基于广义层间位移角谱的复合自复位结构体系的参数分析

提出了复合自复位结构体系,该结构体系在层次上由基本功能分区和损伤控制分区组成。根据不同分区的结构变形特征将复合自复位结构体系简化为由剪切梁和弯曲梁组成的双梁分布体系模型。求解得到复合自复位结构体系振型方程的闭合解,分析该体系在不同剪弯刚度比和弯曲梁与其底部约束刚度比下振型和振型转角的变化规律。基于振型叠加法得到体系的广义层间位移角谱,分析了剪弯刚度比和弯曲梁与其底部约束刚度比、阻尼比和高阶模态对体系广义层间位移角谱的影响。结果表明:在剪弯刚度比介于1~3的区间,弯曲梁与其底部约束刚度比介于1~5的区间,通过附加一定的阻尼,体系不仅可以抑制高阶振型的影响得到较均匀的层间位移分布而且可以降低最大响应。以广义层间位移角谱为工具,可以实现复合自复位结构体系直接基于位移的设计。     

底部两层框架抗震墙砖房第三层与第二层侧移刚度比的合理取值

本文探讨了底部两层框架抗震墙砖房中底部两层层间侧移刚度的简化计算方法，分析指出了计算第二层侧移刚度采用的层间位移，不能从底部两层框架抗震墙的第二层的侧移减去第一层的侧移得到，应扣除钢筋砼墙在第一层楼板处转角产生的侧移，同时，探讨并给出了底部两层框架抗震墙砖房第三层与第二层侧移刚度比的合理取值为１．２～２．０之间，并且不应小于１．０。     

高位转换粘滞阻尼减震结构阻尼器合理阻尼系数研究

根据《高层建筑混凝土结构技术规程》和《建筑抗震设计规范》对高位转换结构体系的框支层的层间位移和结构等效侧向刚度的限制要求,采用等效侧向刚度计算方法,将高位耗能减震结构分解成框撑剪结构和纯剪力结构,结合振型分解反应谱理论和线性粘滞阻尼减震结构等效阻尼比计算方法,推导出了高位转换粘滞阻尼减震结构合理阻尼系数的计算公式。最后,通过算例分析得出,采用上述方法计算高位转换粘滞阻尼减震结构粘滞阻尼系数是可行的,该方法计算公式简单实用,可用于高位转换粘滞阻尼减震结构的初步设计。     

多模态静力推覆分析及其在高层混合结构体系抗震评估中的应用

在已有的研究基础上通过考虑多阶振型质量积的水平力分布形式下的推覆分析,将结构推至每阶振型下的目标位移,采用SRSS组合的方式得到结构的响应。对应每阶振型下推覆分析的目标位移采用弹塑性反应谱来计算。对一高层钢框架-混凝土核心筒混合结构在7度罕遇地震下抗震性能进行了评估,结果显示,多模态静力推覆分析所得的结构响应同非线性动力时程分析所得结果很接近,尤其是在层间位移角及层间剪力这两个重要抗震指标上更为接近。     

港口门座起重机的静,动强度测试分析和疲劳寿命预测

本文针对业已运行多年的门座起重机的安全评估，进行静，动强度测试再分析和疲劳寿命估计的方法和具体实施问题，文中介绍了测试方案的选定，测试数据的处理，测试结果的分析方法，目的在于通过实测和数据处理获取正确的关键性的信息，作为安全分析和疲劳寿命的估计的依据。     

时程分析考虑高阶振型影响的多频段地震波选择方法研究

针对结构抗震时程分析输入地震波选择问题,以加速度反应谱（或设计谱）为目标谱,在反应谱平台段和结构基本周期附近误差双控指标中,引入了由归一化振型参与系数确定的前几阶振型的权重系数,提出了考虑多频段加权匹配的时程分析输入地震波选择方法,以充分考虑高阶振型的影响。以美国SAC Steel Project提出的9层和20层抗弯钢框架Benchmark结构为实例,为方便将建议选波方法与较多地震波输入时程分析结果进行比较,以简单地震信息初选的小型地震波数据库中的20条地震波的均值（放大系数）谱作为目标谱,以这20条地震波时程分析得到的结构最大基底剪力和层间位移角均值为目标反应,前者考虑弹性状态,后者对应弹塑性情况。将按该文方法选出的3条波输入下结构反应均值与目标反应进行了比较分析,初步证实了建议选波方法的可行性。将该文方法与ASCE 7-05地震波输入要求方法对比,在弹塑性反应状态下,两者对结构最大层间位移角沿楼层分布规律的估计以及薄弱层位置的判断均与目标反应较为一致。ASCE 7-05方法输入下结构反应均大于目标反应,偏于安全。而按该文方法输入存在高估和低估结构反应的情况,建议附加"在0.2T₁~1.5T₁（T₁为结构基本周期）区间内,3条地震波的平均谱应在目标谱上方"这一限制条件,以防止低估结构反应的情况发生。     

基于贝叶斯理论的结构件健康状态评估方法研究

以结构件裂纹扩展过程中的健康状态评估为研究对象,针对结构件健康状态评估过程中广泛存在的Weibull型数据的特征,通过将Weibull型分布数据类型与贝叶斯理论相结合来提出了一种基于贝叶斯理论的结构件健康状态评估模型,并通过采用MCMC算法对复杂后验量的计算问题进行了求解。运用声发射手段对实例构件的健康状态数据进行了采集,基于贝叶斯理论的结构件健康状态评估模型对实例构件的健康状态进行了评估,评估结果表明5%与95%两个分位数构成了结构件健康状态评估参数的90%置信区间,后验参数的分布集中,且置信度达到90%,可以实现结构件健康状态的精确评估。     

地铁上盖层间隔震建筑设计研究

层间隔震技术是提升地铁上盖结构抗震性能的有效措施。为识别影响该类结构关键设计指标的控制因素,从而指导该类结构的精细设计,依托一大底盘-双塔楼地铁上盖层间隔震工程案例,考虑了3种塔楼方案和4种隔震层方案,设计了12个分析案例。基于精细模型分析了塔楼、隔震层和大底盘相对刚度比和隔震层屈重比对9个关键设计指标的影响规律,包括塔楼和大底盘的中震减震系数、大震最大层间位移角和楼面绝对加速度,以及隔震层的大震位移、极大面压和极小面压,识别了影响各设计指标的关键影响因素。结果表明:对于塔楼,减震系数和楼面最大绝对加速度的控制因素是隔震层刚度和屈重比,减小两者可以取得更好的控制效果,增大塔楼刚度也会存在一定的控制效果,但相对有限;增大塔楼刚度和减小隔震层刚度及屈重比可以一定程度控制塔楼最大层间位移角,当两者达到一定程度后控制效果均趋于稳定。对于大底盘,塔楼和隔震层对其设计指标影响相对较小。对于隔震层,隔震层刚度及屈重比是大震隔震层位移的主要控制因素,其减小会显著增大该位移;塔楼刚度是极大面压的控制性因素,刚度的增大会带来重力的增大,从而带来极大面压的增大;增大塔楼刚度和减小隔震层刚度均可显著控制支座中的拉应力,其中塔楼刚度的增大效果更为突出。该研究的相关成果可为地铁上盖层间隔震建筑的抗震性能控制和设计提供参考。     

基于分布参数模型的多高层建筑楼面加速度研究EI北大核心CSCD

建筑非结构构件的抗震分析方法及其性能评估愈发受到关注和研究。其中,对楼面加速度需求进行研究可合理确定加速度敏感型非结构构件的地震作用。该研究通过分布参数模型对多高层建筑结构进行简化,建立楼面加速度与地震输入和结构特征的联系,研究了弯剪刚度比对结构动力特性、模态振型的影响;基于模型各阶频率比与弯剪刚度比的关系,提出识别结构弯剪刚度比的方法;选用ATC-63的远近场强震动记录数据集,预测了楼面加速度放大(floor acceleration amplification, FAA)系数,回归拟合了楼面加速度与结构阻尼比、周期、刚度比之间的关系,可用于对楼面加速度的预测。     

圆钢管再生混凝土柱抗震性能与影响因素分析

为了研究圆钢管再生混凝土柱的抗震性能,以再生粗骨料取代率、长细比、轴压比和含钢率为变化参数,设计10个圆钢管再生混凝土柱试件进行低周反复加载试验,观察了其破坏过程及形态,获取其荷载-位移滞回曲线。基于试验实测数据基础,深入分析了各变化参数对强度、刚度、位移延性和耗能系数等抗震性能指标的影响规律。研究结果表明:在破坏形态上,钢管再生混凝土柱与普通钢管混凝土柱相似,均表现为底部钢管鼓曲、混凝土被压碎。钢管再生混凝土柱的滞回曲线饱满,其形状从梭形发展到弓形。钢管再生混凝土柱的各项抗震性能指标能满足现有抗震规范要求,在地震区推广应用钢管再生混凝土柱可行。随着长细比的减小,试件耗能系数减小,而其他抗震性能指标增加。除刚度随轴压比的减小而减小外,其他抗震性能指标对现有的设计参数变化范围并不敏感。试件壁厚优势在强度、弹性阶段刚度和破坏点耗能系数等方面表现较为显著。     

A simplified framework for probabilistic earthquake loss estimation

Earthquake loss estimation procedures exhibit aleatory and epistemic uncertainty imbedded in their various components; i.e. seismic hazard, structural fragility, and inventory data. Since these uncertainties significantly affect decision-making, they have to be considered in loss estimation to inform decision- and policymakers and to ensure a balanced view of the various threats to which society may be subjected. This paper reviews the uncertainties that affect earthquake loss estimation and proposes a simple framework for probabilistic uncertainty assessment suitable for use after obtaining impact results from existing software, such as HAZUS-MH. To avoid the extensive calculations required for Monte Carlo simulation-based approaches, this study develops an approximate method for uncertainty propagation based on modifying the quantile arithmetic methodology, which allows for acceptable uncertainty estimates with limited computational effort. A verification example shows that the results by the approximation approach are in good agreement with the equivalent Monte Carlo simulation outcome. Finally, the paper demonstrates the proposed procedure for probabilistic loss assessment through a comparison with HAZUS-MH results. It is confirmed that the proposed procedure consistently gives reasonable estimates.     

Uncertainty Analysis of Thermophysical Property Measurements of Solids Using Dynamic Methods

This work reports on an analysis of thermophysical properties (thermal conductivity, thermal diffusivity, and specific heat capacity) measurements of solids using dynamic methods. The influence of temperature measurement uncertainty on the parameter estimation uncertainty is studied using a least-squares procedure. The standard and difference analyses are used for optimizing the experiment with respect to the data window or time interval of measurements. The analysis is applied to the extended dynamic plane source method, and the results of numerical computations are illustrated in the form of contour plots.     

密闭空间爆炸温度动态不确定度评估方法研究

融合了灰色模型GM(1,1)、Bootstrap方法以及不确定度评定理论,建立了密闭空间内爆炸温度动态测量不确定度的灰自助评估模型GBM(1,1),选取某次爆炸试验300s的温度数据作为分析数据,运用估计真值、估计区间和平均不确定度等参数表征其估计结果。实验结果表明,GBM(1,1)模型融合了灰色模型GM(1,1)和Bootstrap方法的优势,可以准确模拟动态测量数据的概率分布,并实时跟踪被测量瞬时值的变化趋势。相比于灰色模型GM(1,1)和Bootstrap方法,灰自助模型GBM(1,1)具有更高的真值估计准确度和区间估计可靠度,其估计误差分布区间为［-12.62, 13.58］,标准差为8.69℃,最大相对误差为1.2%,区间估计可靠度高于90%,估计区间能够较完整地包络被测量的动态波动范围。由此证明GBM(1,1)模型能够对密闭空间内爆炸温度的动态测量不确定度做出准确评估。     

基于分位数函数和Bootstrap分布的不确定度评定研究

最大信息熵方法是基于概率分布评定测量不确度的主要方法之一。其所依赖的高阶矩需要较大样本的测量数据,而校准/检测实验室的测量一般为小样本,故用最大熵方法评定小样本测量不确定度缺乏一定的可靠性。提出了基于分位数函数和概率权重矩作为约束条件的最大信息熵不确定度评定法,把矩的计算从高次降为一次,并结合遗传算法求解概率分布,用Bootstrap分布估计扩展不确定度和包含区间,解决了由分位数区间估计分布不对称所致的复杂计算问题。     

Simultaneously Estimating the Time-Dependent Damping and Stiffness Coefficients with the Aid of Vibrational Data

For the inverse vibration problem a mathematical method is required to determine unknown parameters from the measurement of vibration data. When both damping and stiffness functions are identified, it is a rather difficult problem. In this paper we will propose a feasible method to simultaneously estimate both the time-dependent damping and stiffness coefficients through three mathematical transformations. First, the second-order equation of motion is transformed into a self-adjoint first-order system by using the concept of integrating factor. Then, we transform these two ODEs into two hyperbolic type PDEs. Finally, we apply a one-step group preserving scheme for the semi-discretizations of PDEs to obtain two uncoupled algebraic equations, of which the first one is used to estimate the damping coefficient while the second one is used to estimate the stiffness coefficient. The estimated results are acceptable for that used in vibrational engineering. We also discuss the use of velocity and acceleration data as inputs in the estimation. However, it leads to a bad result, and is not suggested for the use in estimation.     

Maximum-Likelihood Data Fusion of Phase-Difference and Threshold-Detection Techniques for Wind-Speed Measurement

Analyses of threshold-detection and phase-difference techniques for wind-speed measurement using ultrasonic transducers are presented. The influence of uncertainties that are associated with additive noise and attenuation of the ultrasonic signal on the wind-speed measurement uncertainty is analyzed. A data-fusion procedure based on the maximum-likelihood estimation (MLE) algorithm is developed for the determination of wind speed, with data gathered through threshold-detection and phase-difference techniques. The data-fusion procedure provides a lower measurement uncertainty than those obtained with the above techniques when taken separately. Practical design issues are considered, and an application example is shown to illustrate the proposed procedure.      

线性参数累积法处理时的精度估计

精度估计是线性参数处理中重要的一部分，而累积法是进行线性参数处理的一种新方法。为此在简述了普通累积法的概念和进行线性参数估计的原理之后，推导出了等精度测量时线性参数精度估计的计算过程和公式，并以测量铜棒长度和线性膨胀系数为例，对其进行了精度估计。结果表明，计算过程简便、公式正确。对于不等精度测量，只需要转化为等精度测量即可。     

Integration of computation and testing for reliability estimation

This paper develops a methodology to integrate reliability testing and computational reliability analysis for product development. The presence of information uncertainty such as statistical uncertainty and modeling error is incorporated. The integration of testing and computation leads to a more cost-efficient estimation of failure probability and life distribution than the tests-only approach currently followed by the industry. A Bayesian procedure is proposed to quantify the modeling uncertainty using random parameters, including the uncertainty in mechanical and statistical model selection and the uncertainty in distribution parameters. An adaptive method is developed to determine the number of tests needed to achieve a desired confidence level in the reliability estimates, by combining prior computational prediction and test data. Two kinds of tests — failure probability estimation and life estimation — are considered. The prior distribution and confidence interval of failure probability in both cases are estimated using computational reliability methods, and are updated using the results of tests performed during the product development phase.     

Reliability analysis of multi‐state series systems with performance sharing mechanism under epistemic uncertainty

For real engineering systems, it is sometimes difficult to obtain sufficient data to estimate the precise values of some parameters in reliability analysis. This kind of uncertainty is called epistemic uncertainty. Because of the epistemic uncertainty, traditional universal generating function (UGF) technique is not appropriate to analyze the reliability of systems with performance sharing mechanism under epistemic uncertainty. This paper proposes a belief UGF (BUGF)‐based method to evaluate the reliability of multi‐state series systems with performance sharing mechanism under epistemic uncertainty. The proposed BUGF‐based reliability analysis method is validated by an illustrative example and compared with the interval UGF (IUGF)‐based methods with interval arithmetic or affine arithmetic. The illustrative example shows that the proposed BUGF‐based method is more efficient than the IUGF‐based methods in the reliability analysis of multi‐state systems (MSSs) with performance sharing mechanism under epistemic uncertainty.     

Reliability assessment for failure-dependent and uncertain systems: A Bayesian network based on copula method and probability-box

Managing failure dependence of complex systems with hybrid uncertainty is one of the hot problems in reliability assessment. Epistemic uncertainty is attributed to complex working environment, system structure, human factors, imperfect knowledge, etc. Probability-box has powerful characteristics for uncertainty analysis and can be effectively adopted to represent epistemic uncertainty. However, arithmetic rules on probability-box structures are mostly used among structures representing independent random variables. In most practical engineering applications, failure dependence is always introduced in system reliability analysis. Therefore, this paper proposes a developed Bayesian network combining copula method with probability-box for system reliability assessment. There are four main steps involved in the reliability computation process: marginal distribution identification and estimation, copula function selection and parameter estimation, reliability analysis of components with correlations and Bayesian forward analysis. The benefits derived from the proposed approach are used to overcome the computational limitations of n-dimensional integral operation, and the advantages of useful properties of copula function in reliability analysis of systems with correlations are adopted. To demonstrate the effectiveness of the developed Bayesian network, the proposed method is applied to a real large piston compressor.