岩土工程可靠度分析的改进四阶矩方法

岩土工程可靠度分析中,功能函数往往呈隐式且具有强非线性性质,而目前最为实用的矩方法,如JC法、二次二阶矩法,主要适用于显式功能函数情形。为此,将高效的统计矩估计方法和可靠度分析的高阶矩法相结合,提出了一种岩土工程可靠度分析的改进四阶矩方法。首先,通过引入变量的独立化变换和线性变换将功能函数转换为参考变量的函数,并结合多变量函数的单变量降维近似方法和参考变量计算节点与权系数的确定方法,建立了功能函数前四阶矩的高效点估计法。然后,将上述统计矩与立方正态变换假设相结合,提出了易于实现的岩土工程可靠度分析的改进四阶矩方法。最后,由数学算例验证了统计矩估计方法的效率和精度,并通过经典的岩土工程算例验证了建议的改进四阶矩方法具有高效率、高精度且操作简单等特点。     

岩土工程可靠度分析的改进响应面法研究

为了提高响应面法的计算效率和精度,对现有的全局响应面法进行了改进。采用径向基函数（RBF）神经网络,代替目前常用的BP网络,迭代过程中在超锥体的范围内构造响应面,逼近隐式的非线性功能函数。数值算例分析表明,与通常的响应面法相比,改进全局响应面法的迭代次数和有限元分析次数均大幅减少,节省机时,有利于提高计算精度。同时,以浅基础和挡土墙为工程背景进行可靠度分析,表明该方法能以较快的收敛速度和较少的有限元分析次数,获得较高精度的可靠度指标,适用于岩土工程的可靠度分析。     

Numerical integration method for computing reliability index of geotechnical system

To account for the uncertainties in the design of a geotechnical system, reliability-based design approach is often adopted, in which the main task is to evaluate reliability index of the system based on a performance function (or limit state function). In this paper, we propose a new method for computing the reliability index, based upon the numerical integration of the cumulative distribution function (CDF) of the performance function. This numerical integration method requires only a deterministic evaluation of the system performance and the joint probability of the uncertain input parameters. The effectiveness and the efficiency of the proposed method, measured in terms of the accuracy and the computational effort, respectively, are demonstrated with two geotechnical problems: a drilled shaft in sand and a semi-gravity retaining wall. The new method is found valid regardless of the type of distribution of uncertain input parameters, whether the correlations exist among these input parameters, whether the system involves single or multiple failure modes, and how the performance function is formulated.     

岩土工程可靠度分析的神经网络四阶矩法

针对岩土工程的功能函数强非线性且难以显式表达的特点,提出了基于人工神经网络的四阶矩法,充分利用了基本随机变量的统计信息。首先利用神经网络对结构的隐式功能函数进行拟合,求得基本随机变量在均值点处的功能函数值及其偏导数,然后利用泰勒级数展开的方法由基本随机变量的前四阶矩求得功能函数的前四阶矩,并借助于Pearson系统获得功能函数的更高阶矩。在此基础上,通过最大熵原理确定以功能函数各阶矩为约束的功能函数的概率密度函数,最后由一次积分得到结构的失效概率。通过数值算例和工程实例不同方法的对比分析,表明基于神经网络的结构可靠度分析四阶矩方法是可行的,有效的,能够满足岩土工程可靠度分析的要求。     

An adaptive high-dimensional model representation method for reliability analysis of geotechnical engineering problems

In this study, a new reliability analysis method was developed based on the adaptive high-dimensional model representation (HDMR) and applied to geotechnical engineering problems. For practical problems requiring finite element (FE) analysis or other numerical methods to evaluate system responses such as stresses and deformations, an efficient and accurate metamodeling technique is needed because it is not efficient or straightforward to directly adopt the conventional sampling-based or gradient-based reliability analysis approaches. In this work, an adaptive metamodeling approach was created and studied based on the HDMR framework and augmented radial basis functions (ARBFs). In this adaptive ARBF-HDMR technique, a simple and inexpensive first-order ARBF-HDMR metamodel was first constructed to explicitly express a performance function, and an alternate first-order reliability method (FORM) was applied to locate the design point and compute the reliability index. A local window was then defined such that additional sample points were generated and a higher-order HDMR component function was created using ARBF and added to the existing ARBF-HDMR metamodel. The accuracy of the ARBF-HDMR metamodel was improved through this adaptive process, especially in the region surrounding the design point. One mathematical and four geotechnical engineering problems were studied and solved using the proposed adaptive ARBF-HDMR approach. The proposed method was found to be capable of obtaining accurate reliability indices within a few iterations in all test problems.     

Use of evolutionary computing for modelling some complex problems in geotechnical engineering

In this paper, the feasibility of using evolutionary computing for solving some complex problems in geotechnical engineering is investigated. The paper presents a relatively new technique, i.e. evolutionary polynomial regression (EPR), for modelling three practical applications in geotechnical engineering including the settlement of shallow foundations on cohesionless soils, pullout capacity of small ground anchors and ultimate bearing capacity of pile foundations. The prediction results from the proposed EPR models are compared with those obtained from artificial neural network (ANN) models previously developed by the author, as well as some of the most commonly available methods. The results indicate that the proposed EPR models agree well with (or better than) the ANN models and significantly outperform the other existing methods. The advantage of EPR technique over ANNs is that EPR generates transparent and well-structured models in the form of simple and easy-to-use hand calculation formulae that can be readily used by practising engineers.     

Implementing statistical fitting and reliability analysis for geotechnical engineering problems in R

Reliability analysis and multivariate statistical fitting are valuable techniques that enhance the scientific basis of regulatory decisions in geotechnical problems. This study introduces the use of several R packages specifically developed to assist risk assessors in their geotechnical projects. Firstly, the fitting of parameterised models either to the distribution of observed samples or to characterise the dependence structures among variables, or both is presented. Secondly, the most popular reliability analysis methods, such as the first- and second-order reliability methods and the random sampling simulation method, are implemented in R. The efficiency of implementing these classical approximation methods is demonstrated through two example problems.     

微波加热在岩土工程中的应用

介绍了微波具有的特性以及微波加热原理,包括偶极极化、离子导电和界面极化三种机制。综述了微波加热技术在岩土工程领域的相关应用,例如快速测定土的含水量、处理固体废弃物、破碎岩石等,概述了该技术在融解冻土、淤泥土脱水、公路再生沥青修复技术方面的成果,并且提出微波加热技术可应用于减少有机土有机物含量、加热快速固结软土,以及微波加热研究的具体方向,期望能推动微波加热技术在岩土工程领域的推广。     

浅部厚层粉性土分层中的一些问题

上海市沿江地区浅部粉性土具有厚度大、物理力学性质复杂多变的特征.文章就该层土的岩土工程分层进行专门讨论.     

扁铲侧胀试验在软土地基评价中的应用研究

在回顾分析国内外利用扁铲侧胀试验评价地基土性参数基础上,介绍了应用扁铲侧胀试验（DMT）和其它试验手段进行高速公路软土地基综合分析评价所取得的一些成果。根据扁铲侧胀试验结果估算的不排水抗剪强度与十字板试验结果基本一致,并能够反映土的强度随深度增长的规律,也分析了造成扁铲侧胀试验结果与室内试验结果之间差异的因素,研究结果可为扁铲侧胀试验在我国岩土工程领域的应用提供参考。     

波速测试在岩土工程中的应用

通过波速测试技术进行岩土体弹性波速度原位测试,利用岩土体的纵、横波速度值能够进行场地类别划分,确定场地卓越周期,以及计算地基土的动参数,为岩土工程提供必要的设计参数。通过计算获得了徐州苏宁广场场地土的纵、横波速度以及场地土的动参数,根据《建筑抗震设计规范》确定徐州苏宁广场场地为二类场地,利用波速值计算场地卓越周期为0. 415 s与规范中查表获得的特征周期一致。为该工程场地工程地质评价和抗震设计提供了丰富的参数。     

一个新的全局优化算法在岩土工程反分析中的应用

DCD(dynamic canonical descent)算法是一个新的全局优化算法,运用该法进行优化时,无需考虑目标函数的可微性,只要正确给定优化变量的优化区间,且该区间具有凸性,那么此算法就能很好地收敛于该区间的全局极小点.针对该算法,建立了相应的算法迭代格式.对数值试验和在岩土工程位移反分析的应用中引入该算法的迭代格式进行全局优化反演,其结果表明:该算法稳定性强,优化结果的可靠度高,收敛速度较快.     

泥质软岩地基水平抗力系数研究

通过室内水平静载试验和数值模拟对泥质软岩地基水平抗力系数的比例系数m进行研究,给出m值参考值,并讨论了影响地基岩土m值的因素,研究结果表明：试验所用的南宁盆地第三系泥岩m值取值范围为17～35 MN/m4,桩径大时取小值,埋深大时取大值;用ANSYS模拟水平静载试验,计算出的m值与室内试验值十分接近,可为今后数值计算m值提供参考。经分析m值的影响因素后认为适当增加桩的埋深、控制岩土含水率及提高混凝土的浇灌质量等可以提高m值     

地基非线性沉降计算原状土切线模量法的推广和应用

根据原状地基的载荷试验曲线,对于试验曲线为任意形式的情况下,提出了直接应用实测压板试验的P-S曲线,依据应力水平确定原状土切线模量的一般方法,建立了应力水平与原状土切线模量的关系。用该切线模量对地基沉降进行分层总和法计算,反映了原状地基土的特点和土的非线性,可以用于较准确地进行地基的沉降计算,且可以计算地基的非线性沉降过程,同时可以克服原切线模量法中假设压板试验曲线为双曲线方程的限制,使原状土切线模量法能应用于更广的范围。通过实例说明了方法的可行性     

岩土工程勘察中桩基参数的综合取值方法

桩基础勘察中采用综合取值法提供的各土层的桩侧极限摩阻力和桩端极限端阻力,在单桩竖向极限承载力静载荷破坏性试验检测中得到验证,用该方法提供的桩基参数能够满足设计对单桩承载力特征值的要求。从工程桩破坏性试验的角度再次对该方法提供的桩基参数进行论证,采用反向对比计算,结果表明这种取值方法提供的桩基参数较为接近土层的真实应力状态。     

浅基础沉降可靠性的Neumann随机有限元分析

将随机土性分布参数模拟为随机场，用矩形和任意四边形局部平均随机场单元来离散随机场，对随机场离散技术和自协方差矩阵的组集方法进行了研究，提出了多维相关正态分布随机数的计算机模拟方法，同摄动随机有限元和直接Monte-Carlo随机有限元相比，Neumann随机有限元具有较好的计算精度和计算效率，研制了Neumann随机有限元的程度，考虑荷载变异性和土性分布参数的变异性，用Neumann随机有限元法进行地基沉降和非均沉降的概率分析。     

Optimization techniques for identifying soil parameters in geotechnical engineering: Comparative study and enhancement

A comparative study of optimization techniques for identifying soil parameters in geotechnical engineering was first presented. The identification methodology with its 3 main parts, error function, search strategy, and identification procedure, was introduced and summarized. Then, current optimization methods were reviewed and classified into 3 categories with an introduction to their basic principles and applications in geotechnical engineering. A comparative study on the identification of model parameters from a synthetic pressuremeter and an excavation tests was then performed by using 5 among the mostly common optimization methods, including genetic algorithms, particle swarm optimization, simulated annealing, the differential evolution algorithm and the artificial bee colony algorithm. The results demonstrated that the differential evolution had the strongest search ability but the slowest convergence speed. All the selected methods could reach approximate solutions with very small objective errors, but these solutions were different from the preset parameters. To improve the identification performance, an enhanced algorithm was developed by implementing the Nelder‐Mead simplex method in a differential algorithm to accelerate the convergence speed with strong reliable search ability. The performance of the enhanced optimization algorithm was finally highlighted by identifying the Mohr‐Coulomb parameters from the 2 same synthetic cases and from 2 real pressuremeter tests in sand, and ANICREEP parameters from 2 real pressuremeter tests in soft clay.     

岩土工程可靠度分析中方差折减函数确定的一般规律

将可靠度理论应用于岩土工程稳定性分析过程中,即使是已证明安全的工程所得到的边坡或地基的失效概率通常较大,导致这一现象的原因是估算的方差偏大。计算土性指标的试验数据仅表征了该试验点的特征,而不是空间平均特征。在随机场理论应用于岩土工程可靠度分析的过程中,方差折减函数是将点特性过渡为空间平均特性的必要参数。首次对闫澍旺等提出的完全不相关距离理论中完全不相关距离的确定方法进行改进,不但理论上有所突破,而且计算方法更为简洁。对折减函数值的确定过程进行了分析,得到了用完全不相关距离方法确定折减函数的一般规律。     

均匀设计在岩土工程概率分析中的应用

基于神经网络的响应面蒙特卡罗方法,通过引入均匀设计来安排RBF神经网络的训练样本集,将均匀设计和RBF网络的优势有机地结合起来：一方面尽量减少训练样本点的数量;另一方面,训练样本点均匀地充满参数空间,有利于提高具有较强局部逼近能力的RBF网络的预测精度。应用该方法进行挡土墙结构抗滑移稳定性的概率分析,结果表明该方法与直接蒙特卡罗模拟的结果相当吻合,能够满足实际工程的精度要求。分析还表明,随机因素对挡土墙结构抗滑移稳定性的影响程度由大到小依次为基底摩擦系数、填土摩擦角、填土重度和填土对挡土墙墙背的摩擦角。     

Distribution of the factor of safety,in geotechnical engineering,for independent piecewise linear capacity and demand density functions

In many geotechnical engineering cases, the factor of safety may be defined as the ratio of the capacity, of the geotechnical structure or its support elements, to the pertinent demand. By representing the capacity and the demand as independent piecewise linear random variables, an analytic solution is obtained for the probability density and cumulative distribution functions of the factor of safety. Thus, solutions for the calculation of the mean value, the standard deviation and the minimum and maximum values of the factor of safety, are provided. Application of the developed analytical solutions, to the probabilistic analysis of a published case of rock spalling in a deposition tunnel complex, follows. The methodology allows for the parametric evaluation of the effect of specific design variables to the distribution of the safety factor and to the probability of failure. The closed form solution may be programmed as a computer code that may run easily on a tablet or netbook or even on a smartphone. It proves useful for the probabilistic design of a variety of geotechnical applications, such as foundations, tunneling, mining, underground roof reinforcement, and earth retaining structures, and permits decisions to be taken in terms of risk and reliability.