随机结构动力可靠度分析的极值概率密度方法

提出了随机结构动力可靠度分析的极值概率密度方法。基于概率密度演化的基本思想,构造一个虚拟随机过程,使得随机结构动力反应的极值为该虚拟随机过程的截口随机变量。进而．采用概率密度演化方法,建立概率密度演化方程并求解给出随机结构动力反应的极值分布。在安全域内积分即可给出结构动力可靠度,当安全界限为随机变量时,采用这一方法几乎不增加额外的工作量,与随机模拟结果的比较表明,本文建议方法具有良好的精度和效率。     

Joint probability density function of the stochastic responses of nonlinear structures

The joint probability density fimction （PDF） of different structural responses is a very important topic in the stochastic response analysis of nonlinear structures. In this paper, the probability density evolution method, which is successfully developed to capture the instantaneous PDF of an arbitrary single response of interest, is extended to evaluate the joint PDF of any two responses. A two-dimensional partial differential equation in terms of the joint PDF is established. The strategy of selecting representative points via the number theoretical method and sieved by a hyper-ellipsoid is outlined. A two-dimensional difference scheme is developed. The free vibration of an SDOF system is examined to verify the proposed method, and a flame structure exhibiting hysteresis subjected to stochastic ground motion is investigated. It is pointed out that the correlation of different responses results from the fact that randomness of different responses comes from the same set of basic random parameters involved. In other words, the essence of the probabilistic correlation is a physical correlation.     

基于随机振动理论的抗震分析方法研究进展

介绍了随机振动理论在工程结构抗震分析方法中的最新进展。对近年来发展的虚拟激励法在线性结构系统中所具有的高效随机振动分析作了较为完整的介绍,尤其在多点地震激励的随机振动分析中具有优越性。同时,介绍了最新发展的概率密度演化方法,这一方法在非线性结构系统分析中具有独特性,可获得非线性结构反应的概率密度分布及其随时间的变化过程。     

基于非平稳随机地震动模型的重力坝抗震可靠度分析

基于正交展开的非平稳随机地震动模型,并考虑混凝土材料的非线性和坝体与库水之间的流固耦合,对印度Koyna重力坝进行有限元分析,得到坝顶水平位移和坝颈拉应力,结合概率密度演化方法和等价极值事件的思想,获得丰富的概率信息。这为坝体结构的随机地震反应分析和可靠度研究提供新的途径。     

Random stability for lateral vibration on footbridge based on IEVIE–PDE method

The pedestrian-induced lateral vibration of footbridges is essentially classified as a nonlinear stochastic vibration. Accordingly, bridge vibration stability falls within the field of nonlinear stochastic vibration stability. At present, the Lyapunov method is mainly used to analyze such stability. However, this method is qualitative, and it cannot quantitatively analyze the vibration stability probability. In this study, a new analytical method based on a comparison of the input energy and the variation of intrinsic energy(IEVIE) is used to analyze the nonlinear stochastic vibration stability of the lateral vibration of the footbridge. The improved Nakamura model is used to describe the lateral nonlinear stochastic vibration of the footbridge. A combination of the IEVIE method and the probability density evolution(PDE) method is then proposed, in which the IEVIE method is utilized to determine vibration stability. The PDE method is used to obtain the reliability of vibration stability. The proposed method is successfully applied to the Millennium Bridge, and its effectiveness is verified by comparing the Monte Carlo and Lyapunov methods. The proposed method can obtain the dynamic probability of the vibration as stable or instable and provide a reference for quantitative analysis of lateral nonlinear stochastic vibration stability of footbridges.     

Inexact two-stage stochastic partial programming: application to water resources management under uncertainty

In this study, an inexact two-stage stochastic partial programming (ITSPP) method is developed for tackling uncertainties presented as intervals and partial probability distributions. A scenario-based interactive algorithm is proposed to solve the ITSPP model. This algorithm is implemented through: (i) obtaining extreme points of the linear partial information (LPI); (ii) generating an inexact two-stage stochastic programming (ITSP) model under each extreme point; (iii) solving ITSP models through interactive algorithm proposed by Huang and Loucks (Civil Eng Environ Syst 17:95–118, 2000); (iv) acquiring the interval solutions under each extreme point and the final optimal interval for the objective function. The developed method is applied to a case study for water-resources planning. The modelling results can generate a series of decision alternatives under various system conditions, and thus help decision makers identify the desired water-resources management policies under uncertainty.     

Nonlinear stochastic seismic analysis of buried pipeline systems

In this paper, a nonlinear stochastic seismic analysis program for buried pipeline systems is developed on the basis of a probability density evolution method (PDEM). A finite element model of buried pipeline systems subjected to seismic wave propagation is established. The pipelines in this model are simulated by 2D beam elements. The soil surrounding the pipelines is simulated by nonlinear distributed springs and linear distributed springs along the axial and horizontal directions, respectively. The joints between the segmented pipes are simulated by nonlinear concentrated springs. Thereafter, by considering the basic random variables of ground motion and soil, the PDEM is employed to capture the stochastic seismic responses of pipeline systems. Meanwhile, a physically based method is employed to simulate the random ground motion field for the area where the pipeline systems are located. Finally, a numerical example is investigated to validate the proposed program.     

Grain yield reliability analysis with crop water demand uncertainty

A new method of reliability analysis for crop water production function is presented considering crop water demand uncertainty. The procedure uses an advanced first-order second moment (AFOSM) method in evaluating the crop yield failure probability. To determine the variance and the mean of actual evapotranspiration as the component of interest for AFOSM analysis, an explicit stochastic optimization model for optimal irrigation scheduling is developed based on the first and second-order moment analysis of the soil moisture state variables. As a result of the study, the violation probabilities of crop yield at different levels were computed from AFOSM method. Also using the optimization results and the double bounded density function estimation methodology, the weekly soil moisture density function is derived which can be used as a short term reliability index. The proposed approach does not involve any discretization of system variables. The results of reliability analysis and optimization model compare favorably with those obtained from simulation.     

Random vibration of hysteretic systems under bi-directional ground motions

A random vibration method is developed for the response analysis of hysteretic structural systems under stochastic two-dimensional earthquake excitations. The biaxial hysteretic restoring force is modelled by coupled non-linear differential equations; the response statistics are obtained using the equivalent linearization technique. The validity of the proposed model is appraised using available biaxial loading tests of reinforced concrete columns. A parametric study was performed to examine the significance of the effects of biaxial interaction under earthquake excitations. A practical method to evaluate the extreme response statistics is also presented.     

Response uncertainty and time-variant reliability analysis for hysteretic MDF structures

Response uncertainty evaluation and dynamic reliability analysis corresponding to classical stochastic dynamic analysis are usually restricted to the uncertainties of the excitation. The inclusion of the parameter uncertainties contained in structural properties and excitation characteristics has become an increasingly important problem in many areas of dynamics. In the present paper, a point estimate procedure is proposed for the evaluation of stochastic response uncertainty, and a response surface approach procedure in standard normal space is proposed for analysis of time-variant reliability analysis for hysteretic MDF structures having parameter uncertainties. Using the proposed procedures, the response uncertainties and time-variant reliability can be easily obtained by several repetitions of stochastic response analysis under given parameters without conducting sensitivity analysis, which is considered to be one of the primary difficulties associated with conventional methods. In the time-variant reliability analysis, the failure probability can be readily obtained by improving the accuracy of the first-order reliability method using the empirical second-order reliability index. The random variables are divided into two groups, those with CDF and those without CDF. The latter are included via the high-order moment standardization technique. A numerical example of a 15F hysteretic MDF structure that takes into account uncertainties of four structural parameters and three excitation characteristics is performed, based on which the proposed procedures are investigated and the effects of parameter uncertainties are discussed. Copyright © 1999 John Wiley & Sons, Ltd.     

Probability density evolution method for seismic liquefaction performance analysis of earth dam

To investigate the seismic liquefaction performance of earth dams under earthquake loading, we present a new methodology for evaluating the seismic response of earth dams based on a performance‐based approach and a stochastic vibration method. This study assesses an earthfill dam located in a high‐intensity seismic region of eastern China. The seismic design levels and corresponding performance indexes are selected according to performance‐based criteria and dam seismic codes. Then, nonlinear constitutive models are used to derive an array of deterministic seismic responses of the earth dam by dynamic time series analysis based on a finite element model. Based on these responses, the stochastic seismic responses and dynamic reliability of the earth dam are obtained using the probability density evolution method. Finally, the seismic performance of the earth dam is assessed by the performance‐based and reliability criteria. Our results demonstrate the accuracy of the seismic response analysis of earth dams using the random vibration method. This new method of dynamic performance analysis of earth dams demonstrates that performance‐based criteria and reliability evaluation can provide more objective indices for decision‐making rather than using deterministic seismic acceleration time series as is the current normal practice. Copyright © 2016 John Wiley & Sons, Ltd.     

Effect of travelling waves on stochastic seismic response and dynamic reliability of a long-span bridge on soft soil

It is generally known that the variability of earthquake ground motion is mainly in time and space. To investigate the impact of this variability on the seismic performance of a long-span flexible structure, we discuss the seismic dynamic responses of a real bridge subjected to stochastic seismic ground motion. We incorporate the effect of wave passage by means of the method of probability density evolution based on dynamic time-history analysis from the perspective of stochastic dynamics. First, we introduce the theory of probability density evolution and a category of stochastic seismic model. We then conduct a series of deterministic seismic dynamic analyses of the bridge to establish the probability density equation. Eventually, we obtain the probability information at the level of the probability density function of the seismic response by solving the probability-density evolution equation. The results show that the impact of travelling waves on a long-span structure is related to the characteristics of the earthquake ground motion and the structure, and that travelling waves increase the variability of the seismic response.     

随机地震作用下特高压换流站阀厅非线性动力可靠度研究

通过模态分析研究了抗震设防烈度为8度（0.3g）的混合结构与全钢结构两种阀厅结构方案的动力特性,基于地震动的地震学模型与概率密度演化法分析了全钢阀厅的非线性随机动力可靠度,根据阀厅角柱柱顶位移响应得到了全钢阀厅动力影响的概率密度曲面及典型时刻的概率密度曲线。研究结果表明:阀塔对结构整体刚度影响较小,工程中可采用无阀模型进行简化计算;高烈度设防地区,推荐采用结构布置相对规则的钢结构方案;随机动力分析相比于确定性分析更能反应地震作用下阀厅动力响应的客观规律;阀厅钢结构方案在罕遇地震作用下可靠度较高,结构安全可靠。     

随机动力系统最优控制准则研究

根据线性二次最优控制理论,给出了系统随机最优控制的控制律一般形式。从目标控制量的物理意义出发,提出了基于系统概率密度演化分析的最优控制准则,建立了递阶层次的演化过程控制准则类。以线性单自由度体系随机地震反应最优控制为例,分析了各控制准则类的权矩阵参数优化结果,并根据最优控制律进行了系统随机最优控制研究。结果表明,本文提出的系统随机最优控制的控制律确定方法可以对系统性态进行有效的控制。     

Laboratory sandbox validation of pollutant source location methods

Inverse methods can be used to recover the pollutant source location from concentration data. In this paper, the relative effectiveness of two proposed methods, simultaneous release function and source location identification (SRSI) and backward probability model based on adjoint state method (BPM-ASM) are evaluated using real data collected by using experimental equipment. The device is a sandbox that reproduces an unconfined aquifer in which all the variables are controlled. A numerical model was calibrated using experimental observations. The SRSI is a stochastic procedure which finds the source location and the release history by means of a Bayesian geostatistical approach (GA). The BPM-ASM provides the backward probability location of the pollutant detected at a monitoring point by means of a reverse transport simulation. The results show that both methods perform well. While the simultaneous release function and SRSI method requires a preliminary delineation of a probable source area and some weak hypotheses about the statistical structure of the unknown release function, the backward probability model requires some hypothesis about the contaminant release time. A case study was performed using two observation points only, and despite the scarcity of data, both methodologies were able to accurately reconstruct the true source location. The GA has the advantage to recover the release history function too, whilst the backward probability model works well with fewer data. If there are many observations, both methodologies may be computationally heavy. A transfer function approach has been adopted for the numerical definition of the sensitivity matrix in the SRSI method. The reliability of the experimental equipment was tested in previous laboratory works, conducted under several different conditions.     

基于概率密度演化的基础隔震结构随机响应分析

针对抗震结构和基础隔震结构,应用概率密度演化方法对其进行多遇地震作用下的线性随机响应分析。通过引入工程地震动物理随机函数模型,采用数论选点法对多维外荷载随机变量进行离散代表点的生成并求得其赋得概率,利用离散代表点合成地震动加速度时程样本作为输入结构的随机激励,对于每条地震波,相当于对结构进行确定性动力反应分析。在求得结构响应及其相关导数后,应用TVD差分格式求解广义概率密度演化方程即可得到所求响应的时变概率密度及其演化。结果表明：基础隔震结构在随机地震作用下相比抗震结构具有良好的减震性能,隔震层的设置能够减小结构位移响应的标准差,减少了结构响应的离散型;概率密度演化方法不仅能够给出结构响应的二阶统计矩,还能全面地反映结构响应的时变概率信息,位移响应的概率密度函数分布不服从正态分布或其他常用分布,且随着时间演化。     

Model updating using noisy response measurements without knowledge of the input spectrum

A new probabilistic model identification methodology is proposed using measured response time histories only. The proposed approach requires that the number of independent measurements is larger than the number of independent excitations. Under this condition, no input measurements or any information regarding the stochastic model of the input is required. Specifically, the method does not require the response to be stationary and does not assume any knowledge of the parametric form of the spectral density of the input. Therefore, the method has very wide applicability. The proposed approach allows one to obtain not only the most probable values of the updated model parameters but also their associated uncertainties using only one set of response data. It is found that the updated probability distribution can be well approximated by a Gaussian distribution centered at the most probable values of the parameters. Examples are presented to illustrate the proposed method. Copyright © 2004 John Wiley & Sons, Ltd.     

Gaussian mixture–based equivalent linearization method (GM-ELM) for fragility analysis of structures under nonstationary excitations

Gaussian mixture–based equivalent linearization method (GM-ELM) is a recently developed stochastic dynamic analysis approach which approximates the random response of a nonlinear structure by collective responses of equivalent linear oscillators. The Gaussian mixture model is employed to achieve an equivalence in terms of the probability density function (PDF) through the superposition of the response PDFs of the equivalent linear system. This new concept of linearization helps achieve a high level of estimation accuracy for nonlinear responses, but has revealed some limitations: (1) dependency of the equivalent linear systems on ground motion intensity and (2) requirements for stationary condition. To overcome these technical challenges and promote applications of GM-ELM to earthquake engineering practice, an efficient GM-ELM-based fragility analysis method is proposed for nonstationary excitations. To this end, this paper develops the concept of universal equivalent linear system that can estimate the stochastic responses for a range of seismic intensities through an intensity-augmented version of GM-ELM. Moreover, the GM-ELM framework is extended to identify equivalent linear oscillators that could capture the temporal average behavior of nonstationary responses. The proposed extensions generalize expressions and philosophies of the existing response combination formulations of GM-ELM to facilitate efficient fragility analysis for nonstationary excitations. The proposed methods are demonstrated by numerical examples using realistic ground motions, including design code–conforming nonstationary ground motions.     

Sensitivity and moment analyses of head in variably saturated regimes

A numerical approach for approximating statistical moments of hydraulic heads of variably saturated flows in multi-dimensional porous media is developed. The approximation relies on a first-order Taylor series expansion of a finite element flow model and an adjoint state numerical method for variably saturated flows to evaluate sensitivities. This approach can be employed to analyze uncertainties associated with predictions of head of steady-state or transient flows in variably saturated porous media, with any type of boundary and initial conditions. Limitations of stochastic analytical methods such as spectral/perturbation approaches and the time-consuming Monte Carlo simulation technique are thus alleviated. An example is given to demonstrate the utility of the approach and to investigate the temporal evolution of head variances in a variably saturated flow regime. Results show that the fluctuation of the water table can have significant impacts on the propagation of the head variance.