Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

An efficient probabilistic design approach for tunnel face stability by inverse reliability analysis

In order to maintain the safety of underground constructions that significantly involve geo-material uncertainties,this paper delivers a new computation framework for conducting reliability-based design(RBD)of shallow tunnel face stability,utilizing a simplified inverse first-order reliability method(FORM).The limit state functions defining tunnel face stability are established for both collapse and blow-out modes of the tunnel face failure,respectively,and the deterministic results of the tunnel face support pressure are obtained through three-dimensional finite element limit analysis(FELA).Because the inverse reliability method can directly capture the design support pressure according to prescribed target reliability index,the computational cost for probabilistic design of tunnel face stability is greatly reduced.By comparison with Monte Carlo simulation results,the accuracy and feasibility of the proposed method are verified.Further,this study presents a series of reliability-based design charts for vividly understanding the limit support pressure on tunnel face in both cohesionless(sandy)soil and cohesive soil stratums,and their optimal support pressure ranges are highlighted.The results show that in the case of sandy soil stratum,the blowout failure of tunnel face is extremely unlikely,whereas the collapse is the only possible failure mode.The parametric study of various geotechnical uncertainties also reveals that ignoring the potential correlation between soil shear strength parameters will lead to over-designed support pressure,and the coefficient of variation of internal friction angle has a greater influence on the tunnel face failure probability than that of the cohesion.

Design for a Crane Metallic Structure Based on Imperialist Competitive Algorithm and Inverse Reliability Strategy

Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization （RBDO） offers a more reasonable design approach. However, existing RBDO methods for crane metallic structures are prone to low convergence speed and high computational cost. A unilevel RBDO method, combining a discrete imperialist competitive algorithm with an inverse reliabil- ity strategy based on the performance measure approach, is developed. Application of the imperialist competitive algorithm at the optimization level significantly improves the convergence speed of this RBDO method. At the reli- ability analysis level, the inverse reliability strategy is used to determine the feasibility of each probabilistic constraint at each design point by calculating its a-percentile per- formance, thereby avoiding convergence failure, calcula- tion error, and disproportionate computational effort encountered using conventional moment and simulation methods. Application of the RBDO method to an actual crane structure shows that the developed RBDO realizes a design with the best tradeoff between economy and safety together with about one-third of the convergence speed and the computational cost of the existing method. This paper provides a scientific and effective design approach for the design of metallic structures of cranes.

Modeling Reliability Engineering Data Using Scale-Invariant Quasi-Inverse Lindley Model

An important property that any lifetime model should satisfy is scale invariance.In this paper,a new scale-invariant quasi-inverse Lindley(QIL)model is presented and studied.Its basic properties,including moments,quantiles,skewness,kurtosis,and Lorenz curve,have been investigated.In addition,the well-known dynamic reliability measures,such as failure rate(FR),reversed failure rate(RFR),mean residual life(MRL),mean inactivity time(MIT),quantile residual life(QRL),and quantile inactivity time(QIT)are discussed.The FR function considers the decreasing or upside-down bathtub-shaped,and the MRL and median residual lifetime may have a bathtub-shaped form.The parameters of the model are estimated by applying the maximum likelihood method and the expectation-maximization(EM)algorithm.The EM algorithm is an iterative method suitable for models with a latent variable,for example,when we have mixture or competing risk models.A simulation study is then conducted to examine the consistency and efficiency of the estimators and compare them.The simulation study shows that the EM approach provides a better estimation of the parameters.Finally,the proposed model is fitted to a reliability engineering data set along with some alternatives.The Akaike information criterion(AIC),Kolmogorov-Smirnov(K-S),Cramer-von Mises(CVM),and Anderson Darling(AD)statistics are used to compare the considered models.

Using Long-Period Body Wave to Inverse Moment Tensors of the M_S6.8 Jiashi,Xinjiang Earthquake in 2003 and the Moderate and Small Earthquakes before and after It

An M_S6.8 strong earthquake took place in Jiashi,Xinjiang on February 24 of 2003.The digital wave form data recorded in Kashi and Wushi stations are selected to inverse the moment tensor solutions for the strong earthquake and the moderate and small earthquakes before and after it(108 earthquakes in 2001～2004).67 focal mechanism solutions have been calculated,and the results agree with those from Harvard University and USGS.The analysis reveals that before the strong earthquake,the moderate and small earthquake distribution was dispersed,and after the event the distribution was mainly concentrated around the strong earthquake.Before the strong earthquake,the seismic faults of the mid and small events had the character of strike-slip and normal faulting,and after the event,they exhibit strike-slip and thrust faulting.The region is dominated by near-NS horizontal compression from the southern block after the strong earthquake.

高置信水平结构逆可靠度分析与优化方法研究进展

不确定性客观存在于工程结构生产制造以及服役等各环节之中并对结构的承载性能影响显著.特别是对于服役条件苛刻的航空航天承载装备,在设计阶段考虑多源不确定性的影响对于结构安全至关重要.在众多不确定性分析方法中,逆可靠度分析方法在效率和稳健性方面具有一定优势.为此,国内外学者在高置信水平结构逆可靠度分析与优化方法方面开展了大量研究并取得了长足进步,包括自适应迭代控制算法、先进可靠度优化策略与非充分样本下的高置信水平设计方法等.本文首先对国内外逆可靠度分析与优化方法取得的进展进行了系统梳理与总结,特别是逆可靠度分析方法的发展历程以及面临的挑战问题,主要包括强非线性功能函数、多设计点以及低失效概率问题.进一步,针对长期困扰可靠度方法实际应用的小样本问题,重点从结构高置信水平可靠度分析与优化理论角度开展系统介绍,详细论述了小样本诱发的认知不确定性到可靠度置信水平的传播链条.最后,基于现有成果和国家重大前沿需求,重点围绕航天装备可重复使用需求对结构可靠度未来研究方向进行了思考与展望,期望相关研究成果能够进一步助力我国航空航天结构实现高可靠性与极致轻量化设计.

踝护具内翻防护性能仿真测试系统研究及踝护具内翻防护性能评价

目的旨在开发一种踝护具内翻防护性能仿真测试系统,以客观地评价踝护具的内翻防护性能、替代人体试验、减少主观因素及个体差异对测试结果的影响。方法踝护具内翻防护性能仿真测试系统主要包括人体踝关节仿真模型、动力机构和着陆斜台等,以模拟人体高空着陆过程。以新型非对称半刚性防护型踝护具为实验对象,以传统踝护具与裸足作为对照,评价指标为踝关节最大内翻角,验证系统的可行性与可靠性。结果踝护具内翻防护性能仿真测试系统结构简单、操作便捷、可重复性好。测试结果客观、数据离散小,能够客观反映踝护具的内翻防护性能,表明新型非对称半刚性踝护具具有良好的内翻防护性能。结论本研究解决了人体试验数据重复性低、离散大等问题,可为进一步推动踝护具内翻防护性能评价标准的建立提供参考。

融合多源信息的降雨入渗边坡概率反分析及可靠度预测

概率反分析是推断不确定土体参数统计特征的重要手段,可以使边坡可靠度评估更接近工程实际。然而目前的概率反分析很少使用多源信息(包括监测数据、观测信息和边坡服役记录),因为这通常涉及数千个随机变量和高维似然函数的评估。因此融合多源信息对空间变异土体参数进行概率反分析进而预测降雨条件下的边坡可靠度是一项具有挑战性的难题。文章将改进的基于子集模拟的贝叶斯更新(mBUS)方法与自适应条件抽样(aCS)算法相结合,构建了空间变异土体参数概率反分析和边坡可靠度预测的框架,并以某一公路边坡为例验证了该框架的有效性。研究结果表明:通过融合多源信息所获得的土体参数后验统计特征与现场观测结果基本吻合;用更新后的土体参数预测得到2004年9月12日该边坡在暴雨工况下的失效概率为23.1%,符合实际边坡失稳情况,说明在此框架下可以充分利用多源信息解决高维概率反分析问题。

RELIABILITY-BASED DESIGN OF COMPOSITES UNDER THE MIXED UNCERTAINTIES AND THE OPTIMIZATION ALGORITHM

This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites.

The reliability of AlGaN/GaN high electron mobility transistors under step-electrical stresses

In spite of their extraordinary performance, AlGaN/GaN high electron mobility transistors （HEMTs） still lack solid reliability. Devices under accelerated DC stress tests （off-state, VDS = 0 state, and on-state step-stress） are investigated to help us identify the degradation mechanisms of the AlGaN/GaN HEMTs. All our findings are consistent with the degradation mechanism based on crystallographic-defect formation due to the inverse piezoelectric effects in Ref. [1] （Joh J and del Alamo J A 2006 IEEE IDEM Tech. Digest p. 415）. However, under the on-state condition, the devices are suffering from both inverse piezoelectric effects and hot electron effects, and so to improve the reliability of the devices both effects should be taken into consideration.

基于机器学习的斜拉索装配容差区间反演方法

为了量化斜拉索在安装过程中抵抗施工误差干扰的能力,从而提高斜拉桥工业化建造可施工性,提出了一种挖掘装配容差性能的区间反演框架,采用可靠度区间下界描述多源不确定性的极端干扰,将反演过程作为一个可靠性约束的多目标优化问题求解,开发了基于机器学习的解耦式预测算法,通过集成有限元响应预测、可靠度边界计算与代理模型构建,实现了最不利可靠度指标的直接映射。通过算例对斜拉桥的斜拉索装配过程进行了容差规划,结果表明:将不确定性合理量化后,目标斜拉索能容许的最大施工张拉力误差可达到217.4~317.3 kN,其抗误差干扰率为7.29%~12.98%。区间反演方法可以显著避免多重嵌套寻优产生的巨量算力消耗;在保证结构可靠性与设计最优性前提下,有效提升了现场张拉过程的兼容性和可控性。

基于可靠度的变压器声功率遗传算法研究

换流变压器是高压直流换流站中主要的噪声源,对换流变压器噪声的预测精度直接影响到后期整个换流站噪声预测模型的准确性,因此,准确获得换流变压器的声功率至关重要。根据《声学户外声传播衰减第2部分:一般计算方法》(ISO 9613-2:1996)中的户外声传播声功率计算方法,构建了声源声功率反推数学模型。利用某变压器周围大量测点现场实测数据,结合可靠度理论,识别并剔除了实测点中受相干声场影响较大的点,实现了换流变压器声功率反演计算,并对测点个数的选取进行了初步研究及优化。与其他声功率测量方法相比,该方法操作简单,对仪器设备要求较低,适用于复杂的声学环境,具有一定的应用前景。

可靠度下多测点实测值的噪声源声功率反演算法

随着城市化和工业化进程的推进,我国环境问题日益凸显,工业噪声已经成为一大焦点。在工业企业噪声预测及控制中,方便、准确获得工业设备的声功率级,提高噪声预测精度尤为重要。根据国际标准ISO9613-2给出的户外传播计算方法中,通过多测点噪声实测数据与理论计算,利用可靠度理论及优化思想,构建基于声源声功率级反推的数学模型,实现声功率级反演计算。应用该方法对江西某水泥厂噪声预测模型进行研究,通过设置不同可靠度,识别并剔除测点数据中偏差较大的点,可最大限度减小测点噪声值不确定度,实现声源声功率级反演计算,从而减小预测值与实测值的综合误差,提高了噪声预测模型精度。

土工构筑物的逆几何可靠性分析算法

针对特定场地下土工构筑物的正常使用极限状态,考虑钻孔灌注桩、抗浮锚杆或CFG桩单桩荷载-位移测试曲线之间的离散性,将测试曲线拟合得到的回归参数集视作随机变量,基于几何可靠性算法框架,运用高斯Copula函数联合分布模型实施由标准正态空间到原始物理空间中随机变量的表征转换,构建基于概率密度等值线的逆几何可靠性算法。该算法假定描述随机变量服从正态分布的某一参数(均值或变异系数)未知,给定目标可靠指标,可推求随机变量的概率密度等值线。通过极限状态方程限定概率密度等值线的几何轮廓,可求解特定目标可靠指标下随机变量的未知均值或变异系数,并求出相应的安全系数。当随机变量服从其他非正态边缘分布时,等值线的几何轮廓仍由一系列离散点近似表征,逆可靠性分析同样适用。建议的算法主要用于解决随机变量部分统计参数缺失或不完备的难题,给定目标可靠指标时可根据构筑物重要性等级进行安全系数校准。

一近海风力机结构响应分析的改进预报方法

为了克服传统的罗森布拉特IFORM(反一阶可靠性法)环境轮廓法的缺点,提出用主成分分析-反一阶可靠性轮廓法来生成更精确的环境轮廓。比较使用主成分分析-反一阶可靠性轮廓法和用罗森布拉特IFORM环境轮廓法获得的一选定近海地点的环境轮廓,以验证主成分分析-反一阶可靠性轮廓法的精度和有效性。接着基于主成分分析-反一阶可靠性轮廓法或罗森布拉特IFORM环境轮廓法得到的最高非线性海况计算一安装在这一选定近海地点的单桩支持型5 MW近海风力机的50年极端结构动力响应。系统地分析和比较计算结果,突出强调利用更符合实际的环境轮廓(如用主成分分析-反一阶可靠性轮廓法所生成的)的必要性和重要性。

基于区间优化算法的电力系统可靠性评估逆问题模型

电力系统可靠性评估逆问题是指从已知的可靠性指标值出发求取未知的元件可靠性参数的问题,是电力系统可靠性领域一个重要的潜在研究方向。只有在待求可靠性参数个数与可靠性指标个数相等的特殊情形下,采用现有的逆问题研究方法才能取得参数的准确值。针对以上不足,首先,基于可靠性指标解析计算函数,构建逆问题的非线性方程组模型。其次,为计及已知可靠性指标个数大于、等于或小于待求参数个数的3种情形,将方程组模型转化为优化问题,建立逆问题的一般性模型。针对逆问题存在多解的情形,以可靠性参数优化为例,说明如何构建对应于具体工程问题的逆问题模型。然后,提出基于改进区间优化算法的逆问题求解方法,该方法能够在逆问题的不同情形之间进行切换,并确保求得最优解。最后,将所提方法应用于RBTS、IEEE-RTS系统和91节点系统,算例结果表明:针对逆问题的上述3种情形,采用所提方法均可有效求得准确的元件可靠性参数。

基于初值修正的电力元件可靠性参数校正

由于元件停运记录的疏漏,少部分元件可靠性参数统计值可能存在错误。错误的可靠性参数会导致误差较大的评估结果,进而影响电网的规划和运行决策,因此,有必要辨识并校正错误可靠性参数。在该背景下,本文利用电力系统可靠性评估逆问题理论,提出基于初值估计策略的元件可靠性参数辨识和校正方法。首先,提出可靠性参数辨识与校正效果的评价指标。其次,采用具有全局寻优能力的改进粒子群优化算法,估计敏感可靠性参数。然后,采用基于参数初值动态修正的滚动估计算法,估计全体参数,并根据各参数估值与其统计值的偏差,辨识错误参数。最后,利用区间算法校正错误参数。算例表明:当系统中参数错误的元件占比不超过9%时,所提模型及算法可辨识出全部错误参数,且其校正结果的误差在1%以内。

数控机床可靠性加速试验与评估研究

针对数控机床可靠性快速测评技术研究不足、行业内缺少相应的可靠性快速测评方法的问题,提出一种基于修正应力的逆幂律模型评估方法。首先,应用AHP方法建立加速应力层次修正结构对加速应力进行修正;其次,基于修正应力的加速模型确定了试验的总体试验方案、流程、剖面以及数据采集方式,并采用修正应力对逆幂律模型进行求解;最后,在某型号国产数控弯管机上开展可靠性加速测评试验。对试验数据中的加速应力应用该方法进行修正并与同型号设备跟踪统计常规试验结果对比,威布尔形状参数的相对误差由7.5%降低至4.7%,MTBF点估计值得相对误差由16.9%降低至5.9%,验证了本测评方法的可行性和准确性。

机场中压供电可靠性研究

以某机场为例,指出机场中压供电系统存在的问题。通过逐步优化中压供电方案,采用一套市电侧的备自投及两套中压ATS解决计量柜分段计量和柴油发电机(以下简称“油机”)电源倒送电的问题,提高了整个机场的供电可靠性。

可靠性理论在边坡反分析中的运用

将反分析方法和可靠性理论相结合,分析了两者的异同点和存在的问题,提出了一种方便而实用计算方法用于在边坡反算中选择岩土体参数,该方法给出了在统计信息有限的情况下,如何处理各参数均值的思路。