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 …

Seismic response prediction of a train-bridge coupled system based on a LSTM neural network

P Xiang, P Zhang, H Zhao, Z Shao… - Mechanics Based Design …, 2024 - Taylor & Francis
High complexity and randomness in high-speed train-bridge interactive dynamic analysis
under earthquake lead to massive calculations in high-speed railway seismic design. To …

LSTM, WaveNet, and 2D CNN for nonlinear time history prediction of seismic responses

C Ning, Y Xie, L Sun - Engineering Structures, 2023 - Elsevier
Predicting the nonlinear time-history responses of civil engineering structures under seismic
loading remains an essential task in earthquake engineering. This paper explores the …

Recent advances in uncertainty quantification in structural response characterization and system identification

K Zhou, Z Wang, Q Gao, S Yuan, J Tang - Probabilistic Engineering …, 2023 - Elsevier
Structural dynamics has numerous practical applications, such as structural analysis,
vibration control, energy harvesting, system identification, structural safety assessment, and …

Deep learning-based methods in structural reliability analysis: a review

SS Afshari, C Zhao, X Zhuang… - … Science and Technology, 2023 - iopscience.iop.org
One of the most significant and growing research fields in mechanical and civil engineering
is structural reliability analysis (SRA). A reliable and precise SRA usually has to deal with …

Fast seismic response estimation of tall pier bridges based on deep learning techniques

C Li, H Li, X Chen - Engineering Structures, 2022 - Elsevier
Seismic responses of tall pier bridges are usually estimated with nonlinear time history
analysis (NLTHA) since it is able to provide rigorous results while the time consumption is …

Seismic Reliability Analysis of Structures by an Adaptive Support Vector Regression-Based Metamodel

A Roy, S Chakraborty - Journal of Earthquake Engineering, 2024 - Taylor & Francis
The dual metamodeling approach is usually adopted to tackle the stochastic nature of
earthquakes in seismic reliability analysis relying on the lognormal response assumption …

A frequency-based ground motion clustering approach for data-driven surrogate modeling of bridges

Y Liao, R Zhang, G Wu, H Sun - Journal of Engineering Mechanics, 2023 - ascelibrary.org
Abstract Machine learning–based methods, especially deep learning methods, have
achieved great success in seismic response modeling due to their exceptional performance …

A comparative study of various metamodeling approaches in tunnel reliability analysis

A Thapa, A Roy, S Chakraborty - Probabilistic Engineering Mechanics, 2024 - Elsevier
Various metamodeling approaches are applied in conjunction with Monte Carlo simulation
and or the second moment-based method for reliability analyses of underground tunnels …

Seismic response prediction of RC bridge piers through stacked long short-term memory network

O Yazdanpanah, M Chang, M Park, CY Kim - Structures, 2022 - Elsevier
This paper aims at addressing the prediction of the displacement time histories and
subsequently hysteresis curves of reinforced concrete bridge piers using a real-time hybrid …