Simplified Method for Spatial Evaluation of Liquefaction Potential in the St. Louis Area

As a part of an earthquake hazard mapping program being undertaken by the U.S. Geological Survey in the St. Louis metropolitan area, surficial geologic mapping and subsurface geotechnical data have been compiled into a three-dimensional geographic information system (GIS). The potential for soil liquefaction was then spatially evaluated by using subsurface information from 562 boreholes for an assumed M7.5 earthquake emanating from the New Madrid Seismic Zone. Geotechnical data (standard penetration test N-values, overburden pressure, and depth-to-groundwater) and the scenario peak ground accelerations (PGA = 0.1, 0.20, and 0.30??g) were applied to evaluate the factor of safety (FS) against earthquake-induced liquefaction. The liquefaction potential index (LPI) method was used in these evaluations because it allows for calculations of FS with depth for 10–25 discrete stratigraphic horizons overlying the bedrock across the St. Louis metropolitan area. LPI values were derived from the correlation between calculated LPI values and the depths-to-groundwater within late Quaternary stratigraphic units. The St. Louis metropolitan area was then classed according to four levels of severity of risk from liquefaction: (1)?no liquefaction potential, (2)?little-to-no likelihood, (3)?moderate, and (4)?severe.     

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 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.     

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.     

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.     

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.     

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.     

Effect of Surface Texturing on CPT Friction Sleeve Measurements

As the use of the cone penetration test (CPT) has increased for geotechnical site characterization, significant research has been performed to identify and control the factors that affect the tip (qc), sleeve (fs), and pore pressure (u) measurements. However, a number of factors that affect the friction sleeve have yet to be understood, appreciated, and accounted for in penetrometer designs. This paper highlights a number of these issues, with specific attention centered on the effect of surface texturing on the friction sleeve measurement. An understanding of the role of surface roughness on soil-geomaterial interfaces provides a framework for analyzing the effect on the friction sleeve measurement and could provide a basis to improve its design. A series of CPT soundings were performed in the southeast United States with conventional smooth and textured friction sleeves. Results indicate that friction measurements with a textured sleeve are 70% greater on average than the value obtained with a conventional smooth friction sleeve in sand and provide a basis for developing new design procedures where interface values are required.     

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.     

Logistic Regression Model for Evaluating Soil Liquefaction Probability Using CPT Data

A simple model for evaluating liquefaction probability using cone penetration test (CPT) data is developed based on logistic regression analyses of 396 case histories. The proposed model uses the normalized cone penetration resistance and soil behavior type index as input parameters; therefore, only CPT testing is necessary for evaluating the liquefaction probability of a site. The selection of the model parameters and the expression of equations are based on results of probability examinations and rigorous statistical analyses. Moreover, the derivation of the logistic regression model is presented in a system of equations. The incorporation of these procedures in developing the model not only fully satisfies the statistic requirements but also highlights the physical meanings of the model parameters. Comparisons of the proposed probability model with previously proposed deterministic and probabilistic approaches are performed to demonstrate the improvements. For practical purposes, the developed model is implemented to establish the relationship between the factor of safety against liquefaction and the probability of liquefaction.     

Random Field Modeling of CPT Data

An extensive set of cone penetration tests (CPT) soundings are analyzed statistically to produce an a priori 1D stochastic soil model for use at other similar sites. The data were collected by the Norwegian Geotechnical Institute at the site of a new airport just north of Oslo, Norway, and consists of 143 CPT soundings over an area of about 18 km2 in a reasonably homogeneous soil mass. The CPT data consist of cone tip resistance, side friction, and pore-water pressure measurements. Only the cone tip resistance is considered in this study, it being considered closest to a “point” property of the soil, and only the vertical variation is characterized. To perform the statistical analysis, the data sets are viewed as independent 1D realizations extracted from a statistically homogeneous 3D random field. Plots of various transformations of the data indicate that the cone tip resistance records are best represented using a fractal stochastic model corresponding to so-called fractional Brownian motion, and its parameters are estimated via maximum likelihood.     

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.     

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.     

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.     

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.     

Different Approaches for Estimating Ground Strains from Pile Driving Vibrations at a Buried Archeological Site

Ground strains were estimated from vibrations measured during pile driving operations at a buried, prehistoric archeological site to monitor potential construction impacts. Subsurface characteristics of the site were investigated using multiple cone penetration test (CPT) soundings and the shear wave velocity profile was measured using the seismic CPT method. Embedded geophones and surface accelerometers were then used to measure ground vibrations during pile driving. Displacement gradients were estimated from the vibrations using the following three methods: (1) the difference between adjacent displacements divided by sensor spacing; (2) peak particle velocity divided by depth-dependent wave velocity (i.e., at the depth where the sensor was placed); and (3) peak particle velocity divided by frequency-dependent wave velocity from a measured dispersion curve. Methods (1) and (3) agreed well, while method (2) caused errors that depended on depth of embedment of the sensors and distance from pile driving. Errors in (2) were attributed to a mismatch between the depth-dependent wave velocity and the wave velocity on the frequency band that carried the largest velocity pulse through the dispersive soil profile. Ground strains were related to displacement gradients based on theoretical solutions of harmonic body waves and Rayleigh waves in dispersive elastic media. The peak estimated ground strains were smaller than the threshold volumetric shear strain, but a few centimeters of settlement were nevertheless observed at the site. The spatial extent of the settlement is characterized using attenuation rules fit to the vibration data, and by calibration with a settlement gauge. Ground cracking and vertical offsets that could potentially mask the archaeological history of the site were neither observed nor predicted from the observed vibration amplitudes. Estimated impact on archeological interpretation of artifacts in their stratigraphic context was likely insignificant except in the immediate region where the piles were driven. This insight will assist in future planning at sites with similar subsurface stratigraphy.     

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.     

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).     

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.     

Influence of Nonplastic Fines on Shear Wave Velocity-Based Assessment of Liquefaction

Many false positives (no liquefaction detected when the normalized shear wave velocity-cyclic stress ratio (Vs1-CSR) combination indicated that it should have been) are observed in the database used in the simplified liquefaction assessment procedure based on shear wave velocity. Two possible reasons for false positives are the presence of a thick surface layer of nonliquefiable soil and the effects of fines on cyclic shear resistance (CRR) and Vs1. About 67% of the false positives that could not have been caused by an overlying thick surface layer are associated with silty sands with less than 35% fines. The effects of fines on the liquefaction resistance of silty sands and on the shear wave velocity are analyzed. Theoretical CRRfield?versus?Vs1 curves for silty sands containing 0 to 15% nonplastic fines are established. They show that the theoretical CRR-Vs1 correlations for silty sands with 5 to 15% nonplastic fines are all located to the far left of the semi-empirical curves that separate liquefaction from no-liquefaction zones in the simplified liquefaction potential assessment procedures. The results suggest the currently used shear wave velocity-based liquefaction potential curves may be overly conservative when applied to sands containing nonplastic fines.