Simplified Cone Penetration Test-based Method for Evaluating Liquefaction Resistance of Soils

This paper presents a new simplified method for assessing the liquefaction resistance of soils based on the cone penetration test (CPT). A relatively large database consisting of CPT measurements and field liquefaction performance observations of historical earthquakes is analyzed. This database is first used to train an artificial neural network for predicting the occurrence and nonoccurrence of liquefaction based on soil and seismic load parameters. The successfully trained and tested neural network is then used to generate a set of artificial data points that collectively define the liquefaction boundary surface, the limit state function. An empirical equation is further obtained by regression analysis to approximate the unknown limit state function. The empirical equation developed represents a deterministic method for assessing liquefaction resistance using the CPT. Based on this newly developed deterministic method, probabilistic analyses of the cases in the database are conducted using the Bayesian mapping function approach. The results of the probabilistic analyses, expressed as a mapping function, provide a simple means for probability-based evaluation of the liquefaction potential. The newly developed simplified method compares favorably to a widely used existing method.     

Discriminant Model for Evaluating Soil Liquefaction Potential Using Cone Penetration Test Data

Statistical analysis using a discriminant model is applied to 399 cone penetration test (CPT) data sets of both liquefaction and nonliquefaction cases, including 174 sets from the Chi-Chi earthquake in Taiwan and 225 sets of synthesized data. The discriminant model employed is a multivariate statistical method. In situ testing results of cone tip resistance qc and sleeve friction ratio Rf are adopted as the major parameters for analyses. A model for evaluating liquefaction potential using CPT-qc data is also established in this study, which allows calculated results to be compared with the empirical curves.     

Assessing Probability-based Methods for Liquefaction Potential Evaluation

This paper presents an assessment of existing and new probabilistic methods for liquefaction potential evaluation. Emphasis is placed on comparison of probabilities of liquefaction calculated with two different approaches, logistic regression and Bayesian mapping. Logistic regression is a well-established statistical procedure, whereas Bayesian mapping is a relatively new application of the Bayes’ theorem to the evaluation of soil liquefaction. In the present study, simplified procedures for soil liquefaction evaluation, including the Seed–Idriss, Robertson–Wride, and Andrus–Stokoe methods, based on the standard penetration test, cone penetration test, and shear wave velocity measurement, respectively, are used as the basis for developing Bayesian mapping functions. The present study shows that the Bayesian mapping approach is preferred over the logistic regression approach for estimating the site-specific probability of liquefaction, although both methods yield comparable probabilities. The paper also compares the three simplified methods in the context of probability of liquefaction, and argues for the use of probability-based procedures for evaluating liquefaction potential.     

CPT-Based Probabilistic and Deterministic Assessment of In Situ Seismic Soil Liquefaction Potential

This paper presents a complete methodology for both probabilistic and deterministic assessment of seismic soil liquefaction triggering potential based on the cone penetration test (CPT). A comprehensive worldwide set of CPT-based liquefaction field case histories were compiled and back analyzed, and the data then used to develop probabilistic triggering correlations. Issues investigated in this study include improved normalization of CPT resistance measurements for the influence of effective overburden stress, and adjustment to CPT tip resistance for the potential influence of “thin” liquefiable layers. The effects of soil type and soil character (i.e., “fines” adjustment) for the new correlations are based on a combination of CPT tip and sleeve resistance. To quantify probability for performance-based engineering applications, Bayesian “regression” methods were used, and the uncertainties of all variables comprising both the seismic demand and the liquefaction resistance were estimated and included in the analysis. The resulting correlations were developed using a Bayesian framework and are presented in both probabilistic and deterministic formats. The results are compared to previous probabilistic and deterministic correlations.     

First-Order Reliability Method for Probabilistic Liquefaction Triggering Analysis Using CPT

The potential for liquefaction triggering of a soil under a given seismic loading is measured herein by probability of liquefaction. The first order reliability method (FORM) is used to calculate reliability index, from which the probability of liquefaction is obtained. This approach requires the knowledge of parameter and model uncertainties; the latter is the focus of this paper. An empirical model for determining liquefaction resistance based on cone penetration test (CPT) is established through “neural network learning” of case histories. This resistance model along with a reference seismic loading model forms a performance function or limit state for liquefaction triggering analysis. Within the framework of the FORM, the uncertainty of this limit state model is characterized through an extensive series of sensitivity studies using Bayesian mapping functions that have been calibrated with a set of quality case histories. In addition, a deterministic model for assessing liquefaction potential in terms of factor of safety is presented, and the probability-safety factor mapping functions for estimating the probability of liquefaction for a given factor of safety in the absence of the knowledge of parameter uncertainty are also established. Examples are presented to illustrate the proposed methods.     

CPT-Based Evaluation of Liquefaction and Lateral Spreading in Centrifuge

Two series of centrifuge model tests were conducted using Nevada sand. Four saturated models placed in a mildly inclined laminar box and simulating a 6-m-thick deposit were shaken inducing liquefaction effects and lateral spreading. The sand was deposited at a relative density, Dr = 45 or 75%; two of the 45% models were subjected to overconsolidation or preshaking. The second series involved in-flight measurements of static cone tip penetration resistance, qc, simulating the standard cone penetration test (CPT) 36-mm cone. Values of qc increased with Dr, overconsolidation, and preshaking. A normalized resistance, qc1N, was assigned to each of the four liquefaction/lateral spreading models. Increases in Dr, overconsolidation, and preshaking decreased liquefaction and ground deformation, but relative density alone captured these effects rather poorly. Conversely, qc1N predicted extremely well the liquefaction and lateral spreading response of the four models, confirming Seed’s hypothesis to explain the success of penetration-based seismic liquefaction charts. The depth to liquefaction measured in the four centrifuge models is consistent with the field CPT liquefaction chart.     

Validation and Application of Empirical Liquefaction Models

Empirical liquefaction models (ELMs) are the standard approach for predicting the occurrence of soil liquefaction. These models are typically based on in situ index tests, such as the standard penetration test (SPT) and cone penetration test (CPT), and are broadly classified as deterministic and probabilistic models. No objective and quantitative comparison of these models have been published. Similarly, no rigorous procedure has been published for choosing the threshold required for probabilistic models. This paper provides (1) a quantitative comparison of the predictive performance of ELMs; (2) a reproducible method for choosing the threshold that is needed to apply the probabilistic ELMs; and (3) an alternative deterministic and probabilistic ELM based on the machine learning algorithm, known as support vector machine (SVM). Deterministic and probabilistic ELMs have been developed for SPT and CPT data. For deterministic ELMs, we compare the “simplified procedure,” the Bayesian updating method, and the SVM models for both SPT and CPT data. For probabilistic ELMs, we compare the Bayesian updating method with the SVM models. We compare these different approaches within a quantitative validation framework. This framework includes validation metrics developed within the statistics and artificial intelligence fields that are not common in the geotechnical literature. We incorporate estimated costs associated with risk as well as with risk mitigation. We conclude that (1) the best performing ELM depends on the associated costs; (2) the unique costs associated with an individual project directly determine the optimal threshold for the probabilistic ELMs; and (3) the more recent ELMs only marginally improve prediction accuracy; thus, efforts should focus on improving data collection.     

Mapping Liquefaction Potential Considering Spatial Correlations of CPT Measurements

The past studies of liquefaction phenomena during earthquakes have contributed to the development of simplified methods employing field test data to assess the liquefaction potential. Since the field data are limited by exploration cost, it is of interest to obtain valuable and meaningful distribution of liquefaction potential of an area from the limited data. This study proposes a method for assessing liquefaction potential over an extensive area according to the random field concept. The spatial structures of soil properties are estimated from the available cone penetration test (CPT) measurements. The soil properties at unsampled locations are simulated using Monte Carlo simulation. The reliability against liquefaction at every location within the study area is evaluated to map the liquefaction potential. The comparison between simulated distributions of liquefaction potential and observed liquefaction phenomena is discussed. The spatial correlation of soil property provides more information than the traditional approach that solely uses the field test data. The influences of CPT data, penetration locations, and spatial structures of soil properties on the mapping results of liquefaction potential are also discussed.     

Retesting of Liquefaction and Nonliquefaction Case Histories from the 1976 Tangshan Earthquake

A field investigation was performed to retest liquefaction and nonliquefaction sites from the 1976 Tangshan earthquake in China. These sites were carefully investigated in 1978 and 1979 by using standard penetration test (SPT) and cone penetration test (CPT) equipment; however, the CPT measurements are obsolete because of the now nonstandard cone that was used at the time. In 2007, a modern cone was mobilized to retest 18 selected sites that are particularly important because of the intense ground shaking they sustained despite their high fines content and/or because the site did not liquefy. Of the sites reinvestigated and carefully reprocessed, 13 were considered accurate representative case histories. Two of the sites that were originally investigated for liquefaction have been reinvestigated for cyclic failure of fine-grained soil and removed from consideration for liquefaction triggering. The most important outcome of these field investigations was the collection of more accurate data for three nonliquefaction sites that experienced intense ground shaking. Data for these three case histories is now included in an area of the liquefaction triggering database that was poorly populated and will help constrain the upper bound of future liquefaction triggering curves.     

Estimation of Footing Settlement in Sand

The settlement of foundations under working load conditions is an important design consideration. Well‐designed foundations induce stress‐strain states in the soil that are neither in the linear elastic range nor in the range usually associated with perfect plasticity. Thus, in order to accurately predict working settlements, analyses that are more realistic than simple elastic analyses are required. The settlements of footings in sand are often estimated based on the results of in situ tests, particularly the standard penetration test (SPT) and the cone penetration test (CPT). In this article, we analyze the load‐settlement response of vertically loaded footings placed in sands using both the finite element method with a nonlinear stress‐strain model and the conventional elastic approach. Calculations are made for both normally consolidated and heavily overconsolidated sands with various relative densities. For each case, the cone penetration resistance qc is calculated using CONPOINT, a widely tested program that allows computation of qc based on cavity expansion analysis. Based on these analyses, we propose a procedure for the estimation of footing settlement in sands based on CPT results.     

Liquefaction Resistance of Clean and Nonplastic Silty Sands Based on Cone Penetration Resistance

Liquefaction of granular soil deposits is one of the major causes of loss resulting from earthquakes. The accuracy in the assessment of the likelihood of liquefaction at a site affects the safety and economy of the design. In this paper, curves of cyclic resistance ratio (CRR) versus cone penetration test (CPT) stress-normalized cone resistance qc1 are developed from a combination of analysis and laboratory testing. The approach consists of two steps: (1) determination of the CRR as a function of relative density from cyclic triaxial tests performed on samples isotropically consolidated to 100 kPa; and (2) estimation of the stress-normalized cone resistance qc1 for the relative densities at which the soil liquefaction tests were performed. A well-tested penetration resistance analysis based on cavity expansion analysis was used to calculate qc1 for the various soil densities. A set of 64 cyclic triaxial tests were performed on specimens of Ottawa sand with nonplastic silt content in the range of 0–15% by weight, and relative densities from loose to dense for each gradation, to establish the relationship of the CRR to the soil state and fines content. The resulting (CRR)7.5-qc1 relationship for clean sand is consistent with widely accepted empirical relationships. The (CRR)7.5-qc1 relationships for the silty sands depend on the relative effect of silt content on the CRR and qc1. It is shown that the cone resistance increases at a higher rate with increasing silt content than does liquefaction resistance, shifting the (CRR)7.5-qc1 curves to the right. The (CRR)7.5-qc1 curves proposed for both clean and silty sands are consistent with field observations.     

Prediction of Soil Composition from CPT Data Using General Regression Neural Network

Soil type is typically inferred from the information collected during a cone penetration test (CPT) using one of the many available soil classification methods. In this study, a general regression neural network (GRNN) was developed for predicting soil composition from CPT data. Measured values of cone resistance and sleeve friction obtained from CPT soundings, together with grain-size distribution results of soil samples retrieved from adjacent standard penetration test boreholes, were used to train and test the network. The trained GRNN model was tested by presenting it with new, previously unseen CPT data, and the model predictions were compared with the reference particle-size distribution and the results of two existing CPT soil classification methods. The profiles of soil composition estimated by the GRNN generally compare very well with the actual grain-size distribution profiles, and overall the neural network had an 86% success rate at classifying soils as coarse grained or fine grained.     

Estimating Liquefaction-Induced Lateral Displacements Using the Standard Penetration Test or Cone Penetration Test

A semiempirical approach to estimate liquefaction-induced lateral displacements using standard penetration test (SPT) or cone penetration test (CPT) data is presented. The approach combines available SPT- and CPT-based methods to evaluate liquefaction potential with laboratory test results for clean sands to estimate the potential maximum cyclic shear strains for saturated sandy soils under seismic loading. A lateral displacement index is then introduced, which is obtained by integrating the maximum cyclic shear strains with depth. Empirical correlations from case history data are proposed between actual lateral displacement, the lateral displacement index, and geometric parameters characterizing ground geometry for gently sloping ground without a free face, level ground with a free face, and gently sloping ground with a free face. The proposed approach can be applied to obtain preliminary estimates of the magnitude of lateral displacements associated with a liquefaction-induced lateral spread.     

Accounting for Soil Aging When Assessing Liquefaction Potential

It has been recognized that liquefaction resistance of sand increases with age due to processes such as cementation at particle contacts and increasing frictional resistance resulting from particle rearrangement and interlocking. As such, the currently available empirical correlations derived from liquefaction of young Holocene sand deposits, and used to determine liquefaction resistance of sand deposits from in situ soil indices [standard penetration test (SPT), cone penetration test (CPT), shear wave velocity test (Vs)], are not applicable for old sand deposits. To overcome this limitation, a methodology was developed to account for the effect of aging on the liquefaction resistance of old sand deposits. The methodology is based upon the currently existing empirical boundary curves for Holocene age soils and utilizes correction factors presented in the literature that comprise the effect of aging on the in situ soil indices as well as on the field cyclic strength (CRR). This paper describes how to combine currently recorded SPT, CPT, and Vs values with corresponding CRR values derived for aged soil deposits to generate new empirical boundary curves for aged soils. The method is illustrated using existing geotechnical data from four sites in the South Carolina Coastal Plain (SCCP) where sand boils associated with prehistoric earthquakes have been found. These sites involve sand deposits that are 200,000?to?450,000?years in age. This work shows that accounting for aging of soils in the SCCP yields less conservative results regarding the current liquefaction potential than when age is not considered. The modified boundary curves indicate that old sand deposits are more resistant to liquefaction than indicated by the existing empirical curves and can be used to evaluate the liquefaction potential at a specific site directly from the current in situ properties of the soil.     

Normalizing the CPT for Overburden Stress

Effective overburden stress can have a significant influence on cone penetration test (CPT) measurements. This influence can lead to an incorrect assessment of soil strength/resistance for such purposes as liquefaction triggering analysis. For an accurate measurement of tip and sleeve resistance, unbiased by overburden stress, it is essential to normalize these index measurements appropriately. Presented herein is a comprehensive study reviewing all aspects of CPT normalization. A result of this study is a variable normalization procedure for the CPT that is based on both empirical results and theoretical analysis. This paper presents these results in the form of an improved normalization scheme and discusses its application in practice.     

Probabilistic Framework for Liquefaction Potential by Shear Wave Velocity

This paper presents a new empirical equation for assessing liquefaction resistance of soils based on shear wave velocity Vs and the results of probabilistic analyses based on this empirical equation. A database consisting of in situ shear wave velocity measurements and field observations of liquefaction∕nonliquefaction in historic earthquakes is analyzed. This database is first used to train and test an artificial neural network to predict the occurrence of liquefaction∕nonliquefaction based on soil and seismic load parameters. The successfully trained and tested neural network is then used to establish the empirical equation. The concept of clean soil equivalence is introduced and used in the development of the empirical equation. The established empirical equation represents a deterministic method for assessing liquefaction resistance of a soil. Based on this newly developed deterministic method, probabilistic analyses of the cases in the database are conducted using the logistic regression approach and the mapping function approach. The results provide a basis for risk-based evaluation of liquefaction evaluation.     

Probabilistic Assessment of Stress Normalization for CPT Data

Currently available cone penetration test (CPT) stress normalization schemes exhibit no consensus on the estimation of the stress normalization component. Depending on which power law stress normalization exponent is used, very different interpretations may result in the analyses where normalized CPT data are used (e.g., CPT-based soil classification and seismic soil liquefaction initiation assessment). Within the confines of this paper, it is intended to clarify and resolve some of these differences, and to propose improved recommendations for CPT stress normalization. For this purpose, available stress normalization databases from theoretical, numerical, and field data analyses approaches were compiled. For the soil types, and stress conditions where compiled database is not conclusive, additional finite element simulations have been performed. The resulting relationship not only eliminates several sources of bias intrinsic to previous, similar correlations, and provides greatly reduced overall uncertainty and variance, it also helps to establish a consensus to the stress normalization issue that have long been difficult and controversial. Key elements in the development of these new correlations are: (1) accumulation of a significantly expanded database of analytical/numerical CPT simulation results, as well as field and chamber test data from homogeneous soil layers; (2) use of improved knowledge and understanding of factors affecting CPT and stress normalization; and (3) use of high-order probabilistic tools (Bayesian updating).     

Subsurface Characterization at Ground Failure Sites in Adapazari, Turkey

Ground failure in Adapazari, Turkey during the 1999 Kocaeli earthquake was severe. Hundreds of structures settled, slid, tilted, and collapsed due in part to liquefaction and ground softening. Ground failure was more severe adjacent to and under buildings. The soils that led to severe building damage were generally low plasticity silts. In this paper, the results of a comprehensive investigation of the soils of Adapazari, which included cone penetration test (CPT) profiles followed by borings with standard penetration tests (SPTs) and soil index tests, are presented. The effects of subsurface conditions on the occurrence of ground failure and its resulting effect on building performance are explored through representative case histories. CPT- and SPT-based liquefaction triggering procedures adequately identified soils that liquefied if the clay-size criterion of the Chinese criteria was disregarded. The CPT was able to identify thin seams of loose liquefiable silt, and the SPT (with retrieved samples) allowed for reliable evaluation of the liquefaction susceptibility of fine-grained soils. A well-documented database of in situ and index testing is now available for incorporating in future CPT- and SPT-based liquefaction triggering correlations.     

Load Testing and Settlement Prediction of Shallow Foundation

The purpose of this study was to critically examine insitu test methods as a means for predicting settlement of shallow foundations. Accordingly, a 1.8?m (6?ft) diameter concrete footing was statically load tested. Prior to construction, insitu [standard penetration test (SPT), cone penetration test (CPT), dilatometer (DMT), and pressuremeter (PMT)] and laboratory tests were performed to determine engineering properties of the soil. Predictions of the footing settlement were made by traditional as well as finite element methods. The results of the static load test showed settlements were over predicted by all methods. However, the traditional methods provided reasonable settlement estimates using either SPT-N or back computed CPT(N) as input. Finite element analyses using either DMT or CPT derived input parameters provided reasonable settlement estimates. Finite element analyses using SPT or PMT derived input parameters provided poor settlement estimates. The Mohr–Coulomb (elastoplastic) model, accounting for overconsolidation, provided better estimates than the hardening soil (hyperbolic-cap) model for all insitu test derived parameters.     

Penetration Resistance of Offshore Skirted Foundations and Anchors in Dense Sand

Penetration of skirts is an essential design issue for offshore skirted foundations and anchors in sand. Skirts may not penetrate far enough into dense sand by the available submerged weight alone. It may therefore be necessary to apply underpressure inside the skirt compartment to produce an increased driving force and to reduce the penetration resistance. This paper recommends procedures to calculate penetration resistance and required underpressure for skirts penetrated in dense sand with and without interbedded clay layers. The recommendations are based on interpretation of skirt penetration data from prototypes, field model tests, and laboratory model tests in dense sand. The paper first presents a model to calculate the penetration resistance of skirts penetrated by weight, or other external vertical load that does not cause flow of water in the sand. Two models are considered; one based on bearing capacity equations with friction angles from laboratory tests, and the other one based on empirical correlations with CPT tip resistance. The bearing capacity model gives more consistent correlations with the empirical data than the CPT model. Thereafter, a model to account for the effect of underpressure applied inside the skirt compartment is proposed. This model is developed based on interpretation of available prototype and model test data from skirts penetrated by underpressure. The results show that underpressure facilitates skirt penetration in sand considerably by providing both an additional penetration force and a reduced penetration resistance. It is also shown that interbedded clay layers can prevent flow of water through the sand and eliminate the beneficial reduction in penetration resistance.