Soil Liquefaction Potential Research Articles

Assessment of liquefaction potential of sand distributed in the coastal area of Ninh Thuan based on SPT values

The liquefaction potential of sandy soil has been widely investigated in the world for many years, especially after the Niigata and Alaska earthquakes in 1964. In which, the SPT values were mostly used for the evaluation of liquefaction potential. In Vietnam, the potential for soil liquefaction has been recently investigated. In the coastal area of Ninh Thuan province, the sand is widely distributed and often exposed on the surface. Additionally, many wind power farms have been built in this area. Thus, it is necessary to evaluate the liquefaction potential of sand distributed in this area. In this study, the potential for sand liquefaction in the coastal area of Ninh Thuan will be evaluated based on SPT values. Two common methods for evaluation of liquefaction potential proposed by Seed and Idriss; Idriss and Boulanger were employed. The research results show that at peak ground acceleration (amax) = 0.07 g and M = 5.5, the sand in the study area is non-liquefiable (safety factor against liquefaction, FS ( 1.48). However, at amax = 0.18 g and M = 7.5, the FS varies from 0.78 to 3.66 for the Seed and Idriss method and from 0.68 to 2.05 for the Idriss and Boulanger method. In general, the FS obtained from the Seed and Idriss method is higher than that obtained from Idriss and Boulanger method. Nevertheless, this insignificantly affects the overall assessment of liquefaction potential. At amax = 0.18 g and M = 7.5, the sand distributed in the study area can be liquefied at a depth of 17 m. However, it is not liquefied when the Nspt is higher than 28 ((N1) 60cs > 20).

Enhancing soil liquefaction risk assessment with metaheuristics and hybrid learning techniques

ABSTRACT Soil liquefaction has garnered significant research attention over several decades due to its profound impact on infrastructure systems in earthquake-prone regions. Given the limitations inherent in the assumptions and approximations of conventional methods, machine learning has emerged as a robust and efficient approach for predicting soil liquefaction potential. This study aims to develop a synergistic JS-CNN-XGB model, unifying the Jellyfish Search (JS) optimizer with a hybrid deep/machine learning model. This amalgamation leverages the feature extraction capabilities of the Convolutional Neural Network (CNN) alongside the classification prowess of the eXtreme Gradient Boosting (XGB) algorithm. The proposed model seamlessly integrates into a user-friendly prediction system, streamlining the liquefaction prediction process. Validation is achieved through case studies involving historical earthquake recordings with diverse classification ratios and varying input attribute quantities. Compared to existing studies, our proposed system showcases a notable 6.2% enhancement in overall liquefaction assessment accuracy, demonstrating improved detection capabilities in imbalanced and balanced datasets. In conclusion, this study underscores an automated system that presents a robust solution to the challenges posed by liquefaction potential assessment in geotechnical engineering.

Quantifying near-fault motion effects on soil liquefaction through effective stress site response analysis

Near-fault (NF) pulse-like ground motions have a significant impact on the performance of structures, but their effects on soil liquefaction potential have been relatively understudied. This paper uses 1D effective stress site response analysis capable of modeling porewater pressure (PWP) generation to investigate the seismic site response under NF and general ground motions. The aim is to assess the effects of NF motions on soil liquefaction by considering different soil models and PWP generation models. The results show that NF ground motions generally induce larger ground responses in terms of PWP generation, especially when the durations of the motions are short. This is due to the higher cumulative absolute velocity associated with NF ground motions compared with general ground motions due to a high-velocity pulse under the same peak ground acceleration. However, this effect diminishes as the duration of motion increases. To avoid underestimating seismic demand, especially for small to moderate earthquakes, a preliminary magnitude scale factor modified for the NF effect is suggested for use in conventional soil liquefaction triggering analysis.

Microbial nitrogen bubble formation in porous media

Microbially induced nitrogen (N2) gas bubbles can desaturate subsurface areas and thus have been considered as an alternative ground improvement technique for mitigating soil liquefaction potential caused by earthquakes. However, the detailed mechanisms of subsurface N2 bubbles are not well understood and remain a subject of ongoing research. In this study, a transparent microfluidic device was utilized to mimic biological N2 gas bubble formation by nitrate-reducing bacteria and to visually characterize the entire process. During N2 gas formation, a limited number of bubble nucleation sites were identified, which gradually expanded upward through the preferential pore channels. N2 gas bubbles tended to create interconnected gas pockets rather than existing as evenly distributed small gas cavities. The degree of water saturation gradually reduced over a week as the bubbles were produced. The gas ganglia repeatedly grew until they reached the top boundary, which triggered a drastic expulsion of bubbles by ebullition. Despite fluctuations in saturation level, the residual saturation was maintained at around 73 %. Comparative experimental case studies of CO2 gas bubble formation were conducted to identify contrasting gas formation mechanisms. CO2 gas bubbles were generated via the abiotic decompression of a supersaturated CO2 solution under two distinct rates of pressure reduction. Rapid CO2 bubble formation led to uniform nucleation and 41 % residual saturation, while slower formation yielded 35 % due to stable liquid displacement by the gas front. This study highlights the potential of the microfluidic device as an experimental tool for visualizing subsurface gas formation mechanisms. The insights gained could further enhance and optimize geotechnical applications involving gas formation in highly saturated soils.

Geotechnical assessment of seismicity and liquefaction potential at the Banarli landfill in Tekirdag, Turkey

This study, conducted in the Banarli district of Tekirdag Province, Turkey, focuses on soil reaction analysis and liquefaction potential in an area where a landfill and an associated power plant are planned. The research was examined with a one-dimensional ground response analysis to understand seismic behaviour, revealing the varied responses of soil categories to seismic waves. Soft soil layers were found to lengthen the dominant period of oscillation rather than significantly enhancing peak acceleration during seismic events. Earthquake records specific to the region were crucial for accurate assessments. The study comprehensively assessed liquefaction potential using various estimation methods, including the probability of liquefaction (PL ), liquefaction potential index (LPI), and liquefaction risk index (IR ). Moreover, this study examined liquefaction potential based on Standard Penetration Test (SPT) results, identifying susceptibility in the clayey sand layer at a depth of 3 to 12 meters. Recommendations for soil improvement measures are made to mitigate the risk. This research highlights the need for “customized seismic protocols” and emphasizes the importance of “site-specific assessments” in construction projects. By addressing susceptibility to liquefaction and proposing targeted ground improvement strategies, we contribute to safer and more resilient infrastructure development.

Corrigendum: The performance comparison of the decision tree models on the prediction of seismic gravelly soil liquefaction potential based on dynamic penetration test

Corrigendum: The performance comparison of the decision tree models on the prediction of seismic gravelly soil liquefaction potential based on dynamic penetration test

Sequential Gaussian simulation predicts soil liquefaction potential

The Yellow River Delta is covered with a large number of pipelines, but due to the complex soil composition in the region, ensuring that pipelines are not damaged by soil liquefaction is an important issue at present. Based on the simplified method of the cone penetration test (CPT), the sequential Gaussian simulation (SGS) can probabilistically simulate the liquefaction potential index (LPI) in the study area to solve the problem of the smoothing effect occurring in the kriging method. In this study, 10 experiments were conducted in the Yellow River Delta to evaluate soil liquefaction within the site using uncertainty analysis by the SGS method. The results indicate that (1) All LPI values in the study area are less than 5, with an overall sub-moderate liquefaction potential. (2) The results of the variogram model show that the Gaussian function model has the best fit with a Root Mean Squared Error of 0.429. The results of the e-type simulation realizations illustrate that the soils around the three sites S1, S5, and S10 exhibit high LPI values, distributed in a band in the middle of the western and eastern parts of the site. (3) Uncertainty analysis was performed using LPI = 2 as a threshold to explore the distribution of areas of moderate liquefaction potential and areas of low liquefaction potential in the study area. (4) Improvements were made to address the current problem of inappropriate values of liquefaction thresholds and the lack of medium liquefaction potential thresholds by proposing when LPI = 20 as the liquefaction threshold, LPI = 10 and 16 as the thresholds for low liquefaction potential, medium liquefaction potential and high liquefaction potential.

Probabilistic and Deterministic Assessment of Seismic Soil Liquefaction Potential in The Niger Delta Region of Nigeria Using Standard Penetration Test-Based

Probabilistic and Deterministic Assessment of Seismic Soil Liquefaction Potential in The Niger Delta Region of Nigeria Using Standard Penetration Test-Based

Evaluation and analysis of liquefaction potential of gravelly soils using explainable probabilistic machine learning model

Majority of the presently available machine learning (ML) models employed to assess the liquefaction potential of soils are for sands or sands containing silt fraction. In the current study, an explainable ML (EML) model has been developed using the updated liquefaction database of gravelly soils. The Chinese dynamic cone penetration test (DPT) and shear wave velocity test results of gravelly soils are used in the analysis. A new empirical correlation between these two in-situ tests’ results is developed using the final processed database. The light gradient boosting machine (LightGBM) is trained using this processed dataset and further tuned using Fast and Lightweight AutoML library (FLAML). The final tuned model shows relatively better deterministic and probabilistic predictive performance for the test sites as compared to the conventional method. An EML technique, SHapley Additive exPlanations (SHAP) is applied to provide further comprehension into the predictions. The developed LightGBM-SHAP model has achieved a right balance between explainability and accuracy. The obtained SHAP plots are consistent with almost all the existing domain knowledge (DK) in gravelly soil liquefaction. The developed model thus fills the gap between the ML-based procedures and the traditional DK of gravelly soil liquefaction.

Soil liquefaction potential of the central Adriatic Coast after the 9th of November 2022 earthquake (Italy)

Soil liquefaction potential of the central Adriatic Coast after the 9th of November 2022 earthquake (Italy)

Modelling and validation of liquefaction potential index of fine-grained soils using ensemble learning paradigms

This study explores the utilization of ensemble-based soft computing techniques for predicting the liquefaction potential of fine-grained soils. Generally, deterministic methods are used to assess the possibility of liquefactions. However, recent advancements have highlighted the implementation of machine learning techniques considering the diverse geotechnical characteristics for liquefaction susceptibility analysis. The current study predicts liquefaction potential index (LPI) of soils using five ensemble-based soft computing paradigms viz., decision tree, random forest, gradient boosting, AdaBoost, and XGBoost regressors. Various influential factors including stress parameters, depth of soil stratum, peak ground acceleration, earthquake magnitude, cyclic stress ratio, fine content, and SPT- N value, were used for estimating the LPI of soils. Experimental results of the employed models were assessed using multiple statistical indices. The results demonstrate that the employed XGBoost model achieved higher predictive accuracy with 99 % accuracy (based on R2 index) during the testing phase. Overall results exhibit that the employed XGBoost paradigm can be utilized as a viable alternative to empirical approaches, enabling an early assessment of liquefaction susceptibility in different engineering projects. This will expedite identification and evaluation of liquefaction hazards, allowing engineers to make more informed decisions.

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%.

Investigation of sand liquefaction potential in cyclic triaxial test and some premilinary research results in Vietnam

In the world, cyclic triaxial tests are widely used to evaluate the liquefaction potential of soil and determine the cyclic parameters for seismic design. However, the application of cyclic trixial test for evaluation of soil liquefaction is still limited in Vietnam. This paper introduced the cyclic triaxial apparatus, method and testing procedure to access the liquefaction potential of sand under cyclic loading. The research on some saturated sandy soils with high fine-grained content in Vietnam showed that the research results of soil liquefaction potential is reliable. In which, the liquefaction characteristics of sand are evaluated based on the changes of stress, strain and pore water pressure according to the cyclic cycles, thereby determining the liquefaction point and liquefaction boundary for fine sandy soils at different density levels.

Site response measurements and implications to soil liquefaction potential using microtremor H/V in Greater Metro Manila, Philippines

This research explores the use of microtremor horizontal-to-vertical spectral ratio (H/V) in obtaining site response characteristics and investigating its relationship with soil liquefaction potential in Greater Metro Manila. We performed single station microtremor measurements in 61 sites along with in situ geotechnical techniques to verify liquefaction potential. The resulting 238 spectral curves were classified according to dominant features and subsequently grouped with the calculated liquefaction potential index (LPI) of the soil. Based on a robust comparison of obtained primary parameters, it is revealed that the shape of the H/V curve, its predominant period and relative amplitude are fundamentally linked to the spatial variability and the shear strength of soils. Therefore, areas of high seismic demand can also have high liquefaction potential, and vice versa. We then correlated the predominant period with the LPI of the soil and extracted a boundary using simple statistical techniques to classify high and low potential for liquefaction subsequently validating its use as a complementary tool for rapid site-specific liquefaction assessment. Such findings are a novel contribution to liquefaction studies employing rapid techniques since the application of microtremors to liquefaction in the Philippines has not been practiced extensively.

Experimental study of the effects of initial shear stress on post-liquefaction behavior of submarine liquefiable ground: An energy-based evaluation

In offshore earthquake regions, granular soils are prone to liquefaction and flow failure, resulting in imponderable damage to adjacent structures. When the foundation is constructed on inclined terrains, initial static shear stress induced by the self-weight of slope soils can significantly affect the soil behavior and liquefaction potential. This paper discusses the effects of initial shear stress on the liquefaction and post-liquefaction behavior through an energy-based approach. A series of monotonic and cyclic undrained simple shear tests are performed under various initial shear stress levels. The cumulative dissipated energy is used to evaluate the effects of initial shear stress on typical soil behaviors, including the onset of instability in monotonic tests and the liquefaction in cyclic tests. In monotonic tests, the cumulative energy required for triggering instability decreases with the initial shear stress level at the post-liquefaction stage. Moreover, at the same relative density, a strain-softening response on virgin samples can be transformed into a strain-hardening type at the post-liquefaction stage. In cyclic tests, a unique correlation is found between cumulative energy and pore water pressure and it is closely related to the initial shear stress level. Based on the test results, two relationships are proposed to estimate the cumulative energy required for liquefaction or flow-type failure at the initial liquefaction and post-liquefaction stages.

Study of soil liquefaction potential at Anutapura General Hospital, Palu City, Central Sulawesi Province

On September 28, 2018, at 18:02 local time, a strong tectonic earthquake with a moment magnitude of 7.5 struck Central Sulawesi Province, Indonesia, triggering liquefaction disasters in Palu city and Sigi district. The project of the Anutapura Medical Centre (AMC) building at the Anutapura General Hospital in Palu city is one of the Indonesian government programs to support the rehabilitation and reconstruction of infrastructure after the earthquake. This hospital is located close to the liquefaction-affected area in Balaroa. Geologically, the hospital area is also located in the formation of Holocene deposits that have not been fully lithified. This study aims to analyze the liquefaction potential, which focuses on the construction area of the AMC building. The soil grain size distribution was used for the preliminary analysis of potentially liquified soils. The SPT-based liquefaction triggering procedure was used to calculate the safety factor (SF) against liquefaction. Subsequently, the SF value was further analyzed using the liquefaction severity index (LSI) to determine the severity level. The results show that soils in the study area have the potential to liquefy with a low to moderate severity level. The results are expected to be used as consideration to mitigate the possible liquefaction.

The Analysis of Liquefaction Potential and Post-Liquefaction Deformations at a Highway Bridge Crossing

The primary goal of this study is to geotechnically analyze the soil strength and liquefaction potential of the soil where the Seyrek highway junction and the bridge are built under earthquake-related dynamic stress. The analyses include comparisons of liquefaction potential using various empirical approaches, studies of post-liquefaction vertical deformation, and investigations into the influence of fill soil on liquefaction-induced surface deformation. Since the analyses of liquefaction potential in soils are made based on the "Simplified Method" approach, this method was also used in this study. This study also used the "Simplified Method" approach, which is the basis for studies of soil liquefaction potential. Four standard penetration tests (SPT) on the bridge piers were used to collect field data, and experiments in the lab were used to establish the requisite soil parameters. When the results of the Simplified Method analysis were performed according to the soil properties of the SK-1, SK-2, SK-3, and SK-4 drillings and the liquefaction analysis results were determined according to the required safety factor (Fs), liquefaction potential up to 18.5 meters was determined in all four SPT locations. Moreover, the results of surface damage effect analyses of the non-liquefied cover/fill layer on the Seyrek crossing bridge soil for all four SPP fields were found to be 'visible" and the liquefiable layer thickness (H2) was found to be 10.5 m. The calculated liquefaction severity index (LS) value was found to be up to 52, which means the liquefaction effect was found to be 'Possible liquefaction damage'.

The performance comparison of the decision tree models on the prediction of seismic gravelly soil liquefaction potential based on dynamic penetration test

Seismic liquefaction has been reported in sandy soils as well as gravelly soils. Despite sandy soils, a comprehensive case history record is still lacking for developing empirical, semi-empirical, and soft computing models to predict this phenomenon in gravelly soils. This work compiles documentation from 234 case histories of gravelly soil liquefaction from across the world to generate a database, which will then be used to develop seismic gravelly soil liquefaction potential models. The performance measures, namely, accuracy, precision, recall, F-score, and area under the receiver operating characteristic curve, were used to evaluate the training and testing tree-based models’ performance and highlight the capability of the logistic model tree over reduced error pruning tree, random tree and random forest models. The findings of this research can provide theoretical support for researchers in selecting appropriate tree-based models and improving the predictive performance of seismic gravelly soil liquefaction potential.

Analysis of Soil Liquefaction Potential through Field Tests Based Method

Abstract: Liquefaction is the phenomena when there is loss of strength in saturated and cohesion-less soils because of increased pore water pressures and hence reduced effective stresses due to dynamic loading. It is a phenomenon inwhich the strength and stiffness of a soil is reduced by earthquake shaking or other rapid loading. The recent increase in Landslides and the repeated evidence of ground failure due to liquefaction motivated this research project. Liquefaction is a soil mechanics problem that often impacts structures that are supported on saturated sanddeposits. The large deformations of the foundation soils typically cause major failures of civil engineering structures. This project involved research of the liquefaction phenomena and the impact experienced on select recent landslides

Characterized model uncertainties of CPT-based simplified procedures for assessing soil liquefaction and its application to Taiwan offshore wind farms

This paper aims to calibrate model uncertainties of the current Cone Penetration Test (CPT) methods for assessing soil liquefaction potential and introduce a new and concise one called the hyperbolic function (HBF) method based on the unique Chi-Chi earthquake database in Taiwan. The development and features of the HBF method were introduced at first. The performance and model uncertainty of each CPT method is then evaluated with a database of historical and Chi-Chi earthquake cases using the indices of the predicted success rate and bias-factor models, respectively. The success rate evaluations show that the HBF is one of the most accurate methods. The calibrated bias-factor models can indicate the conservatism of each CPT method applied to the Taiwan sites. Afterward, the liquefaction hazard curves associated with these CPT methods for Taiwan sites are derived based on the case histories of liquefaction and non-liquefaction in Taiwan. A real case study to illustrate the applications of these calibrated models evaluating liquefaction hazards to an offshore wind farm near Taiwan western coast is also demonstrated in this paper. These above results bring not only recommendations on CPT liquefaction assessment methods incorporated into the Technical Specifications for Site Investigation and Design of offshore wind farms in Taiwan, but procedures to calibrate regional biased models for other offshore wind farms in the world.