Factors of safety and pile load tests

The factor of safety used in designing pile foundations for vertical load should depend on three things, prior information on load capacity summarized by empirical correlations with load capacity models, site specific information derived from load tests, and an objective function reflecting economic and safety considerations. A statistical approach to factor of safety selection was developed in order to suggest improvements of current standards for driven pile design. This approach recognizes a distinction between the variability of pile load capacity within individual sites, and the global variability upon which model correlations are based. Charts have been prepared for determining the FS required to achieve specified reliability indices, as a function of the number of load tests at a particular site and their outcomes.     

评估灌注桩极限承载力的概率能量法

本文研究用概率能量方法评估灌注桩极限承载力的可行性,研究所用数据取自南京市区的２００根桩例的ＣＡＰＷＡＰ反分析与静载试验结果。根据能量守恒定律并结合动态桩－土相互作用模型,详细地推导了桩极限承载力计算公式。并对其中的模型参数,Ｊｓ,Ｊｔ,Ｑｓ,Ｑｔ作为随机变量处理,统计分析了它们的平均值,标准差以及概率分布函数。用蒙特卡洛法模拟确定了桩极限承载力的概率分布函数,并进一步提出了计算桩极限承载力超过某一设计值的概率公式。通过计算的桩极限承载力与静载结果的良好可比性,说明了此方法的台理性与准确性。     

基于Copula函数的CFG桩复合地基载荷-变形曲线的概率分析

CFG桩(cement-fly ash-gravel pile)复合地基是一种重要的地基处理形式,在日益增加的大面积住宅和商业开发中作用越来越突出,然而该种桩型的加卸荷-沉降变形特性仍然需深入研究,尤其在概率评估方面。根据北京星光影视股份有限公司生产科研基地项目工地中的21根CFG桩单桩静载试验和32个复合地基静载试验的原位加卸载测试成果,采用两参数的双曲线或幂曲线回归拟合了每一条加荷-变形曲线。由于土体的内在各向异性和其强度的变异性,评估整个场地的加荷-变形曲线时,其回归参数表现出了较大的离散性。将一个场地的多组回归参数组成一个随机向量,其加载-位移曲线的不确定性可由简单的两变量随机向量体现,引入双变量联结函数（Copula）描述随机回归参数间的相依性。最后,考虑正常使用极限状态,采用基于Copula函数的模拟模型计算了CFG桩复合地基的可靠度指标。研究结果有助于改进CFG桩复合地基的概率设计与评估。     

Characterisation of geotechnical model uncertainty

The calculated response from a numerical model will deviate from the measured one given the presence of modelling idealizations and real world construction effects. This deviation can be directly captured by a ratio between the measured and the calculated quantity. The ratio is also called a model factor in many design guides. The probabilistic distribution of the model factor is arguably the most common and simplest complete representation of model uncertainty. The characterisation of model uncertainty is identified as one of the critical elements in a geotechnical reliability-based design process in Annex D of ISO 2394:2015 “General Principles on Reliability of Structures”. This Spotlight paper reviews the databases for various geo-structures and determines their associated model statistics. Foundation load test databases are the most prevalent. A recent effort to compile a large generic database (PILE/2739) that contains 2739 field load tests conducted on various piles and installed in different soils and countries, is highlighted. This systematic compilation of load test data is part of a broader research agenda to digitalise foundation design for “precision construction”, which is targeted at characterising “site-specific” model factors and soil parameters based on both site-specific and generic data for further customisation of design to a particular site. The mean and COV of the model factor for a range of geo-structures, geomaterials, and limit states (both ultimate and serviceability) are summarized in a form suitable for adoption in design and codes of practice. Based on this summary, it is proposed that a model factor for a design model can be classified as: (1) moderately conservative (1?≤?mean?相似文献   

Serviceability limit state design for uplift of helical anchors in clay

Presently, no displacement-based design methodology exists for helical anchors subjected to tensile or uplift loading. This study investigates the statistical and probabilistic aspects of the load-displacement uncertainty associated with a database of thirty-seven uplift loading tests of helical anchors founded within cohesive soils. Initially, an ultimate resistance model is identified, and the semi-empirical uplift breakout factor statistically characterized. A relationship between ultimate resistance and slope tangent capacity is established, and used to form the basis for normalizing the load-displacement response. Hyperbolic and power law models are statistically evaluated for use in serving as a reference load-displacement model; the hyperbolic curve was selected based on goodness-of-fit statistics. Monte Carlo reliability simulations are used to establish an equivalent-deterministic load factor that associates the selected load factor with a probability of exceeding a pre-determined allowable uplift displacement, given uncertainty in the undrained shear strength, ultimate resistance model, transformation uncertainty, uncertainty in the allowable displacement, and variability in uplift loading. A practical example is provided to show the intended use of this probabilistic helical anchor displacement model.     

基于均匀设计的带桩帽钢管减沉桩承载性能试验研究

采用均匀设计法对桩长、桩距、垫层、桩帽对减沉桩承载性能的影响进行室内模型试验研究。通过6组3×4群桩试验,对不同沉管隧道荷载作用下的土压力、桩身轴力及沉管隧道沉降进行测定。由于采用均匀设计,运用数理统计理论工具对试验数据进行相关性分析和回归分析,从而区别于传统的单因素优选法,使得同时考察多因素、多水平作用下对沉管隧道沉降的综合影响成为可能。分析结果表明,桩长、桩距、桩帽对沉管隧道沉降的影响随着外荷载的增加而改变;垫层厚度和桩帽存在交互作用,两者共同对沉管沉降产生影响。最后,利用拟合结果进行反演分析,在总样本为432种减沉桩组合中找出符合沉降控制要求的最优化组合。反演结果在后续模型试验中得到较好的验证。     

Determination of site-specific soil-water characteristic curve from a limited number of test data— A Bayesian perspective

Determining soilewater characteristic curve(SWCC) at a site is an essential step for implementing unsaturated soil mechanics in geotechnical engineering practice, which can be measured directly through various in-situ and/or laboratory tests. Such direct measurements are, however, costly and timeconsuming due to high standards for equipment and procedural control and limits in testing apparatus. As a result, only a limited number of data points(e.g., volumetric water content vs. matric suction)on SWCC at some values of matric suction are obtained in practice. How to use a limited number of data points to estimate the site-specific SWCC and to quantify the uncertainty(or degrees-of-belief) in the estimated SWCC remains a challenging task. This paper proposes a Bayesian approach to determine a site-specific SWCC based on a limited number of test data and prior knowledge(e.g., engineering experience and judgment). The proposed Bayesian approach quantifies the degrees-of-belief on the estimated SWCC according to site-specific test data and prior knowledge, and simultaneously selects a suitable SWCC model from a number of candidates based on the probability logic. To address computational issues involved in Bayesian analyses, Markov Chain Monte Carlo Simulation(MCMCS), specifically Metropolis-Hastings(M-H) algorithm, is used to solve the posterior distribution of SWCC model parameters, and Gaussian copula is applied to evaluating model evidence based on MCMCS samples for selecting the most probable SWCC model from a pool of candidates. This removes one key limitation of the M-H algorithm, making it feasible in Bayesian model selection problems. The proposed approach is illustrated using real data in Unsaturated Soil Database(UNSODA) developed by U.S. Department of Agriculture. It is shown that the proposed approach properly estimates the SWCC based on a limited number of site-specific test data and prior knowledge, and reflects the degrees-of-belief on the estimated SWCC in a rational and quantitative manner.     

Probabilistic analysis of load-settlement response from pile load tests

The evaluation of variability in ultimate pile capacity from the load-settlement data is useful in the context of code calibration and reliability based design in pile foundations. This paper examines the applicability of two non-linear analytical methods to calculate the load-settlement response of piles using actual test data in terms of percentage deviation from the measured capacity. The degree of agreement associated with each method with respect to field test data is quantified using two different failure criteria (FHWA and Eurocode) for determination of the ultimate load of pile. The analytical methods are used to quantify the variability associated with the soil-pile interface parameters and ultimate capacity using Monte Carlo simulations, which is useful in load-resistance factored/reliability design of pile foundations. Study reveals that variability depends on the method of analysis, percent deviation of prediction from measured values and failure criteria.     

Statistical analysis of the effective stress method and modifications for prediction of ultimate bond strength of soil nails

Uncertainty in the predicted ultimate pullout strength of soil nails can be significant due to the complexity of nail–soil interactions, inherent variability in soil properties and the effects of nail installation. The paper first presents a statistical evaluation of the accuracy of ultimate bond strength of soil nails using the effective stress method (ESM) equation that has been adopted in Hong Kong. A total of 113 ultimate nail capacity data points from field pullout tests were collected from the literature and used to estimate the accuracy of the current ESM. Based on the available data, the current ESM default pullout model is found to be excessively conservative (on average) by at least a factor of three. The spread in prediction accuracy measured by the coefficient of variation (COV) of bias is in the range of 36–43 % after removing anomalous test data. Here, bias is the ratio of measured to predicted pullout load capacity. In addition, the accuracy of the current ESM equation for prediction of nail bond strength is shown to be dependent on the magnitude of predicted ultimate bond strength and magnitude of nominal vertical effective stress which is undesirable. The paper examines four candidate-modified bond strength equations with empirical coefficients that have been back-fitted to measured bond strengths to improve the overall accuracy of the equation and to reduce or remove the undesirable dependencies noted above. One equation with an empirically corrected stress-dependent term is judged to be the best candidate model based on the mean of bias values, spread (COV) of bias values, lack of dependencies and simplicity. Finally, the relative contributions of random variability in soil shear strength to measurement bias in bond strength (prediction accuracy) for each soil type are computed for the best bond strength model. Analysis of the contribution of soil shear strength to prediction accuracy showed that the combination of variability due to factors other than soil shear strength was greater than the variability in soil shear strength alone, where the latter is defined by the soil secant friction coefficient.     

Comparison of the load response of closed-ended and open-ended pipe piles driven in gravelly sand

Slow-maintained static load tests were performed on closed-ended and open-ended steel pipe piles driven side by side in a gravelly sand soil profile. The site investigation consisted of multiple cone penetration tests (CPTs) and standard penetration tests (SPTs), as well as laboratory tests on soil samples collected at various depths from the test site to determine basic soil properties. The test piles were densely instrumented with a combination of electrical-resistance and vibrating-wire strain gauges. The open-ended test pile was a specially fabricated double-wall, fully-instrumented pile, allowing for separation of the measurements of the inner and outer shaft resistances. Detailed comparison of the load test results, in terms of driving resistance, load response and profiles of unit shaft and base resistances for the two test piles, is presented and discussed. The applicability of three CPT-based pile design methods is assessed through a layer-by-layer comparison of the estimated resistances with those measured in the static load tests.

     

MCS-based probabilistic design of embedded sheet pile walls

A probabilistic approach to the design of embedded sheet pile walls is developed in this paper. The approach is based on Monte Carlo simulation (MCS), and it is used to investigate the performance of the partial factors and different design approaches in Eurocode 7 in achieving the target degrees of reliability. The approach is illustrated through an embedded sheet pile wall design example that has been used in literature for the evaluation of Eurocode 7. The approach deals rationally with the correlated load and resistance, and it bypasses a difficult but frequently asked question in Eurocode 7 (i.e. should the passive earth pressure be considered as a load (i.e. action) or a resistance?). The probabilistic design approach (DA) is also used to explore the effects of the soil unit weight variability and uncertainties in over-digging depth and wall friction. The effects of uncertainties in over-digging depth and wall friction are found to be significant. It is also found that, although the soil unit weight variability is generally minor, its effect on the design of embedded sheet pile walls is significant and should be properly accounted for in the design. The MCS-based probabilistic DA proposed in this study provides a straightforward way for proper consideration of such variability with relative ease.     

Correlation of Pile Axial Capacity and CPT Data Using Gene Expression Programming

Numerous methods have been proposed to assess the axial capacity of pile foundations. Most of the methods have limitations and therefore cannot provide consistent and accurate evaluation of pile capacity. However, in many situations, the methods that correlate cone penetration test (CPT) data and pile capacity have shown to provide better results, because the CPT results provide more reliable soil properties. In an attempt to obtain more accurate correlation of CPT data with axial pile capacity, gene expression programming (GEP) technique is used in this study. The GEP is a relatively new artificial intelligent computational technique that has been recently used with success in the field of engineering. Three GEP models have been developed, one for bored piles and two other models for driven piles (a model for each of concrete and steel piles). The data used for developing the GEP models are collected from the literature and comprise a total of 50 bored pile load tests and 58 driven pile load tests (28 concrete pile load tests and 30 steel pile load tests) as well as CPT data. For each GEP model, the data are divided into a training set for model calibration and an independent validation set for model verification. The performances of the GEP models are evaluated by comparing their results with experimental data and the robustness of each model is investigated via sensitivity analyses. The performances of the GEP models are evaluated further by comparing their results with the results of number of currently used CPT-based methods. Statistical analyses are used for the comparison. The results indicate that the GEP models are robust and perform well.     

扩底桩承载力空间屈服包络面的基本特性

通过扩底桩的土槽载荷试验和离心机仿真模型试验,对不同类型荷载之间的相互影响、组合荷载作用下桩的抵抗机理和承载力屈服包络面的特性进行了分析。结果表明：铅直、水平荷载作用下桩的承载力屈服包络线,弯矩、水平荷载作用下的承载力屈服包络线都可近似地用椭圆来表现。屈服包络线可用桩的单方向极限承载力的经验公式来生成。根据承载力空间屈服面的连续性,提出了用桩的单方向极限承载力Vm,Hm,Um和Mm求解桩的承载力空间屈服面的经验公式。在桩的设计计算过程中,必须考虑铅直荷载、水平荷载及弯矩荷载间的相互影响。     

Calibration of resistance factor for design of pile foundations considering feasibility robustness

The resistance factor for pile foundations in load and resistance factor design (LRFD) is traditionally calibrated considering target reliability index (β_T) and statistics of load and resistance bias factors. However, the resistance bias factor is hard to quantify statistically. Consequently, the design obtained using the calibrated resistance factor can still miss β_T if the variation in resistance bias factor has been underestimated. In this paper, we propose a new resistance factor calibration approach to address this dilemma by considering “feasibility robustness” of design in the calibration process. Herein, the feasibility robustness is defined as a probability that the β_T requirement can still be satisfied even in the presence of uncertainty or variation in the computed bearing capacity. For illustration, LRFD approach for pile foundations commonly used in Shanghai, China is examined. Emphasis is placed on re-calibration of resistance factors at various feasibility robustness levels, with due consideration of the variation in the resistance bias factor. A case study is presented to illustrate the use of the re-calibrated resistance factors. The results show that the feasibility robustness is gained at the expense of cost efficiency; in other words, the two objectives are conflicting. To aid in the design decision-making, an optimal feasibility robustness level and corresponding resistance factors are suggested in the absence of a designer’s preference.     

刚-柔性桩复合地基中刚性桩和自由状态下刚性桩性能比较

刚-柔性桩复合地基中刚性桩的荷载传递规律及变形性状明显不同于自由状态下的单桩,由于复合地基中刚性桩、柔性桩、土的互相作用,桩的工作性状要复杂得多。为了比较两者的承载变形特性,在温州地区进行同根桩在不同状态下静荷载对比试验,在静荷载试验过程中同步检测桩身应力情况,结合测试数据对桩沉降特性、荷载传递机理、压缩量特性进行了分析,分析结果对工程设计施工有一定的借鉴价值。     

斜坡基桩水平极限承载力及影响因素模型试验和数值模拟

斜坡上的基桩具有承重和阻滑的双重功能,其受力变形性状远比平地上的情形复杂。采用模型试验和数值模拟相结合的方法研究了其水平承载特性及影响因素。模型试验结果表明：临坡距对基桩的水平承载变形性能有较大影响。同一级荷载下,临坡距较大的桩身水平位移小于临坡距较小的基桩;临坡距较大基桩的临界荷载和极限承载力也大于临坡距小的基桩。数值模拟研究结果表明：基桩水平极限承载力随着斜坡坡比的增大而减小,随着临坡距的增大而增大,与模型试验的结果基本一致。对比分析了斜坡和平地基桩水平承载变形性能的差别,得出了可考虑坡比和临坡距的斜坡基桩水平极限承载力简便计算方法,可为有关规范的修订以及工程设计提供参考。     

群桩基础竖向承载力的可靠性分析

由CPT和静载试验结果综合确定钻孔灌注桩竖向极限承载力,以沿深度方向的一维平稳高斯随机场作为桩基土层土性参数的数学模型,利用相关函数法和变异函数法计算土层的相关范围,进而对相同场地各试桩的承载力进行折算后检验其概率分布,并估计有关统计参数;考虑群桩效应,由桩基沉降反算其作用效应,计算单桩及群桩的可靠度指标。并与未采用随机场模型的计算结果相比较,对竖向荷载下桩基可靠性进行了较系统的研究。     

水平荷载作用下PCC桩复合地基工作性状

利用河海大学岩土所自行研制开发的大型试验模型槽进行PCC桩水平承载足尺试验,实测得到了水平荷载作用下桩身弯矩分布。利用三维弹塑性有限元方法,研究了PCC单桩与等截面实心圆桩、PCC桩复合地基与等截面实心圆桩复合地基在水平荷载作用下的工作性状,对其桩身弯矩和水平位移的分布规律进行了比较,分析了竖向荷载、褥垫层厚度、基础埋深和置换率对PCC桩复合地基桩身性状的影响。研究表明,PCC桩复合地基在水平荷载作用下,随着竖向荷载、褥垫层厚度、基础埋深和置换率的增加,其桩身弯矩和水平位移随之减小。因此,在PCC桩复合地基设计时可以通过适度调整这些影响参数来减小水平荷载作用下的桩身弯矩和水平位移,确保桩身的安全。     

大直径深长桩泥岩侧摩阻力试验研究——以吉林省龙华松花江特大桥工程试桩为例

泥岩地基中泥岩的桩侧摩阻力设计参数比较缺乏。通过对吉林省龙华松花江特大桥工程试桩的自平衡静载试验分析,并结合室内桩和泥岩接触中型剪切摩擦试验,揭示了该地区泥岩地基中大直径深长灌注桩泥岩侧摩阻力作用机制及承载特征,得出了一些对泥岩地基中钻孔灌注桩的设计和深入研究具有指导意义的结论。结果表明：大直径深长桩桩端阻力分担的荷载只占总承载力的一小部分,属摩擦型桩。自平衡测试中,全风化泥岩侧摩阻力达到173 kPa,强风化泥岩侧摩阻力达到279 kPa,中等风化泥岩侧摩阻力达到336 kPa,实测值较规范参考值大很多。建议在桩基设计时通过室内桩和泥岩接触中型剪切摩擦试验,基于莫尔库伦理论预估泥岩侧摩阻力,为桩基承载力的确定提供参考。     

A simplified design method for energy piles

This paper introduces a simplified method to investigate the influence of thermal loads on the shaft friction and tip resistance of energy piles. The method is based on the influence factors (λ and η) which are back-calculated drawing on a large number of field and model tests. Values for λ and η during heating and cooling are suggested. Moreover, a new equation is proposed to calculate total shaft friction. The equations concerning the relationship between η and temperature difference are recommended to investigate the impacts of the thermal load on the pile tip resistance. The slope of the linear equation of an end-bearing pile is 2.14 times that of a floating pile indicating that the pile tip resistance of an end-bearing pile is much more affected by the same thermal load.