308TC222

GIM-to-FEM: From digital ground information models to probabilistic numerical analysis of underground structures

Ksenija Micić, Novak Joksimović, Zehao Ye, Miloš Marjanović, Jelena Ninić

1427TC222

Monitoring Ground Settlement Adjacent to Deep Urban Excavations Using a Multi-Sensor Unmanned Ground Vehicle

Young-Hoon Jung, Taesik Kim, Jinman Jung, Hong Min, Choong-Ki Chung

616TC309

Performance prediction of track granular materials using machine learning approaches with an emphasis on input parameter selection

Rakesh Sai Malisetty, Buddhima Indraratna, Srinivas Alagesan, Haydn Hunt, Yujie Qi, Tim Neville

670TC309

Surrogate model of cofferdams based on physics informed neural networks

Kacper Cerek, Marek Wojciechowski, Elnaz Hadjiloo, Jürgen Grabe

730TC309

A Database-Driven and Machine Learning-Based Approach for Estimating Consolidation Parameters and Drainage Conditions Using CPTu Data

Iman Entezari, James Sharp, Dallas McGowan, Jason DeJong

793TC309

Improving Reliability of Slope Stability Predictions through Physics-Informed Machine Learning

Ekansh Agarwal, Te Pei, Ning Luo

963TC309

Advancing Safety Risk Assessment in Subsea Tunnel Excavation: A Digital Twin Framework Integrating Computer Vision and Material Point Method

Mingliang Zhou, Jie Xu, Zeyu Li, Qihao Jiang, Dongming Zhang, Hongwei Huang

1305TC309

Interpretable Artificial Intelligence for Subsidence Mapping Using City-Scale Geotechnical and Infrastructure Features

Homin Park, Yongmin Kim, Yuanshen Chua, Junghwan Kim, Taesik Kim, Ho Choi

1314TC309

Data-driven discovery of rheological model for steady-state and transient granular flows

Xu Han, Fiona C.Y.Kwok, Lu Jing, Gengchao Yang, Yuri Dumaresq Sobral

1697TC309

Superposition of Random Fields to model multi-output CPTu spatial variability

Stefano Collico, Lluís Monforte, Dani Tarragó, Amadeu Deu