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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 …
methods are gradually proving inadequate in meeting the demands of the new era, such as …
Machine learning-based seismic response and performance assessment of reinforced concrete buildings
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 …
that there is no unique formula used for the prediction of seismic responses. Hence, this …
[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 …
force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of …
Structural identification with physics-informed neural ordinary differential equations
This paper exploits a new direction of structural identification by means of Neural Ordinary
Differential Equations (Neural ODEs), particularly constrained by domain knowledge, such …
Differential Equations (Neural ODEs), particularly constrained by domain knowledge, such …
Attention-based LSTM (AttLSTM) neural network for seismic response modeling of bridges
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 …
safety assessment of bridges subjected to dynamic loads such as earthquakes. To this end …
Real‐time regional seismic damage assessment framework based on long short‐term memory neural network
Effective post‐earthquake response requires a prompt and accurate assessment of
earthquake‐induced damage. However, existing damage assessment methods cannot …
earthquake‐induced damage. However, existing damage assessment methods cannot …
A Bayesian deep learning approach for random vibration analysis of bridges subjected to vehicle dynamic interaction
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 …
essential to conduct random vibration analysis due to the unavoidable uncertainties arising …
[HTML][HTML] Physics-informed deep learning-based real-time structural response prediction method
High-precision and efficient structural response prediction is essential for intelligent disaster
prevention and mitigation in building structures, including post-earthquake damage …
prevention and mitigation in building structures, including post-earthquake damage …
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 …
assessment of a city needs the quick and accurate prediction of the seismic responses of …
The effect of soil-structure interaction on the seismic response of structures using machine learning, finite element modeling and ASCE 7-16 methods
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 …
is considered to be more efficient, cost effective, and safer then fixed-base designs, in most …