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Soil Liquefaction in Geotechnical Engineering
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Soil Liquefaction in Geotechnical Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 2926

Special Issue Editor

Prof. Dr. Yu Zhao

E-Mail Website
Guest Editor
College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
Interests: geotechnical engineering; geological hazard; centrifuge test
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Soil liquefaction is always a challenging and hot topic in geotechnical disciplines, constantly at the forefront of research and discussion, because it poses a significant threat to buildings and infrastructure such as roads, bridges, and underground pipelines. Therefore, this Special Issue is intended for the presentation of new ideas and results in the field of soil liquefaction, covering topics from mechanism analyses to practical applications.

Areas relevant to soil liquefaction include, but are not limited to, soil liquefaction mechanism analyses, liquefaction evaluations, liquefaction mapping, liquefaction prediction, liquefaction-triggering procedures, liquefaction resistance criteria, post-liquefaction behaviors, soil liquefaction numerical simulations, and soil liquefaction centrifuge model tests.

This Special Issue will publish high-quality, original research papers in the overlapping fields below: 

  • Liquefaction resistance criteria；
  • Earthquake-induced liquefaction hazard；
  • Static liquefaction hazard；
  • Soil liquefaction mechanism analysis；
  • Liquefaction evaluation；
  • Liquefaction mapping；
  • Liquefaction prediction；
  • Liquefaction-triggering procedure；
  • Post-liquefaction behaviors;
  • Soil liquefaction numerical simulation；
  • Centrifuge model tests.

Prof. Dr. Yu Zhao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • liquefaction
  • earthquake
  • shear waves
  • seismic hazard
  • centrifuge modeling
  • liquefaction evaluation
  • numerical simulation
  • data mining
  • high overburden stress
  • geological age
  • porewater pressure
  • bender element test
  • static cone penetration test
  • standard penetration tests

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Published Papers (2 papers)

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21 pages, 4599 KB  
Article
Benchmarking ML Approaches for Earthquake-Induced Soil Liquefaction Classification
by Nuray Korkmaz Can, Erkan Caner Ozkat, Nurcihan Ceryan and Sener Ceryan
Appl. Sci. 2025, 15(21), 11512; https://doi.org/10.3390/app152111512 - 28 Oct 2025
Viewed by 675
Abstract
Earthquake-induced soil liquefaction represents a critical geotechnical challenge due to its nonlinear soil–seismic interactions and its impact on structural safety. Traditional empirical methods often rely on simplified assumptions, limiting their predictive capability. This study develops and compares six machine learning (ML) classifiers—namely, Support [...] Read more.
Earthquake-induced soil liquefaction represents a critical geotechnical challenge due to its nonlinear soil–seismic interactions and its impact on structural safety. Traditional empirical methods often rely on simplified assumptions, limiting their predictive capability. This study develops and compares six machine learning (ML) classifiers—namely, Support Vector Machine (SVM), Artificial Neural Network (ANN), k-Nearest Neighbor (kNN), Random Forest (RF), Decision Tree (DT), and Naïve Bayes (NB)—to evaluate liquefaction susceptibility using an original dataset of 461 soil layers obtained from borehole penetration tests in the Edremit region (Balıkesir, NW Turkey). The models were trained and validated using normalized geotechnical and seismic parameters, and their performance was assessed based on accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve (AUC). Results demonstrate that SVM, ANN, and kNN consistently outperformed other models, achieving test accuracies above 93%, F1 scores exceeding 98%, and AUC values between 0.933 and 0.953. In contrast, DT and NB exhibited limited generalization (test accuracy of 84–88% and AUC of 0.78–0.82), while RF showed partial overfitting. In contrast, DT and NB exhibited weaker generalization, with test accuracies of 84% and 88% and AUC values of 0.78 and 0.82, respectively, while RF indicated partial overfitting. The findings confirm the superior capability of advanced ML models, particularly SVM, ANN, and kNN, in capturing complex nonlinear patterns in soil liquefaction. This study provides a robust framework and original dataset that enhance predictive reliability for seismic hazard assessment in earthquake-prone regions. Full article
(This article belongs to the Special Issue Soil Liquefaction in Geotechnical Engineering)
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20 pages, 10406 KB  
Article
A Simplified Model to Predict the Repeated Shear Strain during the Cyclic Triaxial Test by Using an Elastic Coefficient-Damping Ratio System
by Darn-Horng Hsiao, Yao-Wen Liang and Chia-Sheng Hsieh
Appl. Sci. 2024, 14(10), 4178; https://doi.org/10.3390/app14104178 - 15 May 2024
Viewed by 1581
Abstract
Some researchers in past years have tried to develop a simplified method for analyzing soil liquefaction. However, the correctness of the pore water pressure in the model will affect the results. In addition, the formulas derived are not easy, and the exact parameters [...] Read more.
Some researchers in past years have tried to develop a simplified method for analyzing soil liquefaction. However, the correctness of the pore water pressure in the model will affect the results. In addition, the formulas derived are not easy, and the exact parameters of the model are difficult to obtain. This study used a mass-spring-damping system to simulate the repeated strain of liquefaction cyclic triaxial tests. Because the model is simple and the parameters are easy to understand and obtain, it also shows the extensibility of this model. During the parameter study, damping coefficient c and spring coefficient k parameters decreased with the increasing cyclic number. Preliminary results of the research show that this model can further simulate the repeated strain obtained by cyclic triaxial tests without considering the variation of effective stress during cyclic loading. Four samples were used to verify the model’s correctness, and their boring sites were found in Yunlin areas, Taiwan. Simulation results show that the spring-damping system is feasible for simulated cyclic triaxial tests because the simulated results correlate to the testing results in trend. Generally, the first cycle number simulation will be less accurate because the pore water pressure of the specimen changes rapidly when the performance has just started. In contrast, the increase in subsequent cycles may be biased due to cyclic stress variation and soil plasticity during simulation. In the future, pure sand specimens created in the laboratory will be suggested for simulation. Full article
(This article belongs to the Special Issue Soil Liquefaction in Geotechnical Engineering)
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