Strain energy based evaluation of liquefaction and residual pore water pressure in sands using cyclic torsional shear experiments

In this study, cyclic hollow cylinder torsional tests were conducted on the reconstituted specimens of Toyoura sand in a practical range of initial density and stress states. The results were employed to evaluate the liquefaction resistance and residual pore water pressure of sand using the strain energy concept. A simple pore water pressure (PWP) model with two calibration parameters was developed for the prediction of residual pore pressure as a function of cumulative strain energy density and the capacity energy of sand. Capacity energy is defined as the cumulative strain energy that is required for liquefaction onset. Based on the results of the tests, an equation is then presented for the estimation of capacity energy in terms of relative density and initial effective confining pressure of sand. This equation is shown to work well as a state boundary curve, which can discriminate between the liquefied and non-liquefied field case histories. Several extra tests were also performed to investigate the effect of initial static shear stress on the proposed PWP model and capacity energy. The results show that initial shear stress has a minor effect on the trend of the proposed PWP model; however, it definitely affects the capacity energy. The final part of the paper aims to confirm reasonable performance of the proposed PWP model by the available observations of seismically induced pore water pressure in shaking table, centrifuge, and real site conditions.     

A pattern recognition approach to evaluation of soil liquefaction potential using piezocone data

A pattern recognition approach to liquefacation evaluation is propoesed. The state of any soil layer at a level ground site subject to seismic loads is represented by a pattern in a seven-dimensional feature space and can be classified into one of three classes: liquefiable cohesive soil, and non-liquefiable cohesionless soil. The liquefaction potential of the soil layer can be assessed according to the probabilities of the pattern belonging to the three classes. Training patterns derived from field data (piezocone (CPTU) data and maximum ground acceleration) from sites which liquefied or did not liquefy during earthquakes in New Zealand are randomly chosen to design a pattern recognition system to provide an optimal estimation of the liquefaction potential of any soil stratum of interest. Two recognition systems have been set up to estimate the state-conditional probability density function. One is based on a Parzen window approach in which no knowledge of the probabilistic structure of the training patterns is assumed; the other is based on a parameter estimation approach assuming a multivariate normal distribution. The error rate of recognition by the Parzen window approach is 6·9% when taking the window size as 1·5, and the error rate by the parameter estimation approach, which can be easily, is 7·7%. implemented without reference to our training patterns     

Assessment of liquefaction triggering using strain energy concept and ANN model: Capacity Energy

In the present study, an artificial neural network (ANN) model was developed to establish a correlation between soils initial parameters and the strain energy required to trigger liquefaction in sands and silty sands. A relatively large set of data including 284 previously published cyclic triaxial, torsional shear and simple shear test results were employed to develop the model. A subsequent parametric study was carried out and the trends of the results have been confirmed via some previous laboratory studies. In addition, the data recorded during some real earthquakes at Wildlife, Lotung and Port Island Kobe sites plus some available centrifuge tests data have been utilized in order to validate the proposed ANN-based liquefaction energy model. The results clearly demonstrate the capability of the proposed model and the strain energy concept to assess liquefaction resistance (capacity energy) of soils.     

Cyclic undrained behavior of silty sand

Laboratory cyclic triaxial tests were performed to investigate the effect of fine content on the pore pressure generation in sand. Strain-controlled, consolidated undrained tests have been performed with a cyclic shear strain range of 0·015-1·5%. These tests were carried to 1000 cycles or to initial liquefaction, which ever occurred first. Triaxial tests were performed on pure sand silt specimens and specimens with silt additions of 10, 20, 30, and 60% by weight. Two types of silt, a non-plastic silt and a low plasticity silt (PI 10) were used as control materials. The main parameters varied in this study were the amount of silt, the plasticity index of silt, and the void ratio where the observed parameter was the pore pressure generation. For all silt contents, silt plasticity and the number of loading cycles have no significant effect at strain levels below 0·01%. Therefore, threshold strain for silty sands have approximately the same value as sands. For both non-plastic and low plasticity silts, there is a significant increase in the generated pore pressure at high strain levels.     

Assessment of liquefaction potential based on peak ground motion parameters

Conventionally, evaluation of liquefaction potential of loose saturated cohesionless deposits as specified in Japanese design codes employs peak ground acceleration (PGA). However, recent large-scale earthquakes in Japan revealed that liquefaction at some sites did not occur even though large PGAs were recorded at or near these sites. As an alternative approach, an evaluation procedure based on peak ground motion parameters, i.e. incorporating both PGA and the peak ground velocity (PGV), is proposed. By performing parametric studies using one-dimensional seismic response analysis and formulating regression models, seismic-induced shear stresses within the deposit are expressed in terms of peak ground motion parameters at the surface, and these are used to calculate the factor of safety against liquefaction. Application to case histories in Japan indicates that the proposed two-parameter equation can adequately account for the occurrence and non-occurrence of liquefaction at various sites as compared to the conventional PGA-based approach. Moreover, analyses of several strong motion records at various sites show that liquefaction may occur when PGA≥150 gal and PGV≥20 kine, indicating that these values can serve as thresholds in assessing the possible occurrence of liquefaction.     

An experimental study of the liquefaction strength of silty sands in terms of the state parameter

An elaborate program of monotonic and cyclic triaxial laboratory tests on mixtures of sand and silt with fines content 0%, 15% and 25% was performed to investigate the effect of density, consolidation stress and non-plastic fines on the liquefaction strength. The monotonic tests illustrated that the critical state lines of all mixtures do not cross each other, and are, approximately, parallel to each other. The results of the cyclic tests illustrated that the relationship between the cyclic strength and the state parameter does not depend on the consolidation stress, the soil density and the silt content. Analysis in terms of the state parameter showed that: (i) as the consolidation stress increases, the cyclic strength decreases and this effect is more pronounced as the specimens become denser, especially as the fines content increases and (ii) the cyclic strength decreases as the fines content increases and this effect is more pronounced as the specimens become denser.     

基于液化SPT基准值的液化势估计

基于神经网络BP模型和可靠度理论,并沿用抗震规范中液化标准贯入锤击数基准值概念,建立了简化的液化判别概率方法。文中以液化标准贯入锤击数作为估计液化势的基本依据。该基准值是给定地面加速度、土层埋深、地下水位的液化临界锤数,也与震级大小和液化概率有关。为了对不同震级和土层中任一点进行液化判别,引入土层埋深水位以及震级大小对基准值的修正系数。为了方便工程应用,也给出了按地震分组的液化判别方法。     

Evaluation of liquefaction potential using neural-networks and CPT results

In this research, a reliable Cone Penetration Test data set was gathered with a wide range of parameters. This data was incorporated in a Neural-Networks computer software called STATISTICA Neural-Networks. The back propagation algorithm with a multilayer perceptron network is utilized to analyze the liquefaction occurrence in different sites. In this study, different sets of effective parameters for the neural-network analyses are selected such that to reduce the noise and to obtain more accurate results.Considering the relative importance of effective parameters in liquefaction assessment, it is indicated that σ₀, σ′₀ together play a more important role than what previously was assumed and hence the relative importance of the q_c and seismic parameters are decreased compared with the previous works. The results presented here have more accuracy than previous works while at the same time, the range of the parameters used in this study is much wider than what was previously used. This range of parameters makes the proposed method applicable for practical purposes.     

Seismic liquefaction potential assessment by using Relevance Vector Machine

Determining the liquefaction potential of soil is important in earthquake engineering. This study proposes the use of the Relevance Vector Machine (RVM) to determine the liquefaction potential of soil by using actual cone penetration test (CPT) data. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The results are compared with a widely used artifi cial neural network (ANN) model. Overall, the RVM shows good performance and is proven to be more accurate than the ANN model. It also provides probabilistic output. The model provides a viable tool for earthquake engineers to assess seismic conditions for sites that are susceptible to liquefaction.     

Influence of colloidal silica grout on liquefaction potential and cyclic undrained behavior of loose sand

Cyclic triaxial tests were performed to investigate the influence of colloidal silica grout on the deformation properties of saturated loose sand. Distinctly different deformation properties were observed between grouted and ungrouted samples. Untreated samples developed very little axial strain prior to the onset of liquefaction. However, once liquefaction was triggered, large strains occurred rapidly and the samples collapsed within a few additional loading cycles. In contrast, grouted sand samples experienced very little strain during cyclic loading. Additionally, the strain accumulated uniformly throughout loading rather than rapidly prior to collapse and the samples never collapsed. Cyclic triaxial tests were done on samples stabilized with colloidal silica at concentrations of 5, 10, 15, and 20%. In general, samples stabilized with higher concentrations of colloidal silica experienced very little strain during cyclic loading. Sands stabilized with lower concentrations tolerated cyclic loading well, but experienced slightly more strain. Thus, treatment with colloidal silica grout significantly increased the deformation resistance of loose sand to cyclic loading.     

Study of pore pressure variation during liquefaction using two constitutive models for sand

Numerical analyses of liquefiable sand are presented in this paper. Liquefaction phenomenon is an undrained response of saturated sandy soils when they are subjected to static or dynamic loads. A fully coupled dynamic computer code is developed to predict the liquefaction potential of a saturated sandy layer. Coupled dynamic field equations of extended Biot's theory with u–P formulation are used to determine the responses of pore fluid and soil skeleton. Generalized Newmark method is employed for integration in time. The soil behavior is modelled by two constitutive models; a critical state two-surface plasticity model, and a densification model. A class ‘B’ analysis of a centrifuge experiment is performed to simulate the dynamic response of level ground sites. The results of the numerical analyses demonstrate the capability of the critical sate two-surface plasticity model in producing pore pressures that are consistent with observations of the behavior of liquefiable sand in the centrifuge test.     

An improved method of evaluating liquefaction potential with the velocity of shear-waves

According to the results of cyclic triaxial tests, a linear correlation is presented between liquefaction resistance and elastic shear modulus, which shows the relation of G _max (kPa) with (σ_d/2)^1/2(kPa)^1/2. When applied to soils from different sites, the correlation can be normalized in reference to its minimum void ratio (e _min). Accordingly, an improved method is established to evaluate the liquefaction potential with shear-wave velocity. The critical shear-wave velocity of liquefaction is in linear relation with 1/4 power of depth and the maximum acceleration during earthquakes, which can be used to explain the phenomenon that the possibility of liquefaction decreases with the increment of the depth. Compared with previous methods this method turns out simple and effective, which is also verified by the results of cyclic triaxial tests. Foundation item: State Natural Science Foundation (59678020) and Natural Science Foundation of Zhejiang Province (RC9609).     

Spatial variability of liquefaction potential in regional mapping using CPT and SPT data

Cone penetration test (CPT) and standard penetration test (SPT) are widely used for the site specific evaluation of liquefaction potential and are getting increased use in the regional mapping of liquefaction hazard. This paper compares CPT and SPT-based liquefaction potential characterizations of regional geologic units using the liquefaction potential index (LPI) across the East Bay of the San Francisco Bay, California, USA and examines the statistical and spatial variability of LPI across and within geologic units. Overall, CPT-based LPI characterizations result in higher hazard than those derived from the SPT. This bias may result from either mis-classifications of soil type in the CPT or a bias in the CPT simplified procedure for liquefaction potential. Regional mapping based on cumulative distribution of LPI values show different results depending on which dataset is used. For both SPT and CPT-based characterizations, the geologic units in the area have broad LPI distributions that overlap between units and are not distinct from the population as a whole. Regional liquefaction classifications should therefore give a distribution, rather than a single hazard rating that does not provide for variability within the area. The CPT-based LPI values have a higher degree of spatial correlation and a lower variance over a greater distance than those estimated from SPTs. As a result, geostatistical interpolation can provide a detailed map of LPI when densely sampled CPT data are available. The statistical distribution of LPI within specific geologic units and interpolated maps of LPI can be used to understand the spatial variability of liquefaction potential.     

Assessment of soil liquefaction incorporating earthquake characteristics

This paper investigates the effect of nature of the earthquake on the assessment of liquefaction potential of a soil deposit during earthquake loading. Here, the nature of the earthquake is included via the parameter V, the ‘pseudo-velocity’, that is the gross area under the acceleration record of the earthquake at any depth below the ground surface. By analysing a number of earthquake records from different parts of the world, a simple method has been outlined to assess the liquefaction potential of a soil deposit based on the pseudo-velocity. For many earthquakes occurred in the past, acceleration records are available or can be computed at the ground level or some other depth below the ground surface. Therefore, this method is a useful tool at the preliminary design stage to determine the liquefaction potential before going into a detailed analysis. Validation of the method is carried out using a database of case histories consisting of standard penetration test values, acceleration records at the ground surface and field observations of liquefaction/non-liquefaction. It can be seen that the proposed method has the ability to predict soil liquefaction potential accurately, despite its simplicity.     

基于遗传神经网络的砂土液化判别模型

针对BP人工神经网络具有易陷入局部极小等缺陷，本文提出了将遗传算法与神经网络相结合，同时优化网络结构与权值、阈值的思想。根据地震液化的实测资料，建立了砂土液化判别的遗传神经网络模型，比较计算结果证明了该模型的科学性、高效性。文中并进行主成分分析，提出液化影响的主要因素。     

Niveo-aeolian sedimentation of loess and sand: An experimental and micromorphological approach

The concept of a ‘niveo-aeolian influence’ on the genesis of northwest European Pleistocene aeolian sand and loess deposits has been advocated in the past both to explain the presence and the absence of lamination. Field experiments were carried out on artificially deposited alternating layers of sand and snow, and of loess and snow, to investigate the role of a niveo-aeolian mode of deposition on resulting sedimentary structures. Field observations of sand plots revealed minor changes in surface morphology typical of denivation surfaces. The thin sections showed a characteristic porous structure. Deformations of the depositional structure and indications for erosion and redeposition were limited. However, the originally smooth aeolian sedimentary surface of the loess changed considerably. The thin sections showed also a porous, spongy structure. Indications were found for disturbances by frost action, liquefaction during melting of the snow and ice, and redeposition of loess by meltwater. The experimental results strongly suggest that sand and loess deposited as niveo-aeolian material are characterized both by a porous structure, and that the original sedimentary structure of the sand is not affected by snowmelt, whereas loess becomes non-laminated. Thus, the intercalation of snow during sedimentation of sand and loess does not in itself induce a laminated structure.     

Excess pore pressure dissipation and solidification after liquefaction of saturated sand deposits

To understand the post-liquefaction behavior of liquefied ground, it is important to get a better understanding and a more suitable characterization of the variation of excess pore pressure after liquefaction. In this paper, the soil permeability is considered as one of the key soil parameters for clarifying the mechanism of post-liquefaction behavior of liquefied ground. For this reason, a series of shaking table tests were conducted for a Toyoura sand deposit with different soil permeability values. Polymer fluid was used in model tests to vary the permeability of sand deposits. Excess pore pressures and settlements were measured in each test. A basic mechanism in post-liquefaction behavior and the solidification phenomenon after liquefaction were discussed based on these test results. Also, a new method for predicting the dissipation of excess pore pressure was developed. This study provides evidence of the important effect of soil permeability on the velocity with which the solidification front moves upward in liquefied ground. It is suggested that the value of coefficient of permeability of liquefied sand can increase to about 4.0 times the initial value. This variation of permeability after liquefaction should be taken into account in post-liquefaction analysis.     

Evaluation of liquefaction potential of soil based on standard penetration test using multi-gene genetic programming model

This paper discusses the evaluation of liquefaction potential of soil based on standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). The liquefaction classification accuracy (94.19%) of the developed liquefaction index (LI) model is found to be better than that of available artificial neural network (ANN) model (88.37%) and at par with the available support vector machine (SVM) model (94.19%) on the basis of the testing data. Further, an empirical equation is presented using MGGP to approximate the unknown limit state function representing the cyclic resistance ratio (CRR) of soil based on developed LI model. Using an independent database of 227 cases, the overall rates of successful prediction of occurrence of liquefaction and non-liquefaction are found to be 87, 86, and 84% by the developed MGGP based model, available ANN and the statistical models, respectively, on the basis of calculated factor of safety (F _s ) against the liquefaction occurrence.     

Neural network model for liquefaction potential in soil deposits using Turkey and Taiwan earthquake data

Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. Derived from several field and laboratory tests, various simplified procedures such as stress-based, strain-based, Chinese criteria, etc. have been developed by utilizing case studies and undisturbed soil specimens. In order to address the collective knowledge built up in conventional liquefaction engineering, an alternative general regression neural network model is proposed in this paper.To meet this objective, a total of 620 sets of data including 12 soil and seismic parameters are introduced into the model. The data includes the results of field tests from the two major earthquakes that took place in Turkey and Taiwan in 1999 and some of the desired input parameters are obtained from correlations existing in the literature.The proposed GRNN model was developed in four phases, mainly: identification phase, collection phase, implementation phase, and verification phase. An iterative procedure was followed to maximize the accuracy of the proposed model. The case records were divided randomly into testing, training, and validation datasets.Generating a model that takes into account of 12 soil and seismic parameters is not feasible by using simplified techniques; however, the proposed GRNN model effectively explored the complex relationship between the introduced soil and seismic input parameters and validated the liquefaction decision obtained by simplified methods. The proposed GRNN model predicted well the occurrence/nonoccurrence of soil liquefaction in these sites. The model provides a viable tool to geotechnical engineers in assessing seismic condition in sites susceptible to liquefaction.     

Dynamic liquefaction of Jurassic sand dunes: processes,Origins, and implications

Soft‐sediment deformation occurs in ancient eolian dune deposits, but understanding its extent and the conditions and forces behind the deformation often remains elusive. Here we gain insight into the aerial extent and environmental conditions related to intense soft‐sediment deformation, based on an exceptional three dimensional (3D) exposure of eolian dune deposits and preserved geomorphic landscape expressions in the Jurassic Navajo Sandstone at White Pocket, Vermilion Cliffs National Monument, Arizona. Deformation features include elongate northeast trending decameter‐scale mounds and raised ridges cored by deformed and upturned eolian dune sets, overlain by a massive blanket sandstone with breccia blocks. The geomorphic mounds display ~40–60 m spacing, roughly perpendicular to the southerly paleoflow dune foreset directions. The geometry of the deformation is imaged by oblique aerial photography using cameras mounted on a remote control airplane and high resolution panoramas with a robotic camera mount. We interpret the exquisitely preserved deformation features as liquefaction‐induced ground failure, consistent with theoretical and laboratory studies of deformation in saturated sand. A shallow water table affected by differential dune loading facilitated lateral spreading and failure. The transition to steady‐state flow liquefaction near the top of the shallow water table destroyed original sedimentary structure, creating a massive sand blanket that entrained brecciated blocks ripped up during flow. The water‐pressurized, upwelled sediment created the mounds (a relief inversion). In underlying deformed dune sets, deformation was intense but sedimentary structure was not obliterated as deformation progressed from initial cyclic mobility to strain‐softening, but ceased prior to steady‐state flow liquefaction. The spatial extent, topographic relief, and intensity of dynamic deformation suggest an origin of strong ground motion driven by long‐duration surface waves of a large earthquake (> Mw 7–8), possibly related to back arc thrusting from Jurassic subduction of the Pacific plate under North America. Copyright © 2014 John Wiley & Sons, Ltd.