区域土壤环境地球化学研究——异常成因判别·环境质量·污染程度评价的思路与方法

从概念内涵和应用目标出发,认为土壤环境地球化学质量评价应该分为质量现状和污染程度两个方面.在此基础上探讨了区域地球化学资料在土壤环境现状质量评价、异常成因识别、污染元素累积速率和土壤污染程度评价研究的基本思路和方法.     

Modelling the effects of temperature and food on individual growth and reproduction of Daphnia and their consequences on the population level

Individual based simulations of population dynamics require the availability of growth models with adequate complexity. For this purpose a simple-to-use model (non-linear multiple regression approach) is presented describing somatic growth and reproduction of Daphnia as a function of time, temperature and food quantity. The model showed a good agreement with published observations of somatic growth (r² = 0.954, n = 88) and egg production (r² = 0.898, n = 35). Temperature is the main determinant of initial somatic growth and food concentration is the main determinant of maximal body length and clutch size. An individual based simulation was used to demonstrate the simultaneous effects of food and temperature on the population level. Evidently, both temperature and food supply affected the population growth rate but at food concentrations above approximately 0.4 mg Cl⁻¹ Scenedesmus acutus temperature appeared as the main determinant of population growth.

Four simulation examples are given to show the wide applicability of the model: (1) analysis of the correlation between population birth rate and somatic growth rate, (2) contribution of egg development time and delayed somatic growth to temperature-effects on population growth, (3) comparison of population birth rate in simulations with constant vs. decreasing size at maturity with declining food concentrations and (4) costs of diel vertical migration. Due to its plausible behaviour over a broad range of temperature (2–20 °C) and food conditions (0.1–4 mg Cl⁻¹) the model can be used as a module for more detailed simulations of Daphnia population dynamics under realistic environmental conditions.     

Identification of soil degradation during earthquake excitations by Bayesian inference

A Bayesian inference approach is introduced to identify soil degradation behaviours at four downhole array sites. The approach of inference is based on a parametric time‐varying infinite impulse response filter model. The approach is shown to be adaptive to the changes of filter parameters and noise amplitudes. Four sites, including the Lotung (Taiwan), Chiba (Japan), Garner Valley (California), and Treasure Island (California) sites with downhole seismic arrays are analysed. Our results show two major types of soil degradation behaviour: the well‐known strain‐dependent softening, and reduction in stiffness that is not instantaneously recoverable. It is also found that both types of soil degradation are more pronounced in sandy soils than in clayey soils. The mechanism for the second type of soil degradation is not yet clear to the authors and suggested to be further studied. Copyright © 2003 John Wiley & Sons, Ltd.     

System identification of instrumented bridge systems

Several recorded motions for seven bridge systems in California during recent earthquakes were analysed using parametric and non‐parametric system identification (SI) methods. The bridges were selected considering the availability of an adequate array of accelerometers and accounting for different structural systems, materials, geometry and soil types. The results of the application of SI methods included identification of modal frequencies and damping ratios. Excellent fits of the recorded motion in the time domain were obtained using parametric methods. The multi‐input/single‐output SI method was a suitable approach considering the instrumentation layout for these bridges. Use of the constructed linear filters for prediction purposes was also demonstrated for three bridge systems. Reasonable prediction results were obtained considering the various limitations of the procedure. Finally, the study was concluded by identifying the change of the modal frequencies and damping of a particular bridge system in time using recursive filters. Copyright © 2003 John Wiley & Sons, Ltd.     

System identification of linear structures based on Hilbert–Huang spectral analysis. Part 2: Complex modes

A method, based on the Hilbert–Huang spectral analysis, has been proposed by the authors to identify linear structures in which normal modes exist (i.e., real eigenvalues and eigenvectors). Frequently, all the eigenvalues and eigenvectors of linear structures are complex. In this paper, the method is extended further to identify general linear structures with complex modes using the free vibration response data polluted by noise. Measured response signals are first decomposed into modal responses using the method of Empirical Mode Decomposition with intermittency criteria. Each modal response contains the contribution of a complex conjugate pair of modes with a unique frequency and a damping ratio. Then, each modal response is decomposed in the frequency–time domain to yield instantaneous phase angle and amplitude using the Hilbert transform. Based on a single measurement of the impulse response time history at one appropriate location, the complex eigenvalues of the linear structure can be identified using a simple analysis procedure. When the response time histories are measured at all locations, the proposed methodology is capable of identifying the complex mode shapes as well as the mass, damping and stiffness matrices of the structure. The effectiveness and accuracy of the method presented are illustrated through numerical simulations. It is demonstrated that dynamic characteristics of linear structures with complex modes can be identified effectively using the proposed method. Copyright © 2003 John Wiley & Sons, Ltd.     

A neural network approach for structural identification and diagnosis of a building from seismic response data

This work presents a novel procedure for identifying the dynamic characteristics of a building and diagnosing whether the building has been damaged by earthquakes, using a back‐propagation neural network approach. The dynamic characteristics are directly evaluated from the weighting matrices of the neural network trained by observed acceleration responses and input base excitations. Whether the building is damaged under a large earthquake is assessed by comparing the modal parameters and responses for this large earthquake with those for a small earthquake that has not caused this building any damage. The feasibility of the approach is demonstrated through processing the dynamic responses of a five‐storey steel frame, subjected to different strengths of the Kobe earthquake, in shaking table tests. Copyright © 2002 John Wiley & Sons, Ltd.     

System identification of the Vincent Thomas suspension bridge using earthquake records

The Vincent Thomas Bridge in the Los Angeles metropolitan area, is a critical artery for commercial traffic flow in and out of the Los Angeles Harbor, and is at risk in the seismically active Southern California region, particularly because it straddles the Palos Verdes fault zone. A combination of linear and non‐linear system identification techniques is employed to obtain a complete reduced‐order, multi‐input–multi‐output (MIMO) dynamic model of the Vincent Thomas Bridge based on the dynamic response of the structure to the 1987 Whittier and 1994 Northridge earthquakes. Starting with the available acceleration measurements (which consists of 15 accelerometers on the bridge structure and 10 accelerometers at various locations on its base), an efficient least‐squares‐based time‐domain identification procedure is applied to the data set to develop a reduced‐order, equivalent linear, multi‐degree‐of‐freedom model. Although not the main focus of this study, the linear system identification method is also combined with a non‐parametric identification technique, to generate a reduced‐order non‐linear mathematical model suitable for use in subsequent studies to predict, with good fidelity, the total response of the bridge under arbitrary dynamic environments. Results of this study yield measurements of the equivalent linear modal properties (frequencies, mode shapes and non‐proportional damping) as well as quantitative measures of the extent and nature of non‐linear interaction forces arising from strong ground shaking. It is shown that, for the particular subset of observations used in the identification procedure, the apparent non‐linearities in the system restoring forces are quite significant, and they contribute substantially to the improved fidelity of the model. Also shown is the potential of the identification technique under discussion to detect slight changes in the structure's influence coefficients, which may be indicators of damage and degradation in the structure being monitored. Difficulties associated with accurately estimating damping for lightly damped long‐span structures from their earthquake response are discussed. The technical issues raised in this paper indicate the need for added spatial resolution in sensor instrumentation to obtain identified mathematical models of structural systems with the broadest range of validity. Copyright © 2003 John Wiley & Sons, Ltd.     

路用探地雷达的应用技术研究进展

有效、无损、快捷、简便是公路检测技术发展的方向，当前国内外先进的浅层勘探技术——路用探地雷达检测，以其无损、快捷以及浅层高分辨率的优势被迅速应用于公路检测。本文对近年来路用探地雷达技术的发展及应用情况进行了介绍，详细分析了探地雷达的工作原理、系统组成结构。就探地雷达在公路建设、维护过程中的应用情况进行了系统总结。     

The identification and criteria of short-term seismicity gap before a great earthquake

ＴｈｅｉｄｅｎｔｉｆｉｃａｔｉｏｎａｎｄｃｒｉｔｅｒｉａｏｆｓｈｏｒｔｔｅｒｍｓｅｉｓｍｉｃｉｔｙｇａｐｂｅｆｏｒｅａｇｒｅａｔｅａｒｔｈｑｕａｋｅＪＩＮＧＱＵＡＮＣＡＯ（曹井泉）ＪＩＡＬＩＮＳＵＮ（孙加林）ＹＩＹＡＮＧ（杨毅）Ｓｅｉｓｍｏｌ...     

结构参数未知条件下的地震动反演研究

本文运用复合反演的观点研究结构参数未知条件下的地震动反演问题。根据地震作用的力学特性，将其具体化为估计输入的修正条件，文中给出了一类反演算法。理论分析及算例表明，该算法具有稳定的收敛特性以及良好的反演效果。