State of the art in structural health monitoring of offshore and marine structures

H Pezeshki, H Adeli, D Pavlou… - Proceedings of the …, 2023‏ - icevirtuallibrary.com
This paper deals with state of the art in structural health monitoring (SHM) methods in
offshore and marine structures. Most SHM methods have been developed for onshore …

State-of-the-art review on advancements of data mining in structural health monitoring

M Gordan, SR Sabbagh-Yazdi, Z Ismail, K Ghaedi… - Measurement, 2022‏ - Elsevier
To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …

Self-supervised learning for electroencephalography

MH Rafiei, LV Gauthier, H Adeli… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Decades of research have shown machine learning superiority in discovering highly
nonlinear patterns embedded in electroencephalography (EEG) records compared with …

Automated structural design of shear wall residential buildings using generative adversarial networks

W Liao, X Lu, Y Huang, Z Zheng, Y Lin - Automation in Construction, 2021‏ - Elsevier
Artificial intelligence is resha** building design processes to be smarter and automated.
Considering the increasingly wide application of shear wall systems in high-rise buildings …

Attention-based LSTM (AttLSTM) neural network for seismic response modeling of bridges

Y Liao, R Lin, R Zhang, G Wu - Computers & Structures, 2023‏ - Elsevier
Accurate prediction of bridge responses plays an essential role in health monitoring and
safety assessment of bridges subjected to dynamic loads such as earthquakes. To this end …

Intelligent structural design of shear wall residence using physics‐enhanced generative adversarial networks

X Lu, W Liao, Y Zhang, Y Huang - Earthquake Engineering & …, 2022‏ - Wiley Online Library
Intelligent structural design using generative adversarial networks (GANs) is a revolutionary
design approach for building structures. Despite its far‐reaching capability, the data quantity …

Data‐driven rapid damage evaluation for life‐cycle seismic assessment of regional reinforced concrete bridges

JG Xu, DC Feng, S Mangalathu… - … Engineering & Structural …, 2022‏ - Wiley Online Library
Rapid and accurate post‐earthquake damage evaluation of regional reinforced concrete
(RC) bridges is a key issue for assessing the seismic resilience of cities and communities …

Convolutional neural networks (CNNs)-based multi-category damage detection and recognition of high-speed rail (HSR) reinforced concrete (RC) bridges using test …

L Chen, W Chen, L Wang, C Zhai, X Hu, L Sun… - Engineering …, 2023‏ - Elsevier
The fast networking of high-speed rail (HSR) may cause in-service fatigue and ultimate load
damage to bridges. This paper investigates the application of deep convolutional neural …

Image-based reinforced concrete component mechanical damage recognition and structural safety rapid assessment using deep learning with frequency information

Z Bai, T Liu, D Zou, M Zhang, A Zhou, Y Li - Automation in construction, 2023‏ - Elsevier
Safety assessment of post-event damaged structures is vital and significant because it
directly affects life security, structural repair, and economic loss, especially in earthquakes …

A deep learning approach to rapid regional post‐event seismic damage assessment using time‐frequency distributions of ground motions

X Lu, Y Xu, Y Tian, B Cetiner… - … Engineering & Structural …, 2021‏ - Wiley Online Library
Every year, earthquakes result in severe economic losses and a significant number of
casualties worldwide. In limiting the losses that occur after these extreme events, timely and …