Liquefaction-induced Lateral Spreading Research Articles

Seismic Performance of Pile Groups under Liquefaction-Induced Lateral Spreading: Insights from Advanced Numerical Modeling

Post-earthquake investigations have shown that piles in liquefiable soils are highly susceptible to damage, especially in sloping sites. This study examines the seismic performance of pile groups with lateral spreading through advanced numerical modeling. A three-dimensional finite element model, validated against large-scale shaking table test results, is implemented to capture the key mechanisms driving the dynamic response of pile groups under both inertial and kinematic loading conditions. Parametric seismic response analyses are conducted to compare the behavior of batter and vertical piles under varying ground motion intensities. The results indicate that batter piles experience increased axial compressive and tensile forces compared to vertical piles, up to 70% and 20%, respectively. However, batter piles provide enhanced lateral stiffness and shear resistance compared to vertical piles, reducing horizontal displacements by up to 20% and tilting the cap by 85% under strong ground motion. The results demonstrate that batter piles not only enhance the overall seismic stability of the structure but also mitigate the risk of liquefaction-induced lateral spreading in the near-field through pile-pinning effects. While vertical piles are more commonly used in practice, the distinct advantages of batter piles for seismic stability highlighted in this study may encourage using more advanced numerical modeling in engineering projects.

Seismic behavior of piles-supported pier-superstructure to liquefaction-induced lateral spreading considering variability of soil permeability

Seismic behavior of piles-supported pier-superstructure to liquefaction-induced lateral spreading considering variability of soil permeability

Evaluation of soil liquefaction in the city of Hatay triggered after the February 6, 2023 Kahramanmaraş-Türkiye earthquake sequence

This study investigates the consequences of consequences of liquefaction hazards following the February 6, 2023, Kahramanmaraş Earthquakes in Hatay, Türkiye. Field reconnaissance surveys were conducted in areas prone to liquefaction, including recent alluvial basins, the Amik (Amuq) Plain, and the Asi (Orontes) River. Specifically, attention was given to İskenderun (Alexandretta), Dörtyol coasts, the Hatay Airport region, and Demirköprü village near the Asi River. Observations indicated that geological and geomorphological factors primarily influenced liquefaction ejecta and liquefaction-induced lateral spreading in these areas. In Dörtyol, liquefaction manifestations were observed on the coastline, which has undergone natural processes, while in İskenderun, they occurred on human-made extended reclaimed land. Additionally, liquefaction manifestations in the Hatay Airport region were impacted by the drained Amik Lake, and those in Demirköprü Village were influenced by the fluvial nature of the Asi River and its sub facies. The sites experiencing liquefaction and lateral spreading mainly comprised coastal deposits, lacustrine sediments, and sub facies of the meandering river, such as point bars, abandoned channels, and levees. Consequently, the study underscores the significant correlation between geomorphology and liquefaction hazards in the context of the 2023 Kahramanmaraş-Türkiye Earthquakes. Considering these factors may facilitate further research and the identification of sites susceptible to liquefaction.

Seismic fragility assessment of an in-service piled bridge abutment subjected to a liquefaction-induced lateral spreading and mitigation strategy

This study assesses the seismic fragility curves of in-service piled bridge abutments on liquefaction-prone soils and evaluates an optimal countermeasure within the vulnerability framework. Seismic fragility curves, accounting for varying ground motion intensities, assess the seismic risk and describe abutment damage through settlement measurements. The ageing abutment performance is estimated by integrating a corrosion model into fragility curves. The impact of different sheet pile positions on the seismic performance of in-service piled bridge abutments is analysed, and the optimal pile position is discussed. The developed fragility curves provide a rapid and effective risk assessment tool for the seismic performance of in-service abutments and guide liquefaction remedial measures.

Influence of Ground Slope and Relative Density on Liquefaction-Induced Lateral Spreading: A Physical Modeling

Influence of Ground Slope and Relative Density on Liquefaction-Induced Lateral Spreading: A Physical Modeling

Explainable AI models for predicting liquefaction-induced lateral spreading

Introduction: Earthquake-induced liquefaction can cause substantial lateral spreading, posing threats to infrastructure. Machine learning (ML) can improve lateral spreading prediction models by capturing complex soil characteristics and site conditions. However, the “black box” nature of ML models can hinder their adoption in critical decision-making.Method: This study addresses this limitation by using SHapley Additive exPlanations (SHAP) to interpret an eXtreme Gradient Boosting (XGB) model for lateral spreading prediction, trained on data from the 2011 Christchurch Earthquake.Result: SHAP analysis reveals the factors driving the model's predictions, enhancing transparency and allowing for comparison with established engineering knowledge. Notably, the SHAP values expose an unexpected behavior in the PGA feature. Moreover, the results demonstrate that the XGB model successfully identifies the importance of soil characteristics derived from Cone Penetration Test (CPT) data in predicting lateral spreading, validating its alignment with domain understanding.Discussion: This work highlights the value of explainable machine learning for reliable and informed decision-making in geotechnical engineering and hazard assessment.

A prediction model for residual shear strength of liquefiable soil based on lateral spreading cases

The residual shear strength of liquefiable soil plays an important role in evaluating the displacement magnitude of lateral spreading when applying the Newmark sliding block method. Currently, the empirical model is a mainstream alternative method for estimating the residual shear strength. In this study, a database of well-documented lateral spreading cases is used to establish an exponential function for residual shear strength evaluation correlated with the vertical effective stress and normalized standard penetration test blow counts for liquefied soil. A comparative analysis with two other empirical models is conducted, and the lateral spreading of the Wildlife Site during the Superstition Hills earthquake in 1987 is estimated using the Newmark sliding block method. The model exhibits good performance for soil residual shear strength estimation in cases of liquefaction-induced lateral spreading. The average estimated value of the residual shear strength may be appropriate for deterministic analyses in engineering practice.

Sustainability and Resilience Assessment of a Reinforced Concrete Bridge Subjected to Liquefaction-Induced Lateral Spreading

Sustainability and Resilience Assessment of a Reinforced Concrete Bridge Subjected to Liquefaction-Induced Lateral Spreading

Experimental Study of Pile Group Bridge Failure Mechanism Caused by Liquefaction-Induced Lateral Spreading

Experimental Study of Pile Group Bridge Failure Mechanism Caused by Liquefaction-Induced Lateral Spreading

Assessment of liquefaction potential based on shear wave velocity: Strain energy approach

Liquefaction assessment based on strain energy is significantly superior to conventional stress-based methods. The main purpose of the present study is to investigate the correlation between shear wave velocity and strain energy capacity of silty sands. The dissipated energy until liquefaction occurs was calculated by analyzing the results of three series of comprehensive cyclic direct simple shear and triaxial tests on Ottawa F65, Nevada, and Firoozkuh sands with varying silt content by weight and relative densities. Additionally, the shear wave velocity of each series was obtained using bender element or resonant column tests. Consequently, for the first time, a liquefaction triggering criterion, relating to effective overburden normalized liquefaction capacity energy (WL/σc’) to effective overburden stress-corrected shear wave velocity (Vs1) has been introduced. The accuracy of the proposed criteria was evaluated using in situ data. The results confirm the ability of shear wave velocity as a distinguishing parameter for separating liquefied and non-liquefied soils when it is calculated against liquefaction capacity energy (WL/σc’). However, the proposed WL/σc’-Vs1 curve, similar to previously proposed cyclic resistance ratio (CRR)-Vs1 relationships, should be used conservatively for fields vulnerable to liquefaction-induced lateral spreading.

Prediction of liquefaction-induced lateral spreading based on Neural network

In light of inherent errors associated with the existing methods for predicting lateral spreading of liquefied soil during earthquakes, a novel approach has been proposed. Based on the Newmark sliding block method, a neural network model has been trained to calculate lateral liquefaction displacement, which was achieved by compiling a substantial dataset and establishing a comprehensive seismic motion database. Taking into consideration six input features to train the sensitivity model, based on the sensitivity analysis, a predictive model for liquefaction-induced lateral spreading was developed include three parameters, moment magnitude, peak ground acceleration and yield acceleration. This model was then compared to empirical lateral spreading prediction models. The results demonstrate that this model shows notable concurrence with the existing empirical models. Additionally, using 22 well-documented cases of liquefaction-induced lateral spreading, three high-quality models were employed to predict residual shear strength of the soil. Notably, this novel model surpasses the performance of empirical liquefaction-induced lateral spreading prediction models.

Seismic performance of a sheet-pile retaining structure in liquefiable soils: Numerical simulations of LEAP-2022 centrifuge tests

This paper focuses on the numerical simulations of a sheet-pile retaining structure under liquefaction-induced lateral spreading, using data from LEAP-2022 dynamic centrifuge tests conducted at various facilities. The simulations employ an updated pressure-dependent multi-yield surface constitutive model (i.e., OpenSees PDMY03), incorporating dilatancy, cyclic mobility, and associated shear deformation features. To more accurately represent the liquefaction resistance characteristics of medium to dense Ottawa sands during LEAP-2022, the contractive and dilative rules of the PDMY03 model are updated based on experimental observations. Subsequently, the model parameters are calibrated through a series of stress-controlled cyclic direct simple shear (CDSS) tests to closely match the liquefaction strength curves of Ottawa sand. With these calibrated model parameters, dynamic response analyses of the sheet-pile retaining structure in liquefiable soils are performed, and the computed results are directly compared to the centrifuge experimental data. It is demonstrated that the updated PDMY03 constitutive model, combined with the employed computational framework, has the potential to realistically predict the experimental results of the sheet-pile retaining structure subjected to liquefaction-induced lateral spreading. Overall, this comprehensive approach enables a realistic evaluation of the performance of equivalent sheet-pile retaining structures under conditions of seismically-induced liquefaction, as well as other relevant scenarios.

Prediction model of lateral spreading of liquefied soil during earthquakes based on neural network

In response to the complex issue of predicting lateral spreading of liquefied soil during earthquakes, this study establishes a comprehensive seismic database. The Newmark sliding block method is utilized to calculate lateral displacements, and a sensitivity analysis model for liquefaction-induced lateral spreading is developed by considering multiple parameters. Based on the three most influential parameters identified through sensitivity analysis, a novel liquefaction-induced lateral spreading prediction model is proposed. The reliability of this new model is then demonstrated by comparing it with existing classical prediction models, as well as by analyzing correlation coefficients and root mean square errors.

A CAV Attenuation Model for Iran: Application to Liquefaction-Induced Lateral Spreading Assessment

A CAV Attenuation Model for Iran: Application to Liquefaction-Induced Lateral Spreading Assessment

Effects of Soil Crust on Seismic Failure Behavior of Pile Group–Bridge System during Liquefaction-Induced Lateral Spreading: Large-Scale Shake Table Experiments

Effects of Soil Crust on Seismic Failure Behavior of Pile Group–Bridge System during Liquefaction-Induced Lateral Spreading: Large-Scale Shake Table Experiments

Effects of non-liquefiable crust layer and superstructure mass on the response of 2 × 2 pile groups to liquefaction-induced lateral spreading

Effects of non-liquefiable crust layer and superstructure mass on the response of 2 × 2 pile groups to liquefaction-induced lateral spreading

Fluvial geomorphic factors affecting liquefaction-induced lateral spreading

Liquefaction-induced lateral displacements represent a major geohazard in earthquake-prone regions, yet the uncertainty associated with their prediction remains notoriously high. Documented observations after recent earthquakes provide evidence that depositional environment-specific geologic conditions play a crucial role in liquefaction susceptibility, and in the severity and spatial extent of liquefaction-induced ground deformations. However, this evidence is largely qualitative in nature, which limits the potential to incorporate the effects of depositional processes and environments in the next generation of lateral spreading predictive models. This study provides a framework to quantitatively assess the relationship between depositional environment-specific geologic factors and lateral spreading by means of simple fluvial geomorphic facies models, geotechnical engineering data (e.g. Cone Penetration Test data), and geospatial analytics. Three hypotheses are introduced and tested using lateral spreading ground deformations observed following the 2011 Christchurch earthquake along the Avon and Heathcote rivers in New Zealand. The results from this study indicate that the presence of an active (i.e. with active sediment deposition) compared to inactive (e.g. abandoned) channels is the most important fluvial geomorphologic variable out of the three tested. The other two are associated with the location relative to the meander bend position, including location within the point bar (inside) or the cut bank (outside), and upstream versus downstream within a given point bar. Findings from this study show that more lateral spreading occurs within point bars, and upstream (within a given point bar) in simple meander bends. However, the presence of geomorphic complexities (e.g. cut banks connected to an incised channel or tributary and/or channel confinement) can challenge the unbiased quantification of the contribution of a single geomorphic variable to the observed lateral displacements. These findings can be applied to other fluvial environments outside of New Zealand, and the proposed framework can be implemented for other non-fluvial depositional settings.

Smart prediction of liquefaction-induced lateral spreading

The prediction of liquefaction-induced lateral spreading/displacement (Dh) is a challenging task for civil/geotechnical engineers. In this study, a new approach is proposed to predict Dh using gene expression programming (GEP). Based on statistical reasoning, individual models were developed for two topographies: free-face and gently sloping ground. Along with a comparison with conventional approaches for predicting the Dh, four additional regression-based soft computing models, i.e. Gaussian process regression (GPR), relevance vector machine (RVM), sequential minimal optimization regression (SMOR), and M5-tree, were developed and compared with the GEP model. The results indicate that the GEP models predict Dh with less bias, as evidenced by the root mean square error (RMSE) and mean absolute error (MAE) for training (i.e. 1.092 and 0.815; and 0.643 and 0.526) and for testing (i.e. 0.89 and 0.705; and 0.773 and 0.573) in free-face and gently sloping ground topographies, respectively. The overall performance for the free-face topology was ranked as follows: GEP > RVM > M5-tree > GPR > SMOR, with a total score of 40, 32, 24, 15, and 10, respectively. For the gently sloping condition, the performance was ranked as follows: GEP > RVM > GPR > M5-tree > SMOR with a total score of 40, 32, 21, 19, and 8, respectively. Finally, the results of the sensitivity analysis showed that for both free-face and gently sloping ground, the liquefiable layer thickness (T15) was the major parameter with percentage deterioration (%D) value of 99.15 and 90.72, respectively.

Effects of liquefaction-induced lateral spreading on piles, an overview of physical modeling

Destructive damages to deep foundations due to liquefaction-induced lateral spreading during or after major earthquakes in gently sloping or level grounds with a free end have been observed in many earthquakes. The pile foundations supporting structures located in or near the ports and harbors, and also bridge piers, are the most vulnerable structures in this respect, as have been observed in various events in earthquake-prone areas all around the world for decades. Many physical and numerical modeling studies have been carried out to study and understand the insight into different aspects of this phenomenon. In this regard, 1g shake table and Ng centrifuge tests using both rigid and laminar shear boxes have been utilized to physically model the problem and measure the crucial parameters that may play an important role in the effects of lateral spreading on deep foundations. A number of countermeasures have also been examined for tackling this problem. In this paper, the authors describe shortly the physical modeling studies conducted by the first author and his coworkers including the second author on this subject during the last decade. In addition, the various parameters that are involved in physical modeling for studying the behavior of deep foundations subjected to liquefaction-induced lateral spreading are discussed herein. The limitations involved in such physical modeling are also mentioned and some solutions to the involved challenges are discussed as well.

Numerical Investigation of Inclined Piles under Liquefaction-Induced Lateral Spreading

Inclined piles have been widely applied as one of the countermeasures against large lateral spreading induced by soil liquefaction during earthquakes. However, the unsatisfactory performance of inclined piles in past events has impeded their application in seismic areas. To elucidate the performance of inclined piles when subjected to lateral spreading induced by soil liquefaction, numerical analyzes were performed using the OpenSees framework. For this purpose, a comprehensive three-dimensional finite element model was developed. Interface elements were used between the soil and the pile to account for the friction and gapping mechanisms. A multi-yield-surface plasticity constitutive relationship for sand was adopted to simulate the soil liquefaction behavior. Based on the proposed numerical model, parametric analyzes were conducted to investigate the influence of various factors on the behavior of inclined piles, including the raked angle of the pile, the ground slope, the soil profile, and the amplitude of the input motion. The response of the system indicates that inclined piles can behave better than vertical piles in decreasing soil deformation and the cap response. The influences of the investigated factors are highlighted to adopt the appropriate pile inclination in laterally spreading ground and maximize the advantages of using inclined piles.