Comparison of adaptive structural damage identification techniques in nonlinear hysteretic vibration isolation systems

Early structural damage identification to obtain an accurate condition assessment can assist in the reprioritization of structural retrofitting schedules in order to guarantee structural safety. Nowadays, seismic isolation technology has been applied in a wide variety of infrastructure, such as buildings, bridges, etc., and the health conditions of these nonlinear hysteretic vibration isolation systems have received considerable attention. To effectively detect structural damage in vibration isolation systems based on vibration data, three time-domain analysis techniques, referred to as the adaptive extended Kalman filter （AEKF）, adaptive sequential nonlinear least-square estimation （ASNLSE） and adaptive quadratic sum-sqnares error （AQSSE）, have been investigated. In this research, these analysis techniques are compared in terms of accuracy, convergence and efficiency, for structural damage detection using experimental data obtained through a series of laboratory tests based on a base-isolated structural model subjected to E1 Centro and Kobe earthquake excitations. The capability of the AEKF, ASNLSE and AQSSE approaches in tracking structural damage is demonstrated and compared.     

Life‐cycle cost assessment of RC and ECC frames using structural optimization

In this study life‐cycle cost (LCC) assessment of structural frames is performed. Two different materials, reinforced concrete (RC) and reinforced engineered cementitious composites (ECC), with different response characteristics are used to model the frames. ECC is characterized by high tensile ductility and energy absorption and reduced crack widths when compared to conventional concrete. However, the material is more expensive than conventional concrete; therefore, in order to quantify the potential benefits that could be obtained by replacing concrete with ECC, the life‐cycle performance is evaluated in an optimization framework. Three different structural frames are considered: an RC only frame, an ECC only frame and a multi‐material (MX) frame in which ECC is selectively applied at the potential plastic hinge locations while the remainder of the frame is made of RC. The structural capacity and earthquake demand are evaluated using rigorous analysis methods to capitalize on different characteristics of concrete and ECC, and both aleatory and epistemic uncertainties are incorporated into the LCC formulation. It is found that both the initial and LCC of frames that use ECC are lower due to savings in material and labor cost of transverse reinforcement for the former and due to increased capacity and reduced demand for the latter. Copyright © 2012 John Wiley & Sons, Ltd.     

Review of the Kalman-type hydrological data assimilation

ABSTRACT

There is great potential in Data Assimilation (DA) for the purposes of uncertainty identification, reduction and real-time correction of hydrological models. This paper reviews the latest developments in Kalman filters (KFs), particularly the Extended KF (EKF) and the Ensemble KF (EnKF) in hydrological DA. The hydrological DA targets, methodologies and their applicability are examined. The recent applications of the EKF and EnKF in hydrological DA are summarized and assessed critically. Furthermore, this review highlights the existing challenges in the implementation of the EKF and EnKF, especially error determination and joint parameter estimation. A detailed review of these issues would benefit not only the Kalman-type DA but also provide an important reference to other hydrological DA types.

Editor D. Koutsoyiannis; Associate editor F. Pappenberger     

Generalized LSG models with spatially varying Coriolis parameter

In this paper, we derive and study approximate balance models for nearly geostrophic shallow water flow where the Coriolis parameter is permitted to vary across the domain as long as it remains nondegenerate. This situation includes, for example, the β-plane approximation to the shallow water equations at mid-latitudes. Our approach is based on changing configuration space coordinates in the underlying variational principle in such a way that consistent asymptotics in the transformed Lagrangian leads to a degenerate Lagrangian structure. In this paper, we restrict our attention to first-order models. We show that the resulting models can be formulated in terms of an advected potential vorticity with a nonlinear vorticity inversion relation. We study the associated solvability conditions and identify a subfamily of models for which these conditions are satisfied without additional restrictions on the data. Finally, we provide the link between our framework and the theory of constrained Hamiltonian systems.     

Trimmed L-moments (1,0) for the generalized Pareto distribution

Abstract

Statistical analysis of extremes is often used for predicting the higher return-period events. In this paper, the trimmed L-moments with one smallest value trimmed—TL-moments (1,0)—are introduced as an alternative way to estimate floods for high return periods. The TL-moments (1,0) have an ability to reduce the undesirable influence that a small value in the statistical sample might have on a large return period. The main objective of this study is to derive the TL-moments (1,0) for the generalized Pareto (GPA) distribution. The performance of the TL-moments (1,0) was compared with L-moments through Monte Carlo simulation based on the streamflow data of northern Peninsular Malaysia. The result shows that, for some cases, the use of TL-moments (1,0) is a better option as compared to L-moments in modelling those series.

Citation Ahmad, U.N., Shabri, A. & Zakaria, Z.A. (2011) Trimmed L-moments (1,0) for the generalized Pareto distribution. Hydrol.Sci. J. 56(6), 1053–1060.     

Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records

Abstract

New mathematical programming models are proposed, developed and evaluated in this study for estimating missing precipitation data. These models use nonlinear and mixed integer nonlinear mathematical programming (MINLP) formulations with binary variables. They overcome the limitations associated with spatial interpolation methods relevant to the arbitrary selection of weighting parameters, the number of control points within a neighbourhood, and the size of the neighbourhood itself. The formulations are solved using genetic algorithms. Daily precipitation data obtained from 15 rain gauging stations in a temperate climatic region are used to test and derive conclusions about the efficacy of these methods. The developed methods are compared with some naïve approaches, multiple linear regression, nonlinear least-square optimization, kriging, and global and local trend surface and thin-plate spline models. The results suggest that the proposed new mathematical programming formulations are superior to those obtained from all the other spatial interpolation methods tested in this study.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi

Citation Teegavarapu, R.S.V., 2012. Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records. Hydrological Sciences Journal, 57 (3), 383–406.     

From marginal to conditional probability functions of parameters in a conceptual rainfall–runoff model: an event-based approach

ABSTRACT

A parameter estimation strategy for a conceptual rainfall–runoff (CRR) model applied to a storm sewer system in an urban catchment (Chassieu, Lyon, France) is proposed on the basis of event-by-event Bayesian local calibrations. The marginal distribution formed by locally-estimated parameters is divided into conditional functions, clustering the event-based parameters based on their transferability to similar rainfall events. The conditional functions showed to be consistent with an observed bimodality in the marginal representation, reflecting two different hydrological conditions mainly related to the magnitude of the rainfall intensities (high or low). The improvements achieved by expressing the parameter probability functions into a conditional form are shown in terms of accuracy (Nash-Sutcliffe efficiency criterion), precision (average relative interval length) and reliability (percentage of coverage) for simulating flow rate in 255 and 110 calibration/verification events.     

云南中小地震矩震级的测定

利用云南省测震台网的数字地震波形资料,反演了2008年1月至2012年9月675个中小地震的震源波谱参数,并计算了这些地震的地震矩M0和矩震级Mw,最后利用回归分析方法得到了近震震级ML和Mw之间的关系式.     

基于环境激励的ERA方法在网架结构振动测试中的应用研究

基于环境激励的结构振动测试的方法中ERA方法是重要的时域分析方法.本文主要是以随机减量法(RD)和NExT两种数据处理方法结合ERA算法,对绥化学院正在建的网架结构的基本模态参数进行测试.通过分析比较得出RD/ERA和NExT/ERA较直接ERA有更高的精度,且实测分析结果与有限元分析结果较吻合.为网架结构在环境激励下用ERA方法测试模态参数提供了实验依据.     

芦山地震有限断层混合震源模型模拟

建立了基于有限断层的芦山地震的混合震源模型,突出破裂面上滑动量分布中凹凸体的主导作用,同时借助k平方模型表达对震源复杂性认识尚不够深入所带来的随机性.混合震源模型中全局震源参数均值与局部震源参数均值的确定,主要依据统计的半经验标定公式,进一步借助截断正态分布将区域地震、地质构造、地震活动性提供的参数限值结合起来,生成最终的震源参数值.基于上述思路,本文共建立了30组芦山地震混合震源模型,进而以芦山地震8个近场观测台站为试算点,借助地震动反应谱残差评价的方法,从30组模型中选定了表达“平均”特征的混合震源模型.