Monitoring of structural systems by using frequency data

The present work evaluates the possibility of using dynamic data to assess structural integrity. It addresses the problem of understanding when it is sufficient to measure and use only natural frequencies, thus avoiding the need to measure modal shapes. The classic problem of detecting damage in beams, or beam assemblies, due to concentrated cracks, or damage spread over a structural member is dealt with. Damage is represented as a decrease in stiffness and linear behaviour before and after the event assumed to have caused damage is considered. Damage is restricted to a few unknown sections or elements, so that only the modification of few parameters of the system need to be determined. This study thus rejects assumptions unrelated to the physical aspects of the problem, in contrast to many papers on the subject. The amount of data to locate and quantify damage correctly is discussed; general considerations lead to the conclusion that a unique and reliable estimate of the damage can be obtained using only few additional frequency data with respect to the number of damaged zones. Continuous and discrete (finite element) models are examined. Finally the paper considers the applications to both analytical and experimental data of the procedure developed, which takes account of the peculiar characteristics of damage detection problem. Copyright © 1999 John Wiley & Sons, Ltd.     

Site-specific seismic design of damage tolerant structural systems using a novel concept

Designing more seismic load-tolerant structures is one of the major challenges of the world communities. It is due to the inability of the profession to predict future design earthquake time histories at a site compounded by the failure to appropriately incorporate uncertainties in other design variables and structural behavior just before failure. A site-specific method is proposed to generate a suite of ground excitation time histories and a novel risk estimation is developed considering major sources of nonlinearity and uncertainty. For wider application and acceptance, the risk evaluation procedure essentially consists of few deterministic time domain finite element analyses. The procedure is verified and showcased by estimating risks associated with three buildings designed by professional experts in the Los Angeles area satisfying the post-Northridge design criteria for the overall lateral deflection and inter-story drift. The accuracy of the estimated risk is verified using the Monte Carlo simulation technique. In all cases, the probabilities of collapse are found to satisfy the current code requirements. The spread in the reliability indexes for each building for both limit states cannot be overlooked, indicating the significance of the frequency contents of the time histories. The inter-story drift is found to be more critical than the overall lateral displacement. The reliability indexes for both limit states are similar only for few cases. The authors believe that they proposed an alternative to the classical random vibration and simulation approaches. The proposed site-specific seismic safety assessment procedure can be used by practicing engineers for routine applications.     

On seismic classification using non-stationary models and a definition of complexity

A non-stationary stochastic model is proposed for seismic records of P-waves from underground nuclear explosions and natural earthquakes. When estimating the parameters of interest an asymptotically “efficient” procedure is described and its statistical properties are derived. Numerical results are also provided in support of the model.By considering the relevant parameters in the model, two discriminating procedures are described and one is illustrated numerically using available records. Based on these parameters, “complexity” is defined and its relation to the best linear discriminant function is pointed out.     

Identification of linear structural systems using earthquake-induced vibration data

This paper addresses the issue of system identification for linear structural systems using earthquake induced time histories of the structural response. The proposed methodology is based on the Eigensystem Realization Algorithm (ERA) and on the Observer/Kalman filter IDentification (OKID) approach to perform identification of structural systems using general input–output data via Markov parameters. The efficiency of the proposed technique is shown by numerical examples for the case of eight-storey building finite element models subjected to earthquake excitation and by the analysis of the data from the dynamic response of the Vincent-Thomas cable suspension bridge (Long Beach, CA) recorded during the Whittier and the Northridge earthquakes. The effects of noise in the measurements and of inadequate instrumentation are investigated. It is shown that the identified models show excellent agreement with the real systems in predicting the structural response time histories when subjected to earthquake-induced ground motion. Copyright © 1999 John Wiley & Sons, Ltd.     

一种新的巨型-子结构控制体系在非平稳地震作用下的反应分析

本文研究了一种新的控制结构体系——巨型-子结构控制体系。根据控振结构体系的特点和通过对该结构的变形分析:主框架采用弯曲模型,而次框架采用剪切模型的集中质量模型,据此推导了控振结构的运动方程。利用复模态方法,对它和普通巨型框架结构进行了2种非平稳地震作用下的对比分析。研究结构表明:这种新的结构体系能有效控制地震响应,结构安全性和舒适度均有明显提高。     

Modeling non-stationary extreme waves using a point process approach and wavelets

In the present paper a statistical model for extreme value analysis is developed, considering seasonality. The model is applied to significant wave height data from the N. Aegean Sea. To build this model, a non-stationary point process is used, which incorporates apart from a time varying threshold and harmonic functions with a period of one year, a component μ _w(t) estimated through the wavelet transform. The wavelet transform has a dual role in the present study. It detects the significant “periodicities” of the signal by means of the wavelet global and scale-averaged power spectra and then is used to reconstruct the part of the time series, μ _w(t), represented by these significant features. A number of candidate models, which incorporate μ _w(t) in their location and scale parameters are tried. To avoid overparameterisation, an automatic model selection procedure based on the Akaike information criterion is carried out. The best obtained model is graphically evaluated by means of diagnostic plots. Finally, “aggregated” return levels with return periods of 20, 50 and 100 years, as well as time-dependent quantiles are estimated, combining the results of the wavelet analysis and the Poisson process model, identifying a significant reduction in return level estimation uncertainty, compared to more simple non-stationary models.     

Statistical insight into constant-ductility design using a non-stationary earthquake ground motion model

A recently developed earthquake ground motion model non-stationary in both intensity and frequency content is validated at the inelastic Single-Degree-Of-Freedom (SDOF) structural response level. For the purpose of this study, the earthquake model is calibrated for two actual earthquake records. The objective of a constant (or target) displacement ductility used in conventional earthquake-resistant design is examined from the statistical viewpoint using this non-stationary earthquake model. The non-linear hysteretic structural behaviour is modelled using several idealized hysteretic SDOF structural models. Ensemble-average inelastic response spectra corresponding to various inelastic SDOF response (or damage) parameters and conditioned on a constant displacement ductility response are derived from the two identified stochastic ground motion models. The effects of the type of hysteretic behaviour, the structural parameters, the target displacement ductility factor, and the ground motion model on the statistics of the inelastic response parameters are thoroughly investigated. The results of this parametric study shed further light on the proper interpretation and use of inelastic response or damage parameters in earthquake-resistant design in order to achieve the desirable objective of ‘constant-damage design’. © 1997 by John Wiley & Sons, Ltd.     

Hybrid structural control using viscoelastic dampers and active control systems

Viscoelastic (VE) dampers and active control (AC) systems are studied together as a hybrid system for their effectiveness in reducing the response of seismic structures. VE dampers have properties which are both frequency and temperature-dependent. On the other hand, AC systems for seismic structures require rather large control forces in order to be effective. The possibility of combining VE dampers and AC systems to improve the performance of both systems is examined. It is found that for the same response reduction, the addition of VE dampers to an AC system reduces the required control forces considerably, which reduces the cost of the AC system. The addition of the AC system helps improve the velocity performance of VE dampers and considerably reduces the possibility of shear failure of the viscoelastic material. Two procedures for evaluating the damping effect of the VE dampers are suggested which can be applied to either shear-type or framed structures. Two control algorithms based on drift and velocity/acceleration feedback are compared to existing algorithms. A method of determining the weighting matrices of an AC system is presented which reduces the required control forces for certain control algorithms.     

Partial eigensolution of damped structural systems by Arnoldi's method

An efficient numerical algorithm is developed to solve the quadratic eigenvalue problems arising in the dynamic analysis of damped structural systems. The algorithm can even be applied to structural systems with non-symmetric matrices. The algorithm is based on the use of Arnoldi's method to generate a Krylov subspace of trial vectors, which is then used to reduce a large eigenvalue problem to a much smaller one. The reduced eigenvalue problem is solved and the solutions are used to construct approximate solutions to the original large system. In the process, the algorithm takes full advantage of the sparseness and symmetry of the system matrices and requires no complex arithmetic, therefore, making it very economical for use in solving large problems. The numerical results from test examples are presented to demonstrate that a large fraction of the approximate solutions calculated are very accurate, indicating that the algorithm is highly effective for extracting a number of vibration modes for a large dynamic system, whether it is lightly or heavily damped.     

Locating anomalies by gravity gradiometry using the matched filter with a probabilistic assessment

The matched filter can be used to identify the location of a specific signal embedded in background correlated noise. The maximum filter output indicates the likely location and, with appropriate statistical assumptions on the noise, it also serves as a test statistic in the probabilistic evaluation of the filter’s performance. Different setups of the Neyman-Pearson statistical hypothesis test yield predictions of either the probability of a miss or that of a false alarm. The needed statistics of the maximum filter output are properly obtained using the distribution of order statistics. Through Monte Carlo simulations, we analyzed the ability of the matched filter to identify a sub-surface anomaly in typically correlated gravity fields using observations of elements of the gravity gradient tensor. We also evaluated the reliability of the hypothesis testing and the associated predicted probabilities of misses and false alarms. Our simulations and statistical analyses confirm that the power of the tests increases as the signal strength increases and as more gradient tensor components per observation point are included. We also found that the hypothesis test that is designed to predict the probability of a miss is more robust and powerful than the one for predicting a false alarm. Moreover, the probability of a miss is somewhat smaller than the probability of a false alarm under otherwise equal circumstances.     

Ground-roll attenuation using a 2D time-derivative filter

We present a new filtering method for the attenuation of ground-roll. The method is based on the application of a bi-dimensional filter for obtaining the time-derivative of the seismograms. Before convolving the filter with the input data matrix, the normal moveout correction is applied to the seismograms with the purpose of flattening the reflections. The method can locally attenuate the amplitude of data of low frequency (in the ground-roll and stretch normal moveout region) and enhance flat events (reflections). The filtered seismograms can reveal horizontal or sub-horizontal reflections while vertical or sub-vertical events, associated with ground-roll, are attenuated. A regular set of samples around each neighbourhood data sample of the seismogram is used to estimate the time-derivative. A numerical approximation of the derivative is computed by taking the difference between the interpolated values calculated in both the positive and the negative neighbourhood of the desired position. The coefficients of the 2D time-derivative filter are obtained by taking the difference between two filters that interpolate at positive and negative times. Numerical results that use real seismic data show that the proposed method is effective and can reveal reflections masked by the ground-roll. Another benefit of the method is that the stretch mute, normally applied after the normal moveout correction, is unnecessary. The new filtering approach provides results of outstanding quality when compared to results obtained from the conventional FK filtering method.     

Improving hydrodynamic modeling of river networks by incorporating data assimilation using a particle filter

Numerical modeling is a well-recognized method for studying the hydrodynamic processes in river networks. Multi-source measurements also offer abundant information on the patterns and mechanisms within the processes. Therefore, improving hydrodynamic modeling of river networks through the use of data assimilation techniques has become a hot research topic in recent years. The particle filter (PF) is a commonly used data assimilation method and has been proven to be applicable to various nonlinear and non-Gaussian models. In the current study, an improved numerical hydrodynamic model for large-scale river networks is established by incorporating the advanced PF algorithm. Furthermore, the PF method based on the Gaussian likelihood function (GLF) and the method based on the Cauchy likelihood function (CLF) are compared for a complex river network scenario. The feasibility of the PF-based methods was evaluated through application to the Yangtze-Dongting River-lake Network (YDRN) by assimilating water stage data collected at six hydrometric stations during the entire hydrodynamic process in 2003. Additionally, the parameters used in the likelihood function, which affect the assimilation performance, also were explored in the current study. The study results found that the accuracy of the model-derived water stage data was improved when the PF-based methods are utilized, with improvement not only at the data assimilation (calibration) sites but also at three hydrometric stations not used in the data assimilation (i.e., verification sites). The highest average Nash-Sutcliffe Efficiency result for the six assimilation sites were 0.98 while the lowest summed root-mean-square-error result was 1.801 m. The comparison results also indicated that the CLF-based PF outperformed the GLF-based PF when high-accuracy observed data are available. Specifically, the CLF can effectively resolve the filtering failure problem and the dispersion problem of PFs, and further improve the accuracy of the filtering results for a river network scenario. In summary, the CLF-based PF method along with high-accuracy observation data shows promise to provide reliable reference and technical support for hydrodynamic modeling of large-scale river networks.     

On‐line identification of non‐linear hysteretic structural systems using a variable trace approach

In this paper, an adaptive on‐line parametric identification algorithm based on the variable trace approach is presented for the identification of non‐linear hysteretic structures. At each time step, this recursive least‐square‐based algorithm upgrades the diagonal elements of the adaptation gain matrix by comparing the values of estimated parameters between two consecutive time steps. Such an approach will enforce a smooth convergence of the parameter values, a fast tracking of the parameter changes and will remain adaptive as time progresses. The effectiveness and efficiency of the proposed algorithm is shown by considering the effects of excitation amplitude, of the measurement units, of larger sampling time interval and of measurement noise. The cases of exact‐, under‐, over‐parameterization of the structural model have been analysed. The proposed algorithm is also quite effective in identifying time‐varying structural parameters to simulate cumulative damage in structural systems. Copyright © 2001 John Wiley & Sons, Ltd.     

Extended Kalman filter for material parameter estimation in nonlinear structural finite element models using direct differentiation method

This paper presents a novel nonlinear finite element (FE) model updating framework, in which advanced nonlinear structural FE modeling and analysis techniques are used jointly with the extended Kalman filter (EKF) to estimate time‐invariant parameters associated to the nonlinear material constitutive models used in the FE model of the structural system of interest. The EKF as a parameter estimation tool requires the computation of structural FE response sensitivities (total partial derivatives) with respect to the material parameters to be estimated. Employing the direct differentiation method, which is a well‐established procedure for FE response sensitivity analysis, facilitates the application of the EKF in the parameter estimation problem. To verify the proposed nonlinear FE model updating framework, two proof‐of‐concept examples are presented. For each example, the FE‐simulated response of a realistic prototype structure to a set of earthquake ground motions of varying intensity is polluted with artificial measurement noise and used as structural response measurement to estimate the assumed unknown material parameters using the proposed nonlinear FE model updating framework. The first example consists of a cantilever steel bridge column with three unknown material parameters, while a three‐story three‐bay moment resisting steel frame with six unknown material parameters is used as second example. Both examples demonstrate the excellent performance of the proposed parameter estimation framework even in the presence of high measurement noise. Copyright © 2015 John Wiley & Sons, Ltd.     

Time delayed control of structural systems

Time delays are ubiquitous in control systems. They usually enter because of the sensors and actuators used in them. Traditionally, time delays have been thought to have a deleterious effect on both the stability and the performance of controlled systems, and much research has been done in attempting to eliminate them, compensate for them, or nullify their presence. In this paper we take a different view. We investigate whether purposefully injected time delays can be used to improve both the system's stability and performance. Our analytical, numerical, and experimental investigation shows that this can indeed be done. Analytical results of the effects of time delays on collocated and non‐collocated control of classically damped and non‐classically damped systems are given. Experimental and numerical results confirm the theoretical expectations. Issues of system uncertainties and robustness of time delayed control are addressed. The results are of practical value in improving the performance and stability of controllers because these characteristics (performance and stability) improve dramatically with the intentional injection of small time delays in the control system. The introduction of such time delays constitutes a ‘minimal change’ to a controller already installed in a structural system for active control. Hence, from a practical standpoint, time delays can be implemented in a nearly costless and highly reliable manner to improve control performance and stability, an aspect that cannot be ignored when dealing with the economics and safety of large structural systems subjected to strong earthquake ground shaking. Copyright © 2003 John Wiley & Sons, Ltd.     

Estimation of a non-stationary prior covariance from seismic data

Non-stationarity in statistical properties of the subsurface is often ignored. In a classical linear Bayesian inversion setting of seismic data, the prior distribution of physical parameters is often assumed to be stationary. Here we propose a new method of handling non-stationarity in the variance of physical parameters in seismic data. We propose to infer the model variance prior to inversion using maximum likelihood estimators in a sliding window approach. A traditional, and a localized shrinkage estimator is defined for inferring the prior model variance. The estimators are assessed in a synthetic base case with heterogeneous variance of the acoustic impedance in a zero-offset seismic cross section. Subsequently, this data is inverted for acoustic impedance using a non-stationary model set up with the inferred variances. Results indicate that prediction as well as posterior resolution is greatly improved using the non-stationary model compared with a common prior model with stationary variance. The localized shrinkage predictor is shown to be slightly more robust than the traditional estimator in terms of amplitude differences in the variance of acoustic impedance and size of local neighbourhood. Finally, we apply the methodology to a real data set from the North Sea basin. Inversion results show a more realistic posterior model than using a conventional approach with stationary variance.     

近断层地震动的频谱周期参数和非平稳特征分析

分析地震动的频谱周期参数和频率非平稳特征,是地震危险性分析和结构抗震设计的重要内容.本文对近断层地震动记录按照不同的运动特征分组,进行了Hilbert-Huang变换分析.结合相关的定义得到了表征地震动频谱特性的7个周期参数,包括:Fourier幅值谱平均周期Tm、Hilbert边际谱平均周期Tmh、特征周期Tc、卓越周期等,并计算了地震动的Hilbert谱瞬时频率时程变异系数.计算结果表明,从整体上把握地震动频谱特性的三个周期参数Tm 、Tmh 和Tc适合于表征近断层地震动的频谱成份.近断层地震动的频率非平稳特征显著,Hilbert谱瞬时频率变异系数良好地反映了地震动的频率非平稳性质和程度.而且,考察了近断层地震动运动特征对地震动频谱周期参数和频率非平稳性的影响.     

唐山震后建设与抗震结构体系

1976年唐山大地震至今已30年,唐山的震后建设先后经历了抗灾建设、恢复建设和发展建设三个阶段。三个不同的建设阶段所采用的抗震结构体系有所不同,也反映了我国抗震理论和实践的进步与发展。本文总结了三个不同建设时期唐山市建筑工程采用的主要抗震结构体系,并对唐山市建筑抗震结构体系的发展提出了建议。     

粒子滤波非线性AVO反演方法

提出一种新的AVO非线性反演方法,即利用粒子滤波器来求解AVO非线性贝叶斯反演问题,利用随机带权样本逼近后验概率.论文首先论述了粒子滤波器的基本原理,包括状态转移模型与观测模型,权值预测与更新,重要性密度采样等粒子滤波器应用中的关键技术.然后建立了适合于AVO反演的粒子滤波器状态转移模型和观测模型.最后,利用该方法分别对模型数据和实际资料进行了反演计算.反演结果表明,该方法具有较好的稳定性,在AVO反演中具有的一定的应用潜力.同时对地球物理反演的其他问题求解也提供了一条新的途径.