A New Computer Program for Pile Capacity Prediction using CPT Data

An interactive computer program “GLAMCPT” is developed for application in soil profiling and prediction of pile load capacity using cone penetration test (CPT) and laboratory soil test results. GLAMCPT calculates pile capacity according to 10 selected methods from European design codes, refereed international publications and recommendations of professional institutions. To demonstrate the capabilities of the program, a database of comprehensive ground investigation and full-scale pile tests in sand, at a Belgian site, is analysed using GLAMCPT. The database comprises 11 static tests and 12 dynamic tests on piles of different construction techniques, including driven pre-cast concrete piles and screwed cast in-situ piles, installed using 5 different procedures. Prior to pile installation, CPTs were carried out at each proposed pile location. Comparison of GLAMCPT predictions with the observed pile capacities reveals that the most accurate of the existing methods yields an average, μ, of predicted to observed pile head capacity [P_uh(p)/P_uh(m)] equal to 0.94. The most consistent method produces a coeffcient of variation (COV) of [P_uh(p)/P_uh(m)] equal to 0.1 and ranking index (RI) of 0.08. Parametric studies have been carried out using GLAMCPT to formulate an improved predictive method, which yielded: μ = 0.99, COV = 0.07 and RI = 0.04.     

Piles shaft capacity from CPT and CPTu data by polynomial neural networks and genetic algorithms

Cone penetration test (CPT) is one of the most common in situ tests which is used for pile design because it can be realized as a model pile. The measured cone resistance (q_c) and sleeve friction (f_s) usually are employed for estimation of pile unit toe and shaft resistances, respectively. Thirty three pile case histories have been compiled including static loading tests performed in uplift, or in push with separation of shaft and toe resistances at sites which comprise CPT or CPTu sounding. Group method of data handling (GMDH) type neural networks optimized using genetic algorithms (GAs) are used to model the effects of effective cone point resistance (q_E) and cone sleeve friction (f_s) as input parameters on pile unit shaft resistance, applying some experimentally obtained training and test data. Sensitivity analysis of the obtained model has been carried out to study the influence of input parameters on model output. Some graphs have been derived from sensitivity analysis to estimate pile unit shaft resistance based on q_E and f_s. The performance of the proposed method has been compared with the other CPT and CPTu direct methods and referenced to measured piles shaft capacity. The results demonstrate that appreciable improvement in prediction of pile shaft capacity has been achieved.     

Assessment of direct CPT and CPTU methods for predicting the ultimate bearing capacity of single piles

Twelve methods to determine axial pile capacity directly based on cone penetration test (CPT) and piezocone penetration test (CPTU) data are presented, compared and evaluated. Analyses and evaluation were conducted on three types of piles of different size and length. All the tested piles have failed at the end of static load test. Both the CPT methods and the CPTU methods were used to estimate the load bearing capacities of the investigated piles (Q_p). The static load test was performed to determine the measured load bearing capacities (Q_m). The pile capacities determined through different methods were compared with the measured values obtained from the static load tests. Two criteria were selected as bases of evaluation: the best fit line for Q_p versus Q_m and the arithmetic mean and standard deviation for the ratio Q_p/Q_m. Results of the analyses showed that the best methods for determining pile capacity are the two CPTU methods. Furthermore, the CPTU method is simple, easy to apply, and not influenced by the subjective judgements of operating staff. Therefore, it is quite suitable for the application in pile engineering practice.     

Prediction of ultimate axial load-carrying capacity of piles using a support vector machine based on CPT data

The support vector machine (SVM) is a relatively new artificial intelligence technique which is increasingly being applied to geotechnical problems and is yielding encouraging results. In this paper SVM models are developed for predicting the ultimate axial load-carrying capacity of piles based on cone penetration test (CPT) data. A data set of 108 samples is used to develop the SVM models. These data were obtained from the literature containing pile load tests and each sample contains information regarding pile geometry, full-scale static pile load tests and CPT results. Moreover, a sensitivity analysis is carried out to examine the relative significance of each input variable with respect to ultimate strength prediction. Finally, a statistical analysis is conducted to make comparisons between predictions obtained from the SVM models and three traditional CPT-based methods for determining pile capacity. The comparison confirms that the SVM models developed in this paper outperform the traditional methods.     

Statistical Evaluation of CPT and CPTu Based Methods for Prediction of Axial Bearing Capacity of Piles

Piles are structural members made of steel, concrete, or wood installed into the ground to transfer superstructure loads to the soil. Nowadays, many structures are built on poor lands, and therefore piles have crucial roles in such structures. Performing in-situ tests such as cone penetration (CPT) and piezocone penetration tests (CPTu) have always been of great importance in designing piles. These tests have a brilliant consistency with reality, and as a result, the outcome data can be used in order to achieve reliable pile designing models and reduce uncertainty in this regard. In this paper, the capability of various CPT and CPTu based methods developed from 1961 to 2016 has been investigated using four statistical methods. Such CPT and CPTu based methods are adopted for direct prediction of axial bearing capacity of piles using CPT and CPTu field data. For this purpose, 61 sets of field data prepared from CPT and CPTu have been collected. The data sets were utilized in order to calculate the axial bearing capacity of piles (Q_E) through 25 different methods. In addition, the measured axial pile capacities (Q_M) have been collected, recorded and prepared from field static load tests, respectively. Then, four different statistical approaches have been applied to assess the accuracy of these methods. Finally, the most reliable and accurate methods are presented.

     

Cone Penetration Test Based Direct Methods for Evaluating Static Axial Capacity of Single Piles

The direct cone penetration test (CPT) based pile design methods use the measured penetrometer readings by scaling relationships or algorithms in a single-step process to enable the assessment of pile capacity components of shaft and base resistance (f _p and q _b, respectively) for evaluation of full-size pilings. This paper presents a state-of-the-art review of published works that focus on direct CPT evaluation of static axial pile capacity. The review is presented in a chronological order to explicate the evolution over the past six decades of an in situ test based solution for this soil-structure interaction problem. The objective of this study is an attempt to assemble maximum published methods proposed as a result of past investigations in one resource to afford researchers and practitioners with convenient access to the respective design equations and charts. In addition to an all-inclusive summary table and the design charts, a compilation of significant findings and discussions thereof are presented. Furthermore, potential future research directions are indicated, with special emphasis on the optimal use of the modern multi-channel hybrid geophysical-geotechnical seismic CPT to evaluate the complete axial pile load–displacement response.     

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。     

考虑土参数自相关距离影响的单桩可靠性设计方法

在岩土工程设计中,准确地衡量土层参数的空间变异性决定了设计结构的可靠性和经济性,土参数的自相关距离是反映其空间变异性的一个重要指标。目前对于自相关距离与结构可靠性之间的关系的研究还很不完善。本文以单桩可靠性设计为例,选取工程场地的静力触探试验数据,引入随机场理论描述侧摩阻力和锥尖阻力的分布特征,利用递推平均法计算各地基土层侧摩阻力和锥尖阻力的自相关距离,在描述土层侧摩阻力和锥尖阻力的分布特征时考虑了自相关距离的影响,进一步结合蒙特卡洛法计算单桩的可靠指标。结果表明土参数取值考虑自相关距离的影响后,降低了土参数分布的离散程度,计算的单桩可靠指标更高。在保证桩基安全度的前提下,设计结果能够降低工程成本。     

静压预应力混凝土管桩土塞效应试验研究

对淤泥质黏土互层以及粉土两种土层条件下静压预应力混凝土管桩的土塞效应进行了试验研究。现场及室内试验结果显示,管桩径厚比越大、土层条件越为坚硬则形成的土塞相对高度越大。上硬下软的土层分布易形成闭塞现象,而上软下硬的情况则易导致土塞的滑动。沉桩过程中,管壁端阻与静力触探锥尖阻力具有极为相似的变化规律,两者比值不随土塞高度变化率及沉桩深度的变化而改变。管壁端阻与锥尖阻力的相关性与土层条件密切相关,对于淤泥质黏土和粉土而言,两者比值分别为0.59和0.81。土塞的分层与地基土层分布基本一致,且分层界面为向上凸起的曲面。土塞形成过程中挤密效应是显著的,黏聚力则因扰动的影响有不同程度的降低。直剪试验显示,土塞抗剪强度的时效性是显著的。粉土中预应力混凝土管桩有效土塞高度约为5～6倍桩径,为整个土塞高度的70%;而淤泥质黏土中有效土塞高度大于4倍桩径。试验结果与已有的研究结果较为接近     

单桩极限承载力的静力触探估算法研究

结合上海现行规范,在利用高应变动力测试获得单桩极限侧摩阻力和极限端阻力的基础上,提出静力触探估算单桩极限承载力的修正公式,并对其中的修正系数进行分析,从而获得了修正系数的统计结果。为减少高应变动力测试可能带来的误差,利用静载荷结果对所得的修正公式进行再次修正,并最终获得由静力触探估算单桩极限承载力的公式。工程实例验证表明,用所得公式计算单桩极限承载力的结果精度更高,从而为研究静力触探确定单桩极限承载力提供了一种新的途径。     

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.     

砂土中单桩静载室内模型试验及颗粒流数值模拟

通过自行设计的可视化模型箱,进行了单桩静载室内模型试验,考虑了不同桩径、不同土体密实度等影响因素,研究了单桩的沉降模式、桩侧摩阻力和桩端阻力的发挥性状及随沉降的发展模式,并通过拍摄跟踪和图像处理技术,研究了桩端和桩周土体的孔隙率的变化规律;对二维颗粒流程序进行开发,模拟了单桩静载过程中桩端阻力和桩周土体孔隙率的变化情况。结果表明,颗粒流数值模拟能够较好地模拟单桩静载过程,研究成果进一步揭示了单桩静载过程的宏细观机制。     

Load-settlement behavior modeling of single piles using artificial neural networks and CPT data

Pile foundations are usually used when the conditions of the upper soil layers are weak and unable to support the super-structural loads. Piles carry these super-structural loads deep into the ground. Therefore, the safety and stability of pile-supported structures depends largely on the behavior of the piles. In addition, accurate prediction of pile behavior is necessary to ensure appropriate structural and serviceability performance. In this paper, an ANN model is developed for predicting pile behavior based on the results of cone penetration test (CPT) data. Approximately 500 data sets, obtained from the published literature, are used to develop the ANN model. The paper compares the predictions obtained by the ANN with those given by a number of traditional methods and it is observed that the ANN model significantly outperforms the traditional methods. An important advantage of the ANN model is that the complete load-settlement relationship is captured. Finally, the paper proposes a series of charts for predicting pile behavior that will be useful for pile design.     

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.

     

海洋静力触探在海上平台桩基承载力计算中的应用

静力触探探测具有原位性、连续性、高效性以及高分辨率的优点,利用海洋静力触探探测成果计算海上平台桩基承载力具有非常大的应用空间。以胜利油田埕岛海域某平台为例,使用ROSON100型海洋静力触探仪对平台各桩腿开展原位探测,同步进行钻探取样及室内土工参数测试。分别利用静力触探和钻探取样测试成果计算了平台桩基承载力,对比讨论了3种桩基承载力计算方法之间的异同。结果表明:3种方法对应的桩侧摩阻力随埋深变化整体趋势基本一致;基于一定区域工程经验,钻探规范法和静探间接法得到的桩端阻力、单桩极限承载力基本吻合,而静探直接法得到的桩端阻力和单桩极限承载力相较前两者明显偏大;考虑以粉砂作为持力层的前提下3种桩基极限承载力计算方法表现出较好的兼容性。研究成果可为海洋工程桩基承载力计算提供新的借鉴,具有一定科学意义和应用价值。     

静压沉桩与CPTU贯入离心模型试验及机制研究

为了探究静压沉桩与CPTU贯入力学机制,开展了饱和黏土中静压沉桩及CPTU贯入的离心模型试验,获得了静压沉桩与CPTU贯入过程中土压力、超孔压和贯入阻力的变化规律。同时,将静压桩和CPTU压入过程视为一系列球孔的连续贯入,应用圆孔扩张解答,建立了静压沉桩和CPTU贯入过程中锥头阻力、侧阻力与超孔压的预测方法。通过离心模型试验和理论预测结果的对比分析表明：随着桩体的压入,桩周土体的超孔压和土压力均逐渐增大,当桩头通过监测点时,超孔压与土压力均达到最大值;在饱和黏土中,CPTU锥头阻力、锥侧摩阻力和锥头超孔压与锥头贯入深度总体上呈线性关系。预测方法估算沉桩和CPTU贯入引起的土压力、超孔压与模型试验结果相符,较好地反映了饱和黏土中静压沉桩和CPTU贯入的力学机制。     

CPT-based probabilistic evaluation of seismic soil liquefaction potential using multi-gene genetic programming

In this paper, liquefaction potential of soil is evaluated within a probabilistic framework based on the post-liquefaction cone penetration test (CPT) data using an evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). Based on the developed limit state function using MGGP, a relationship is given between probability of liquefaction (P_L) and factor of safety against liquefaction using Bayesian theory. This Bayesian mapping function is further used to develop a P_L-based design chart for evaluation of liquefaction potential of soil. Using an independent database of 200 cases, the efficacy of the present MGGP-based probabilistic method is compared with that of the available probabilistic methods based on artificial neural network (ANN) and statistical methods. The proposed method is found to be more efficient in terms of rate of successful prediction of liquefaction and non-liquefaction cases, in three different ranges of P_L values compared to ANN and statistical methods.     

Growth-rate-dependent prediction of pile set-up and its application in driven pile foundation construction

In this paper research was presented on the development of a growth-rate-dependent model for pile set-up prediction using the restrike and static/statnamic load testing data collected from different projects. The data included: a) restrike records from ninety-five production piles and restrike and load test results of nine instrumented piles driven in soft clays from the relocation project of Highway No. 1 in Louisiana (LA-1); and b) restrike and static load testing data of five fully instrumented square PPC piles driven at four different bridge sites in various soil layers from sands to clays in Florida. Research effort was focused on the prediction of the ultimate shaft resistances with pile set-up formulated using the pile resistance growth rate-dependent model. The timeframe of interest was studied for a practical set-up magnitude such as 90% of the ultimate shaft resistance (Q₉₀). As an application of the rate-dependent model, it was found that piles at the LA-1 relocation project, in general, reached about 95% of the ultimate shaft resistances at the time of 2 weeks after pile installation. The strategy of incorporation of pile set-up in adjusting pile driving criteria or/and design during pile construction, such as the experience-based plan of a two-week waiting period adopted by Louisiana DOTD, was investigated and justified.     

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。     

大型石化地基振冲碎石桩处理现场试验研究

针对大型炼厂工程地基处理的复杂性,开展了振冲碎石桩的现场试验。利用静力触探试验检测桩体密实度和判别饱和砂土液化。基于旁压试验、标准贯入试验和重型动力触探试验结果,分析了施工前后地基承载力和土体工程特性变化情况。以单桩和复合地基载荷试验结果验证了桩间土、单桩及复合地基的承载性能。研究结果表明,振冲碎石桩对桩长范围的砂土具有明显的挤密效应,工程特性和场地的均匀性在处理后有了明显改善和提高,有效地消除了桩长范围内砂土的液化可能性。静载荷试验结果表明,振冲碎石桩复合地基承载力能达到设计要求;振冲碎石桩对砂土层下卧黏性土层的加固作用不明显,部分深度范围内土体强度降低;当地面以下10 m内不存在厚度大于5 m的软土夹层时,较薄的软土夹层状对挤密加固其余深度的砂土未产生明显影响,对地基承载力影响亦较小。