Application of ChatGPT in seepage-induced slope stability

ChatGPT has been recently applied to many engineering fields including geotechnical engineering. This study investigates the chance of using ChatGPT for seepage-induced slope stability problems based on the grid and radius method. The Python code for solving seepage and slope analysis was first generated, followed by the coupling of those two analyses was performed using ChatGPT. In addition, the grid search method and three scenarios of optimization methods were applied to determine the best optimization method for the computational efficiency of the developed framework. The comparable factor of safety (maximum error of 1.86%) shown in this study compared to those obtained by commercial software demonstrated the feasibility of using ChatGPT-generated code for seepage-induced slope stability analysis. Furthermore, the use of optimization techniques enabled up to a 70% reduction in calculation time, and the relatively easy implementation of optimization methods using ChatGPT implies that the appropriate prompts in ChatGPT can provide a wide range of applications in slope stability analysis.

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Publication Details

Journal
KSCE Journal of Civil Engineering
Published
2025-11-12
DOI
https://doi.org/10.1016/j.kscej.2025.100457
Primary Topic
Geotechnical Engineering and Analysis
Type
article
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article

Application of ChatGPT in seepage-induced slope stability

Jaeho Kwak, Jongmuk Won
KSCE Journal of Civil Engineering
Geotechnical Engineering and Analysis
article

Application of ChatGPT in seepage-induced slope stability

Jaeho Kwak, Jongmuk Won
article en

Abstract

ChatGPT has been recently applied to many engineering fields including geotechnical engineering. This study investigates the chance of using ChatGPT for seepage-induced slope stability problems based on the grid and radius method. The Python code for solving seepage and slope analysis was first generated, followed by the coupling of those two analyses was performed using ChatGPT. In addition, the grid search method and three scenarios of optimization methods were applied to determine the best optimization method for the computational efficiency of the developed framework. The comparable factor of safety (maximum error of 1.86%) shown in this study compared to those obtained by commercial software demonstrated the feasibility of using ChatGPT-generated code for seepage-induced slope stability analysis. Furthermore, the use of optimization techniques enabled up to a 70% reduction in calculation time, and the relatively easy implementation of optimization methods using ChatGPT implies that the appropriate prompts in ChatGPT can provide a wide range of applications in slope stability analysis.

KSCE Journal of Civil EngineeringVol. 30(4)
Ulsan National Institute of Science and Technology (KR)
Openalex Percentile: Top 59%
Geotechnical Engineering and Analysis
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Application of ChatGPT in seepage-induced slope stability — Jaeho Kwak, Jongmuk Won · KSCE Journal of Civil Engineering (2025) | TGRS Research Map | TGRS