State-of-the-art AI-based computational analysis in civil engineering

C Wang, L Song, Z Yuan, J Fan - Journal of Industrial Information …, 2023 - Elsevier
With the informatization of the building and infrastructure industry, conventional analysis
methods are gradually proving inadequate in meeting the demands of the new era, such as …

Structural identification with physics-informed neural ordinary differential equations

Z Lai, C Mylonas, S Nagarajaiah, E Chatzi - Journal of Sound and Vibration, 2021 - Elsevier
This paper exploits a new direction of structural identification by means of Neural Ordinary
Differential Equations (Neural ODEs), particularly constrained by domain knowledge, such …

Machine learning-based seismic response and performance assessment of reinforced concrete buildings

F Kazemi, N Asgarkhani, R Jankowski - Archives of Civil and Mechanical …, 2023 - Springer
Complexity and unpredictability nature of earthquakes makes them unique external loads
that there is no unique formula used for the prediction of seismic responses. Hence, this …

Real‐time regional seismic damage assessment framework based on long short‐term memory neural network

Y Xu, X Lu, B Cetiner, E Taciroglu - Computer‐Aided Civil and …, 2021 - Wiley Online Library
Effective post‐earthquake response requires a prompt and accurate assessment of
earthquake‐induced damage. However, existing damage assessment methods cannot …

[HTML][HTML] Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods

N Asgarkhani, F Kazemi… - … Applications of Artificial …, 2024 - Elsevier
Abstract Nowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral
force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of …

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 …

A Bayesian deep learning approach for random vibration analysis of bridges subjected to vehicle dynamic interaction

H Li, T Wang, G Wu - Mechanical Systems and Signal Processing, 2022 - Elsevier
Vehicle actions represent the main operational loading for various types of bridges. It is
essential to conduct random vibration analysis due to the unavoidable uncertainties arising …

Recurrent neural networks for complicated seismic dynamic response prediction of a slope system

Y Huang, X Han, L Zhao - Engineering Geology, 2021 - Elsevier
Earthquake-induced landslides have resulted in huge casualties and considerable financial
repercussions, and slope dynamic response analysis has always been a hot issue. The …

The effect of soil-structure interaction on the seismic response of structures using machine learning, finite element modeling and ASCE 7-16 methods

T Ali, MN Eldin, W Haider - Sensors, 2023 - mdpi.com
Seismic design of structures taking into account the soil-structure interaction (SSI) methods
is considered to be more efficient, cost effective, and safer then fixed-base designs, in most …

Rapid seismic response prediction of RC frames based on deep learning and limited building information

W Wen, C Zhang, C Zhai - Engineering Structures, 2022 - Elsevier
Building portfolio is the important urban engineering system, and the seismic resilience
assessment of a city needs the quick and accurate prediction of the seismic responses of …