[HTML][HTML] Interpreting random fields through the U-Net architecture for failure mechanism and deformation predictions of geosystems
The representation of spatial variation of soil properties in the form of random fields permits
advanced probabilistic assessment of slope stability. In many studies, the safety margin of …
advanced probabilistic assessment of slope stability. In many studies, the safety margin of …
Unfavorable geology recognition in front of shallow tunnel face using machine learning
Subsoil profile map** is typically based on spatially discrete borehole logs obtained from
site geotechnical investigations. During the map**, soil information between two …
site geotechnical investigations. During the map**, soil information between two …
Slope stability machine learning predictions on spatially variable random fields with and without factor of safety calculations
Abstract Random field Monte Carlo (MC) reliability analysis is a robust stochastic method to
determine the probability of failure. This method, however, requires a large number of …
determine the probability of failure. This method, however, requires a large number of …
Deep learning for efficient stochastic analysis with spatial variability
Using machine-learning models as surrogate models is a popular technique to increase the
computational efficiency of stochastic analysis. In this technique, a smaller number of …
computational efficiency of stochastic analysis. In this technique, a smaller number of …
Quantitative analysis of subway station seismic deformation under random earthquakes and uncertain soil properties using the equivalent linearization method
The seismic performance of underground structures is strongly influenced by the
characteristics of both the surrounding soil and the earthquake. In contrast to traditional …
characteristics of both the surrounding soil and the earthquake. In contrast to traditional …
[HTML][HTML] Development of mathematically motivated hybrid soft computing models for improved predictions of ultimate bearing capacity of shallow foundations
AI Lawal, S Kwon - Journal of Rock Mechanics and Geotechnical …, 2023 - Elsevier
Ultimate bearing capacity (UBC) is a key subject in geotechnical/foundation engineering as
it determines the limit of loads imposed on the foundation. The most reliable means of …
it determines the limit of loads imposed on the foundation. The most reliable means of …
Convolutional neural networks prediction of the factor of safety of random layered slopes by the strength reduction method
The strength reduction method is often used to predict the stability of soil slopes with
complex soil properties and failure mechanisms. However, it requires a considerable …
complex soil properties and failure mechanisms. However, it requires a considerable …
A RBFNN based active learning surrogate model for evaluating low failure probability in reliability analysis
L Cao, SG Gong, YR Tao, SY Duan - Probabilistic Engineering Mechanics, 2023 - Elsevier
This paper presents a novel active learning surrogate model for estimating low failure
probability in the reliability analysis of complex structures based on a radial basis function …
probability in the reliability analysis of complex structures based on a radial basis function …
Surrogate-assisted uncertainty modeling of embankment settlement
The structural optimization of basal reinforced piled embankments is usually conducted by
examining design alternatives while ignoring the inherent variability of soil properties and …
examining design alternatives while ignoring the inherent variability of soil properties and …
[HTML][HTML] A modified back analysis method for deep excavation with multi-objective optimization procedure
Real-time prediction of excavation-induced displacement of retaining pile during the deep
excavation process is crucial for construction safety. This paper proposes a modified back …
excavation process is crucial for construction safety. This paper proposes a modified back …