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.     

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.     

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).     

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.     

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.     

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.     

CPT-Based Probabilistic Soil Characterization and Classification

Due to lack of soil sampling during conventional cone penetration testing, it is necessary to characterize and classify soils based on tip and sleeve friction values as well as pore pressure induced during and after penetration. Currently available semiempirical methods exhibit a significant variability in the estimation of soil type. Within the confines of this paper it is attempted to present a new probabilistic cone penetration test (CPT)-based soil characterization and classification methodology, which addresses the uncertainties intrinsic to the problem. For this purpose, a database composed of normalized corrected cone tip resistance (qt,1,net), normalized friction ratio (FR), fines content (FC), liquid limit (LL), plasticity index (PI), and soil type based on the unified soil classification system was complied. Soil classification was performed by laboratory testing of the standard penetration test disturbed samples retrieved from the boreholes within mostly 2?m of each CPT hole. The resulting database was probabilistically assessed through Bayesian updating methodology allowing full and consistent representation of relevant uncertainties, including (1) model imperfection; (2) statistical uncertainty; and (3) inherent variability. As a conclusion, different sets of FC, LL, PI, and A-line boundary curves along with a new CPT-based, simplified soil classification scheme are proposed in the qt,1,net and FR domain. Probabilistic uses of the proposed models are illustrated through a set of illustrative examples.     

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.     

Liquefaction Potential Index: Field Assessment

Cone penetration test (CPT) soundings at historic liquefaction sites in California were used to evaluate the predictive capability of the liquefaction potential index (LPI), which was defined by Iwasaki et al. in 1978. LPI combines depth, thickness, and factor of safety of liquefiable material inferred from a CPT sounding into a single parameter. LPI data from the Monterey Bay region indicate that the probability of surface manifestations of liquefaction is 58 and 93%, respectively, when LPI equals or exceeds 5 and 15. LPI values also generally correlate with surface effects of liquefaction: Decreasing from a median of 12 for soundings in lateral spreads to 0 for soundings where no surface effects were reported. The index is particularly promising for probabilistic liquefaction hazard mapping where it may be a useful parameter for characterizing the liquefaction potential of geologic units.     

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.     

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.     

SPT and CPT Testing for Evaluating Lateral Loading of Deep Foundations

Current design software (FloridaPier, Com624P) requires p-y curves to estimate the foundation lateral load resistance. Input parameters used to develop these curves can be obtained from in situ [standard penetration test (SPT) and cone penetration test (CPT)] correlations. This paper presents an evaluation of predictions using input soil parameters from SPT and CPT correlations versus field measured values. A lateral load test database consisting of 24 SPT and 6 CPT data sets was developed. The comparisons showed that four different SPT correlations for ? coupled with three different k-values all produce similar R-values. (R-value = measured∕predicted × 100%). Therefore, little difference exists between the SPT correlation combinations, albeit the estimated k value has a greater effect on predicted deformation. Similar combinations of CPT correlations also show little effect among the commonly used correlations. SPT predictions are quite conservative at low load levels (R-values ≈ 53%) and remain conservative (R-values ≈ 87%) at high load levels. Also, the scatter (standard deviation) is high (≈40%). CPT evaluations gave unconservative predictions (R-values ≈ 105 to 154%). In addition, the scatter (standard deviation) is high (≈34 to 74%).     

Probabilistic Seismic Demand Models and Fragility Estimates for Reinforced Concrete Highway Bridges with One Single-Column Bent

In performance-based seismic design, general and practical seismic demand models of structures are essential. This paper proposes a general methodology to construct probabilistic demand models for reinforced concrete (RC) highway bridges with one single-column bent. The developed probabilistic models consider the dependence of the seismic demands on the ground motion characteristics and the prevailing uncertainties, including uncertainties in the structural properties, statistical uncertainties, and model errors. Probabilistic models for seismic deformation, shear, and bivariate deformation-shear demands are developed by adding correction terms to deterministic demand models currently used in practice. The correction terms remove the bias and improve the accuracy of the deterministic models, complement the deterministic models with ground motion intensity measures that are critical for determining the seismic demands, and preserve the simplicity of the deterministic models to facilitate the practical application of the proposed probabilistic models. The demand data used for developing the models are obtained from 60 representative configurations of finite-element models of RC bridges with one single-column bent subjected to a large number of representative seismic ground motions. The ground motions include near-field and ordinary records, and the soil amplification due to different soil characteristics is considered. A Bayesian updating approach and an all possible subset model selection are used to assess the unknown model parameters and select the correction terms. Combined with previously developed capacity models, the proposed seismic demand models can be used to estimate the seismic fragility of RC bridges with one single-column bent. Seismic fragility is defined as the conditional probability that the demand quantity of interest attains or exceeds a specified capacity level for given values of the earthquake intensity measures. As an application, the univariate deformation and shear fragilities and the bivariate deformation-shear fragility are assessed for an example bridge.     

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.     

Standard Penetration Test-Based Probabilistic and Deterministic Assessment of Seismic Soil Liquefaction Potential

This paper presents new correlations for assessment of the likelihood of initiation (or “triggering”) of soil liquefaction. These new correlations eliminate several sources of bias intrinsic to previous, similar correlations, and provide greatly reduced overall uncertainty and variance. Key elements in the development of these new correlations are (1) accumulation of a significantly expanded database of field performance case histories; (2) use of improved knowledge and understanding of factors affecting interpretation of standard penetration test data; (3) incorporation of improved understanding of factors affecting site-specific earthquake ground motions (including directivity effects, site-specific response, etc.); (4) use of improved methods for assessment of in situ cyclic shear stress ratio; (5) screening of field data case histories on a quality/uncertainty basis; and (6) use of high-order probabilistic tools (Bayesian updating). The resulting relationships not only provide greatly reduced uncertainty, they also help to resolve a number of corollary issues that have long been difficult and controversial including: (1) magnitude-correlated duration weighting factors, (2) adjustments for fines content, and (3) corrections for overburden stress.     

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.     

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.     

Case History Evaluation of Laterally Loaded Piles

This paper examines seven case histories of load tests on piles or drilled shafts under lateral load. Since the current design software to estimate lateral load resistance of deep foundations requires p-y curves. The first approach used was correlative whereby soil parameters determined from in situ tests [standard penetration test (SPT) and cone penetration test (CPT)] were used as input values for standard p-y curves. In the second approach p-y curves were calculated directly from the stress deformation data measured in dilatometer (DMT) and cone pressuremeter tests. The correlative evaluation revealed that, on the average, predictions based upon the SPT were conservative for all loading levels, and using parameters from the CPT best predicted field behavior. Typically, predictions were conservative, except at the maximum load. Since traditionally SPT and CPT correlation-based p-y curves are for “sands” or “clays,” this study suggests that silts, silty sands, and clayey sands should use cohesive p-y curves. For the directly calculated curves, DMT derived p-y curves predict well at low lateral loads, but at higher load levels the predictions become unconservative. p-y curves derived from pressuremeter tests predicted well for both “sands” and “clays” where pore pressures are not anticipated.     

Probability of Exceedance Estimates for Scour Depth around Bridge Piers

Scour at a bridge pier is the formation of a hole around the pier due to the erosion of soil by flowing water; this hole in the soil reduces the carrying capacity of the foundation and the pier. Excessive scour can cause a bridge pier to fail without warning. Current predictions of the depth of the scour hole around a bridge pier are based on deterministic models. This paper considers two alternative deterministic models to predict scour depth. For each deterministic model, a corresponding probabilistic model is constructed using a Bayesian statistical approach and available field and experimental data. The developed probabilistic models account for the estimated bias in the deterministic models and for the model uncertainty. Parameters from both prediction models are compared to determine their accuracy. The developed probabilistic models are used to estimate the probability of exceedance of scour depth around bridge piers. The method is demonstrated on an example bridge pier. The paper addresses model uncertainties for given hydrologic variables. Hydrologic uncertainties have been presented in a separate paper.