如何办好由中国地震局主办2008年在我国北京举行的第14届世界地震工程大会谈了一些初步的看法。笔者愿以此文使国内同行对本届大会有一个概略的了解。     

Modified hydrograph method for arid regions

There is a real need for more research on regionalization of flood estimation methods in arid zones. Such estimations are important because reliable long‐term storm rainfall and corresponding runoff measurements are commonly unavailable. This is the situation in many parts of the Kingdom of Saudi Arabia. Hence, it is necessary to develop a new approach, one that suits the conditions found in the Kingdom, which depend on available, but incomplete measurements and catchment morphological features. In this paper, a modified methodology based on the classical Snyder approach is proposed and it is referred to as the Saudi Geological Survey (SGS) approach in order to reflect works of this kind within the Survey. The basis of the methodology has two phases, namely, logical and empirical. The former phase is valid for any part of the world whether humid or arid, but the latter phase is location specific, which in the case of this paper, is the Arabian Peninsula. The application of the methodology is presented for Wadi Baysh, a major wadi in the south‐western part of the Kingdom. Furthermore, a synthetic unit hydrograph (UH) methodology based on a Gamma distribution function is also presented with applications to some of the Wadi Baysh sub‐basins. For this purpose, a dimensionless UH has been obtained, which is special for the area. Copyright © 2007 John Wiley & Sons, Ltd.     

Linear geophysical inversion via the discrete cosine pseudo‐inverse: application to potential fields

In this paper, we present a methodology to perform geophysical inversion of large‐scale linear systems via a covariance‐free orthogonal transformation: the discrete cosine transform. The methodology consists of compressing the matrix of the linear system as a digital image and using the interesting properties of orthogonal transformations to define an approximation of the Moore–Penrose pseudo‐inverse. This methodology is also highly scalable since the model reduction achieved by these techniques increases with the number of parameters of the linear system involved due to the high correlation needed for these parameters to accomplish very detailed forward predictions and allows for a very fast computation of the inverse problem solution. We show the application of this methodology to a simple synthetic two‐dimensional gravimetric problem for different dimensionalities and different levels of white Gaussian noise and to a synthetic linear system whose system matrix has been generated via geostatistical simulation to produce a random field with a given spatial correlation. The numerical results show that the discrete cosine transform pseudo‐inverse outperforms the classical least‐squares techniques, mainly in the presence of noise, since the solutions that are obtained are more stable and fit the observed data with the lowest root‐mean‐square error. Besides, we show that model reduction is a very effective way of parameter regularisation when the conditioning of the reduced discrete cosine transform matrix is taken into account. We finally show its application to the inversion of a real gravity profile in the Atacama Desert (north Chile) obtaining very successful results in this non‐linear inverse problem. The methodology presented here has a general character and can be applied to solve any linear and non‐linear inverse problems (through linearisation) arising in technology and, particularly, in geophysics, independently of the geophysical model discretisation and dimensionality. Nevertheless, the results shown in this paper are better in the case of ill‐conditioned inverse problems for which the matrix compression is more efficient. In that sense, a natural extension of this methodology would be its application to the set of normal equations.     

A comprehensive and systematic approach to developing and documenting conceptual models of contaminant release and migration at the Hanford Site

The U. S. Department of Energys Richland Operations Office has initiated efforts to adapt and implement the features, events, and processes (FEP) methodology used in scenario development for nuclear waste disposal programs to the environmental management and remediation problems facing the Hanford site. These efforts have shown that modification of the FEPs methodology to incorporate the use of process relationship diagrams (PRD) is effective in facilitating the development of conceptual models and selection of potentially relevant factors (i.e., FEPs) to be incorporated into a specific environmental assessment. In adopting this methodology for Hanford, a master PRD was created to provide a structure to identify these factors and to illustrate the relationships among them. The organizational framework of the master PRD was developed to match the organization of current Hanford site-wide environmental assessment activities and to facilitate screening of the FEPs relevant to the specific assessments needed for the site.     

Statistical estimation of the relative efficiency of natural attenuation mechanisms in contaminated aquifers

Using monitored natural attenuation is an increasingly popular strategy for dealing with contaminated aquifers. This paper provides a statistical methodology for the estimation of the relative efficiency of natural attenuation mechanisms. The methodology provides estimates, with associated measures of uncertainty, of the relative efficiency of four types of bio-degradation (oxidation using oxygen as the electron-acceptor, denitrification, iron reduction and sulfate reduction). A data set from Trecate, Italy, is analysed using the methodology. The analysis shows that sulfate is the main cause of hydrocarbon removal on this site. It is also seen that oxidation using oxygen seems to be more preferential than the other reactions, in the sense that this reaction is relatively more efficient than other reactions at locations where the hydrocarbon concentration is low.