Development of a seismic vulnerability and risk model for typical bridges considering innovative intensity measures

SQ Li, J Zhong - Engineering Structures, 2024‏ - Elsevier
Seismic intensity measures are one of the core parameters for estimating regional bridges'
seismic risk and vulnerability. Using macroscopic seismic intensity indicators to predict and …

Seismic acceleration response prediction method of the PSCFST bridge based on TCN

G Xue, J Miao, D Zhang, S Zuo, C Zhang… - Journal of Constructional …, 2025‏ - Elsevier
Precast segment self-centering concrete filled steel tube (PSCFST) bridge has become a
research hotspot in the field of infrastructure because of its excellent seismic performance …

A pre-trained deep learning model for fast online prediction of structural seismic responses

WJ Tang, DS Wang, HB Huang, JC Dai… - International Journal of …, 2024‏ - World Scientific
Deep learning techniques have gradually attracted considerable research interest in
numerous application scenarios because of their capacity to simplify and accelerate …

Predicting compressive strength of fiber-reinforced coral aggregate concrete: Interpretable optimized XGBoost model and experimental validation

Z Sun, X Wang, H Huang, Y Yang, Z Wu - Structures, 2024‏ - Elsevier
The addition of macro and micro fibers can enhance the compressive strength of fiber-
reinforced coral aggregate concrete (FRCAC-CS). Traditional explicit models for FRCAC-CS …

Performance evaluation of hybrid fiber-reinforced concrete based on electrical resistivity: Experimental and data-driven method

Z Sun, Y Li, T Han, L Su, X Zhu, J He, S **e… - Construction and Building …, 2024‏ - Elsevier
This study investigates the electrical resistivity (ER) of hybrid fiber-reinforced concrete
(HFRC) containing basalt micro fibers (BF) and basalt macro fibers (BMF) through …

Machine-Learning Applications in Structural Response Prediction: A Review

A Afshar, G Nouri, S Ghazvineh… - Practice Periodical on …, 2024‏ - ascelibrary.org
Structural health monitoring (SHM) is an important and practical procedure for ensuring the
structural integrity and serviceability of civil engineering structures such as bridges …

Response prediction and probabilistic analysis of the vehicle-ballasted track system considering track irregularity based on long-short term memory neural network

H Liu, L Song, L Xu, Z Yu - Engineering Applications of Artificial Intelligence, 2024‏ - Elsevier
It is necessary to efficiently and accurately predict the dynamic behavior of the train-track
system subjected to massive random track geometric excitations for system evaluation and …