Stochastic dynamic stiffness of a surface footing for offshore wind turbines: Implementing a subset simulation method to estimate rare events

The purpose of this study, which concerns the stochastic dynamic stiffness of foundations for large offshore wind turbines, is to quantify uncertainties related to the first natural frequency of a turbine supported by a surface footing and to estimate the low event probabilities. Herein, a simple model of a wind turbine structure with equivalent coupled springs at the base is calibrated with the mean soil property values. A semianalytical solution, based on the Green׳s function for a layered half-space is utilized for estimation of foundation responses. Soil elastic modulus and layer depth are considered as random variables with lognormal distributions. The uncertainties are quantified, and the estimation of rare events of the first natural frequency is discussed through an advanced reliability approach based on subset simulation. This analysis represents a first step in the estimation of the safety with respect to the failure of a turbine in the fatigue limit state.     

中强地震随机有限断层模型应力降参数的确定方法

随机有限断层模型是模拟地震动加速度时程的一个重要工具.但将其应用于中强地震时,由于震源信息的准确性较差从而使模型参数具有较大的不确定性.尤其针对其中最为关键的应力降参数,目前相关研究较为缺乏且尚未形成系统的确定方法.本文基于美国Little Skull Mountain Mw5.6级地震2个近场台站记录的地震动模拟,详细研究了采用随机有限断层法拟合中强地震地震动伪加速度反应谱（PSA）来确定应力降参数值的方法,并在计算应力降时引入了其它震源参数的不确定性,随后对此方法的可行性进行了验证.研究表明：采用不同频段反应谱残差和计算得到的应力降值差别较大,确定中强地震应力降较为合适的反应谱频段是中高频,采用该频段确定的应力降参数值模拟的反应谱和峰值加速度与实际记录较为符合;脉冲子断层百分比、断层长宽、倾角和深度等震源参数按截断的正态分布或均匀分布随机抽样,拟合得到的应力降参数值与通过实际震源模型参数得到的值相近.以上研究结果对确定一个区域中强地震应力降或中强地震近场强震动模拟研究提供了更进一步的研究方法和研究方向.     

Robustness of the holistic seismic risk evaluation in urban centers using the USRi

The Urban Seismic Risk index (USRi) published in a previous article (Carreño et al., Nat Hazards 40:137–172, 2007) is a composite indicator that measures risk from an integrated perspective and guides decision-making for identifying the main interdisciplinary factors of vulnerability to be reduced or intervened. The first step of the method is the evaluation of the potential physical damage (hard approach) as a result of the convolution of the seismic hazard with the physical vulnerability of buildings and infrastructure. Subsequently, a set of social context conditions that aggravate the physical effects is also considered (soft approach). According to this procedure, the physical risk index is evaluated for each unit of analysis from existing loss scenarios, whereas the total risk index is obtained by multiplying the former index by an impact factor using an aggravating coefficient, based on variables associated with the socio-economic conditions of each unit of analysis. The USRi has been developed using the underlying holistic and multi-hazard approach of the Urban Risk Index framework proposed for the evaluation of disaster risk in different megacities worldwide. This article presents the sensitivity analysis of the index to different parameters such as input data, weights and transformation functions used for the scaling or normalization of variables. This analysis has been performed using the Monte Carlo simulation to validate the robustness of this composite indicator, understanding as robustness how the cities maintain the ranking as well as predefined risk level ranges, when compared with the deterministic results of risk. Results are shown for different cities of the world.     

Dynamic responses under the excitation of pulse sequences

This paper studies the dynamic responses of SDOF system under pulse-dominant excitations. The purpose of the study is to prepare for scrutiny of some near-field pulse-dominant ground motions and their potential to cause structural damage. Extending the single pulse dynamics, we consider the effect of pulse sequences. This kind of excitation was particularly obvious in some of previous earthquakes such as Northridge (1994) and Chi-Chi (1995). Based on the duration,peak and rise and decay era of the main pulse as well as its relationship with the predecessor and successor pulses, we propose a classification for the pulse sequences. Consequent studies have been carried out for acceleration, velocity and displacement response spectra of the main pulse with either a predecessor or a successor pulse. The analysis also includes general response behaviors in different fundamental period segments and special aspects of response at certain points (e.g., the corresponding peak points).     

川滇地区地震动预测模型及其对2021年漾濞6.4级地震的适用性

随着川滇地区强震记录的不断增加,为了建立更符合该区域地震动特征的预测模型,文中基于该区域现有的地震动数据,通过随机效应回归模型建立适用于川滇地区的地震动预测模型;2021年5月21日,云南省大理州漾濞县发生6.4级地震,为了分析文中预测模型对漾濞地震的适用性,首先根据预测模型的适用范围选取合适的漾濞地震数据,计算真实记...     

Scaling law of the reduced magnetic helicity in fast streams

The reduced magnetic helicity is a quantity related to the handedness of the magnetic field fluctuations. In the present paper we study the scaling law of the reduced magnetic helicity in fast streams in the solar wind by using high-resolution magnetic field data by the Ulysses spacecraft. We show that at high frequencies both the left-hand and the right-hand helicity survives, implying that there is no predominance of a single sign. In addition, the scaling law of the magnetic helicity exhibits a strong dependence on the data set analyzed and we do not observe any universal behavior.     

测井、井间地震与地面地震数据联合约束下的地质统计学随机建模方法研究

利用能够整合测井信息与井间地震信息的地质统计学随机模拟方法,结合传统的地质统计学反演思路,得到了一种能够同时整合测井、井间地震与地面地震三种先验信息的地质统计学反演与储层建模方法.由于井间射线信息、测井信息与地面地震数据在随机反演与建模过程当中都得到了尊重,因此与传统地质统计学反演仅利用了测井与地面地震数据相比,本文的地质统计学反演与建模方法更充分地利用了先验信息,有效提高了反演的精度,降低了随机建模中的多解性.基于理论数据的测试证实了上述观点.     

Seismic demand models for probabilistic risk analysis of near fault vertical ground motion effects on ordinary highway bridges

The influence of vertical ground motions on the seismic response of highway bridges is not very well understood. Recent studies suggest that vertical ground motions can substantially increase force and moment demands on bridge columns and girders and cannot be overlooked in seismic design of bridge structures. For an evaluation of vertical ground motion effects on the response of single‐bent two‐span highway bridges, a systematic study combining the critical engineering demand parameters (EDPs) and ground motion intensity measures (IMs) is required. Results of a parametric study examining a range of highway bridge configurations subjected to selected sets of horizontal and vertical ground motions are used to determine the structural parameters that are significantly amplified by the vertical excitations. The amplification in these parameters is modeled using simple equations that are functions of horizontal and vertical spectral accelerations at the corresponding horizontal and vertical fundamental periods of the bridge. This paper describes the derivation of seismic demand models developed for typical highway overcrossings by incorporating critical EDPs and combined effects of horizontal and vertical ground motion IMs depending on the type of the parameter and the period of the structure. These models may be used individually as risk‐based design tools to determine the probability of exceeding the critical levels of EDP for pre‐determined levels of ground shaking or may be included explicitly in probabilistic seismic risk assessments. Copyright © 2011 John Wiley & Sons, Ltd.     

Nonlocal period parameters of frequency content characterization for near-fault ground motions

This paper focuses on the frequency property analysis of near-fault ground motions with and without distinct pulses, separately from the Chi-Chi and Northridge earthquakes. Ten scalar period parameters of ground motions, especially several nonlocal period parameters, are considered. Two new nonlocal parameters, namely the mean period of Hilbert marginal spectrum (T_mh) and the improved characteristic period (T_gi), are suggested. Moreover, comprehensive comparison and analysis indicate that T_mh, T_gi and T_avg (average spectral period) can distinguish the low-frequency components of near-fault ground motions; T_m (mean period of Fourier amplitude spectrum) and T_o (smoothed spectral predominant period) represent the moderate- and high-frequency components, respectively. The variance coefficient of predominant instantaneous frequency of Hilbert spectrum (H_cov) can be regarded as an alternative index to measure the non-stationary degree of near-fault ground motions. Finally, the velocity pulses and earthquake magnitude remarkably affect the frequency parameters of near-fault ground motions. Copyright © 2012 John Wiley & Sons, Ltd.     

Efficient risk assessment of lifeline networks under spatially correlated ground motions using selective recursive decomposition algorithm

For effective hazard mitigation planning and prompt-but-prudent post-disaster responses, it is essential to evaluate the reliability of infrastructure networks accurately and efficiently. A nonsimulation-based algorithm, termed as a recursive decomposition algorithm (RDA), was recently proposed to identify disjoint cut sets and link sets and to compute the network reliability. This paper introduces a ‘selective’ RDA, which preferentially identifies critical disjoint cut sets and link sets to calculate the probabilities of network disconnection events with a significantly reduced number of identified sets. To this end, the original RDA is improved by replacing the shortest path algorithm with an algorithm that identifies the most reliable path, and by using a graph decomposition scheme based on the probabilities associated with the subgraphs. The critical sets identified by the algorithm are also used to compute conditional probability-based importance measures that quantify the relative importance of network components by their contributions to network disconnection events. This paper also introduces a risk assessment framework for lifeline networks based on the use of the selective RDA, which can consider both interevent and intraevent uncertainties of spatially correlated ground motions. The risk assessment framework and the selective RDA are demonstrated by a hypothetical network example, and the gas and water transmission networks of Shelby County in Tennessee, USA. The examples show that the proposed framework and the selective RDA greatly improve efficiency of risk assessment of complex lifeline networks, which are characterized by a large number of components, complex network topology, and statistical dependence between component failures. Copyright © 2012 John Wiley & Sons, Ltd.