Assessment Of Soil Liquefaction Research Articles

Soil liquefaction manifestations at Hatay Airport after the February 2023 Türkiye earthquake sequence

Hatay Airport was shaken by the Mw 7.8 and Mw 7.5 Pazarcık and Ekinözü-Elbistan Kahramanmaraş earthquake sequence on February 6, 2023. Two weeks after these events, Mw 6.3 Yayladağı-Hatay earthquake shook the site again. This paper presents the results of the reconnaissance assessment of soil liquefaction at the site, focusing on mostly three aspects: (a) the seismic response of the Hatay Airport, particularly the surface manifestations of seismic soil liquefaction in the form of soil ejecta; (b) the findings of site investigation studies performed before and after the seismic events, and (c) assessments for soil liquefaction susceptibility. Among the soil ejecta samples collected, three out of five are classified as clayey sand and fall within or near the boundary of the “further studies required” region on the susceptibility charts. The remaining two ejecta samples, composed of low and high-plasticity clay soils with PI values of 31 and 36% fall within the “not susceptible” region. The deviation from the current state of knowledge might be attributed to liquefaction-induced seepage eroding clayey soils to the ground surface or limitations in the current liquefaction susceptibility assessment methods for fine-grained soils, which may not accurately delineate the boundaries between susceptible and not-susceptible zones. Determining the most likely explanation requires additional site investigation studies, including CPT soundings, extending beyond the scope of this reconnaissance study. The documented case history and assessment results are expected to enhance the understanding of seismic soil liquefaction in fine-grained soils and contribute to the development of predictive models based on case histories for assessing liquefaction susceptibility and triggering.

Initial assessment of soil liquefaction potential for selected sites in Hilla city, Babylon Governorate, Iraq

The current research focused on the use of some geotechnical characteristics for the initial assessment of soil liquefaction at sites in the city of Hilla, Babylon Governorate. Five sites were chosen in the city centre and relatively close to the Shatt Al-Hilla. Geotechnical properties data were used to separate soils that can be classified as liquefiable from those that are not. The criteria used in this study were of two types: the Second Chinese Criteria, which is based on the natural water content and liquid limit; and the Modified Chinese Criteria, which depends on the clay content and liquid limit for the liquefaction potential of the soil. The results of this study showed that in the Second Chinese Criteria the risk of soil increases with an increase in the natural water content and a decrease in the liquid limit; however, in the Modified Chinese Criteria, the liquefaction potential increases with a decrease in the clay content to less than 10% and in the liquid limit to less than or equal to 32%.

Soil Liquefaction Assessment by CPT and VS Data and Incomplete-Fuzzy C-Means Clustering

Soil Liquefaction Assessment by CPT and VS Data and Incomplete-Fuzzy C-Means Clustering

Assessment of soil liquefaction beneath the National Capital Region of Delhi: implications for earthquake-resilient structures

Assessment of soil liquefaction beneath the National Capital Region of Delhi: implications for earthquake-resilient structures

Model uncertainties of SPT, CPT, and VS-based simplified methods for soil liquefaction assessment

Simplified methods for assessing soil liquefaction potential based on the standard penetration test (SPT) are prevalent in practice and widely accepted by several seismic design codes. When encountering sites that have not been investigated using SPT, such as offshore sites or sites with a high level of gravel content, engineers can only substitute the methods based on piezocone penetration test data (CPT-qc methods) or shear wave velocity measurements (VS-based methods); however, these two approaches perform inconsistently with methods based on SPT data (SPT-N methods). As a result, this paper exploits the datasets consisting of SPT, CPTU, and in situ seismic test measurements from 13 alluvium sites in the Taipei Basin to compare the performance of prevalent SPT-N, CPT-qc, and VS-based methods. The discrepancies (uncertainties) of these methods are characterized as Gaussian distribution models, which is believed to be a feasible strategy for predicting equivalent results for SPT-N methods when SPT data are not available. Finally, the application of the proposed models to liquefaction potential index evaluation is demonstrated using a real case study.

Interpretation of In Situ State Parameters of Piezocone Penetration Tests in High Pile Rebound Soils

Abstract Cone penetrometer testing (CPT) was performed along with pile driving analysis (PDA) at six piling projects to determine typical soil characteristics encountered during excessive pile rebound. The PDA test was used to develop profiles of rebound versus elevation, while the CPT test was utilized to provide continuous variations of soil parameters with depth. In situ data from the CPT and PDA tests were matched based on depth and elevation, then averaged over four depth intervals ranging from 1B to 8B (B is the pile’s diameter). The results indicated that the rebound and non-rebound CPT data plots clustered in distinctive regions on the soil liquefaction assessment chart. The rebound data showed dilative behavior with state parameter values less than −0.125, while the non-rebound data exhibited contractive behavior, with larger state parameter values. Predictive models for estimating the magnitude of pile rebound in terms of normalized CPT data were thus developed using stepwise linear and nonlinear regression analyses. The results for these showed promising correlations between rebound, pore water pressure, cone tip resistance and state parameter predicted as a function of friction ratio. Additionally, the depth of soil layers underneath the pile’s toe was found to play a prominent role in controlling the extent and the amount of rebound. The CPT data as averaged over 4B and 8B intervals also showed a clear tendency to determine problematic pile rebound zones, though no such tendency was seen in data averaged over 1B and 2B intervals.

Probabilistic Soil Liquefaction Assessment: A Case Study for Agartala City in Tripura in North-East India

A sudden increase in pore water pressure causes the effective stress to decrease significantly, which in turn causes a loss of shear strength and the subsequent outcome of allowing the soil to behave as a liquid, resulting in soil liquefaction. Agartala, the capital of Tripura, is located in northeastern India, and the entire region is considered seismically active according to the seismic zoning map of India as per IS 1893:2002 (Part 1); the entire region is classified as Zone-V. Significant earthquakes have struck this region, including the 1897 Shillong and 1950 Assam earthquakes. The city is vulnerable to liquefaction due to alluvial soil and a low groundwater table. Several parameters are involved in assessing liquefaction potential in the deterministic method and have different input parameter uncertainties, resulting in inconsistent outcomes. As a result, evaluating liquefaction susceptibility requires a thorough probability approach that considers parameter uncertainty. In this work, the soil liquefaction potential of Agartala City is assessed using fuzzy logic and compared to the conventional Reliability technique using the first-order second-moment method. Soil liquefaction potential was properly calculated using both approaches for the 71 boreholes in and around Agartala city. The outcomes are shown as contour maps representing spatial variations of the probability of liquefaction at different depths. In this study, Fuzzy logic is used to model the relationships between different soil parameters, which can help better understand the soil\'s behaviour during liquefaction. This developed method can assess the vulnerability of liquefaction potential and select appropriate materials and construction processes.

Explainable machine learning model for liquefaction potential assessment of soils using XGBoost-SHAP

Most of the existing machine learning (ML)-based models for liquefaction assessment of soils are black-box in nature. Database considered in the existing studies for model development is imbalanced. In this study, an attempt is made to include the coefficient of permeability and thickness of the critical layer from the available information to the existing database. The eXtreme Gradient Boosting (XGBoost) ML algorithm is used for the model development in a probabilistic framework. The k-means synthetic minority oversampling technique (SMOTE) is introduced to improve the overall accuracy of the model by suitably modelling the imbalanced dataset. An improvement of the model is also performed by tuning the hyperparameters using searching algorithms to increase further the accuracy. An explainable machine learning (EML) technique, SHapley Additive exPlanations (SHAP) is employed to provide additional insights into the developed XGBoost model. From the SHAP results, it is found that the equivalent clean sand cone penetration resistance and coefficient of permeability are the first and the fourth important input parameters affecting the liquefaction potential. It is concluded that the EML technique is capable of bridging the gap between the conventional domain knowledge of liquefaction and soft computing approaches.

Soil liquefaction assessment by using hierarchical Gaussian Process model with integrated feature and instance based domain adaption for multiple data sources

For soil liquefaction prediction from multiple data sources, this study designs a hierarchical machine learning model based on deep feature extraction and Gaussian Process with integrated domain adaption techniques. The proposed model first combines deep fisher discriminant analysis (DDA) and Gaussian Process (GP) in a unified framework, so as to extract deep discriminant features and enhance the model performance for classification. To deliver fair evaluation, the classifier is validated in the approach of repeated stratified K-fold cross validation. Then, five different data resources are presented to further verify the model’s robustness and generality. To reuse the gained knowledge from the existing data sources and enhance the generality of the predictive model, a domain adaption approach is formulated by combing a deep Autoencoder with TrAdaboost, to achieve good performance over different data records from both the in-situ and laboratory observations. After comparing the proposed model with classical machine learning models, such as supported vector machine, as well as with the state-of-art ensemble learning models, it is found that, regarding seismic-induced liquefaction prediction, the predicted results of this model show high accuracy on all datasets both in the repeated cross validation and Wilcoxon signed rank test. Finally, a sensitivity analysis is made on the DDA-GP model to reveal the features that may significantly affect the liquefaction.

ОЦЕНКА СЕЙСМИЧЕСКОЙ РАЗЖИЖАЕМОСТИ ГРУНТОВ ЮЖНОЙ ЧАСТИ БАРЕНЦЕВА МОРЯ

The article presents analysis of results of seismic liquefaction assessment of soils distributed in the southern part of the Barents Sea. Studies of the tendency of seabed soils to liquefaction were carried out as part of the engineering-geological surveys for the construction of production facilities of the Shtokman gas-condensate field (ShGKF). A review of similar studies carried out in seismically hazardous areas of the Black Sea, the Sea of Azov and the Sea of Okhotsk is given. It is noted that formation of seismic deformations caused by liquefaction of soils is very dangerous for oil and gas production facilities both onshore and offshore. The dynamic stability of soils in the southern area of the Barents Sea was performed based on the results of cone penetration testing and calculation of seismic liquefaction potential. It is shown that the studied clay and sandy soils of the foundations of the ShGKF project facilities, on the basis of cone penetration testing, are not prone to liquefaction under the seismic loads typical for the southern part of the Barents Sea. At the same time values of seismic liquefaction potential indicate the possibility of coastal sandy soils transition to fluid state for earthquakes of 7,7 intensity according to the MSK-64 scale. It is recommended to predict the danger of liquefaction of these soils by dynamic properties laboratory determination.

Seismic gravelly soil liquefaction assessment based on dynamic penetration test using expanded case history dataset

Seismic gravelly soil liquefaction assessment based on dynamic penetration test using expanded case history dataset

Assessment and identification of three types of difficult soils

The soil engineer needs to be able to readily identify difficult or problematic soils and to determine the amount of settlement that may occur. This paper deals with the assessment and identification of three types of difficult soils: collapsible soils, swelling soils, and liquefiable soils. In the first instance, the study investigates the effect of some soil properties on wetting-induced collapse strain and the swelling potential of soils. Also, two new methods for predicting soil collapse and swelling potential are developed. The proposed relationships correlate between collapse strain and swelling potential and some soil parameters which are believed to govern soil collapse and swelling. Validation of these two relationships with some data reported in literature is also examined. Furthermore, the paper describes the different steps suggested in a new procedure for soil liquefaction assessment. The procedure was presented in the form of an evaluation guide. In addition, a relationship was suggested for computing the potential for liquefaction. An application of the proposed procedure to a practical case is included in order to validate and illustrate the different steps to be followed in the suggested evaluation procedure.

A constrained neural network model for soil liquefaction assessment with global applicability

A constrained back propagation neural network (C-BPNN) model for standard penetration test based soil liquefaction assessment with global applicability is developed, incorporating existing knowledge for liquefaction triggering mechanism and empirical relationships. For its development and validation, a comprehensive liquefaction data set is compiled, covering more than 600 liquefaction sites from 36 earthquakes in 10 countries over 50 years with 13 complete information entries. The C-BPNN model design procedure for liquefaction assessment is established by considering appropriate constraints, input data selection, and computation and calibration procedures. Existing empirical relationships for overburden correction and fines content adjustment are shown to be able to improve the prediction success rate of the neural network model, and are thus adopted as constraints for the C-BPNN model. The effectiveness of the C-BPNN method is validated using the liquefaction data set and compared with that of several liquefaction assessment methods currently adopted in engineering practice. The C-BPNN liquefaction model is shown to have improved prediction accuracy and high global adaptability.

Soil Liquefaction Assessment Using Soft Computing Approaches Based on Capacity Energy Concept

Soil liquefaction is one of the most complicated phenomena to assess in geotechnical earthquake engineering. The conventional procedures developed to determine the liquefaction potential of sandy soil deposits can be categorized into three main groups: Stress-based, strain-based, and energy-based procedures. The main advantage of the energy-based approach over the remaining two methods is the fact that it considers the effects of strain and stress concurrently unlike the stress or strain-based methods. Several liquefaction evaluation procedures and approaches have been developed relating the capacity energy to the initial soil parameters, such as the relative density, initial effective confining pressure, fine contents, and soil textural properties. In this study, based on the capacity energy database by Baziar et al. (2011), analyses have been carried out on a total of 405 previously published tests using soft computing approaches, including Ridge, Lasso & LassoCV, Random Forest, eXtreme Gradient Boost (XGBoost), and Multivariate Adaptive Regression Splines (MARS) approaches, to assess the capacity energy required to trigger liquefaction in sand and silty sands. The results clearly prove the capability of the proposed models and the capacity energy concept to assess liquefaction resistance of soils. It is also proposed that these approaches should be used as cross-validation against each other. The result shows that the capacity energy is most sensitive to the relative density.

Exposure and loss assessment of soil liquefaction in coastal area of Kulon Progo, Indonesia

Soil Liquefaction is a phenomenon of loss of strength of the granural soil layers due to increased pore water stress caused by earthquake shocks. Soil liquefaction can cause material and life damage if occurs in the developed area. Kulon Progo Regency based on the Atlas of Liquefaction Susceptibility Zones in 2019, has high susceptibility zones, which has the potential for flow liquefaction, lateral spreading, vertical displacement, and sand boil. This study aims to assess the exposure and loss index in liquefaction hazard zone based on the characteristics of land use and social demographic. The exposure index is obtained from overlaying between susceptibility map and liquefaction exposure variables, when the loss assessment is done by simulating the losses in several earthquake moment magnitude scenarios. Study results show that high exposure surrounding the residential zone in the south of the Wates Urban Area and the construction location of the Yogyakarta International Airport. There are settlement areas potentially affected by lateral spreading in Glagah, Karangwuni, Banaran, and Karangsewu Villages. While the results of the loss assessment show that transport infrastructure and residential buildings are the most affected objects when liquefaction phenomena occur due to the earthquake. Managing the expansion of settlement area through zoning regulation and technical engineering approach is needed to reduce losses due to future liquefaction phenomenon.

Probabilistic assessment of soil liquefaction considering spatial variability of CPT measurements

ABSTRACTThe conventional liquefaction potential assessment methods (also known as simplified methods) profoundly rely on empirical correlations based on observations from case histories. A probabilistic framework is developed to incorporate uncertainties in the earthquake ground motion prediction, the cyclic resistance prediction, and the cyclic demand prediction. The results of a probabilistic seismic hazard assessment, site response analyses, and liquefaction potential analyses are convolved to derive a relationship for the annual probability and return period of liquefaction. The random field spatial model is employed to quantify the spatial uncertainty associated with the in-situ measurements of geotechnical material.

Assessment of soil liquefaction based on capacity energy concept and multivariate adaptive regression splines

Soil liquefaction is one of the most complicated phenomena to assess in geotechnical earthquake engineering. The procedures that have been developed to determine the liquefaction potential of sandy soil deposits can be categorized into three main groups: stress-based, strain-based, and energy-based procedures. The main advantage of the energy-based approach over the other two methods is the fact that it considers the effects of strain and stress concurrently unlike the stress or strain-based methods. Several liquefaction evaluation procedures have been developed, relating the capacity energy to initial soil parameters such as the relative density, initial effective confining pressure, fine contents and soil textural properties. Analyses have been carried out on a total of 302 previously published tests using a nonparametric regression procedure known as multivariate adaptive regression splines (MARS), to assess the capacity energy required to trigger liquefaction in sand and silty sands. The capacity energies estimated by this proposed model compare favorably with the centrifuge test data sets used for validation purpose.

In situ-based assessment of soil liquefaction potential-Case study of an earth dam in Tunisia

The present paper examines the evaluation of liquefaction potential of an earth dam foundation in Tunisia. The assessment of soil liquefaction was made using deterministic and probabilistic simplified procedures developed from several case histories. The data collected from the field investigation performed before and after the vibrocompaction are analyzed and the results are reported. The obtained results show that after vibrocompaction, a significant improvement of the soil resistance reduces the liquefaction potential of the sandy foundation. Indeed, in the untreated layers, the factor of safety FS drops below 1 which means that the soil is susceptible for liquefaction. However, in the compacted horizons, the values of FS exceed the unit which justifies the absence of liquefaction hazard of the foundation.

3D liquefaction assessment of soils surrounding circular tunnels

The aim of this paper is to investigate the effect of underground circular tunnels on cyclic behavior and liquefaction potential of soils surrounding them. For this purpose, an intensive numerical analyses scheme which includes three-dimensional, finite difference based total stress analyses on generic soil, tunnel and earthquake combinations has been performed. The effect of tunnel diameters, depth of tunnel center, support thickness of tunnels and the strength of soils have been discussed in detail. It is concluded that changing the diameter and support thickness of the tunnels does not make a remarkable change on surface acceleration. Similarly, the liquefaction potential of the soils considered does not depend on the diameter and support thickness. However, it was shown that the most important parameter defining the liquefaction potential is the depth of the tunnel from the ground surface. If the tunnels are deeper, they are less vulnerable to liquefaction compared to shallow tunnels.

Simplified Soil Liquefaction Assessment Based on Cumulative Kinetic Energy Density: Attenuation Law and Probabilistic Analysis

AbstractLiquefaction of sandy soils has led to catastrophic damage to structures during past earthquakes. Implementing simplified procedures such as the shear-stress method is the most prevalent current practice in assessing liquefaction. Because there may be no perfect single simplified procedure, use of multiple methods is reasonable to minimize the risk of uncertainty. This paper presents an alternative simplified method for assessing soil liquefaction that is based on the cumulative kinetic energy density (CKED). Strong ground-motion data were employed, and with the aid of a genetic programming tool, an attenuation relationship was developed for estimating the CKED in liquefiable sites. CKED at a given layer depth was estimated by applying a depth-reduction factor. A simple correlation was developed for estimating the depth-reduction factor by way of equivalent linear site-response analysis on actual liquefiable soil profiles. The performance of the model presented herein was evaluated by implementing...