A long short-term memory based deep learning algorithm for seismic response uncertainty quantification
The application of metamodeling technique to overcome computational challenge of Monte
Carlo simulation (MCS) technique for response uncertainty quantification under stochastic …
Carlo simulation (MCS) technique for response uncertainty quantification under stochastic …
Generalized stacked LSTM for the seismic damage evaluation of ductile reinforced concrete buildings
To organize accurate and effective emergency responses after an earthquake, it is vital to
conduct an early and precise assessment of damage to structures. The use of …
conduct an early and precise assessment of damage to structures. The use of …
Unveiling out-of-distribution data for reliable structural damage assessment in earthquake emergency situations
To ensure accurate and effective emergency responses following an earthquake, one must
promptly and accurately assess damage to structures with minimal manual effort. An …
promptly and accurately assess damage to structures with minimal manual effort. An …
Investigation of Degradation Modeling for Aircraft Structures: A Systematic Literature Review
L Jilke, F Raddatz, G Wende - AIAA AVIATION 2023 Forum, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-3550. vid Remaining useful life
prognostics, maintenance planning and prognostics and health management are crucial …
prognostics, maintenance planning and prognostics and health management are crucial …
Long short-term memory-based deep learning algorithm for damage detection of structure
R De, A Kundu, S Chakraborty - … Mechanics, Vol II: Select Proceedings of …, 2022 - Springer
A long short-term memory-based (LSTM) deep learning algorithm is explored for damage
detection of structure using acceleration response time history. The architecture of the LSTM …
detection of structure using acceleration response time history. The architecture of the LSTM …
Physics-informed DeepONet with stiffness-based loss functions for structural response prediction
Finite element modeling is a well-established tool for structural analysis, yet modeling
complex structures often requires extensive pre-processing, significant analysis effort, and …
complex structures often requires extensive pre-processing, significant analysis effort, and …
Rescaled-LSTM for predicting aircraft component replacement under imbalanced dataset constraint
Deep learning approaches are continuously achieving state-of-the-art performance in
aerospace predictive maintenance modelling. However, the data imbalance distribution …
aerospace predictive maintenance modelling. However, the data imbalance distribution …
Constant-amplitude fatigue crack growth sequence regression on an aircraft lap joint using a 1-D convolutional network
MI Mas, MI Fanany, T Devin… - 2017 1st International …, 2017 - ieeexplore.ieee.org
A difficult issue that faces the operators of aging aircraft is to assure the regulators that their
aircraft is structurally sound. From a structural perspective, aircrafts are complex and …
aircraft is structurally sound. From a structural perspective, aircrafts are complex and …
On the usage of hybrid 1-D convolutional network and long-short-term-memory network for constant-amplitude multiple-site fatigue damage prediction on aircraft lap …
MI Mas, MI Fanany, T Devin… - … and Technology (SIET), 2017 - ieeexplore.ieee.org
Multiple site fatigue damage is a problem that affects many operators of aging aircraft. The
methods currently in place for prediction of such damage are conservative, sensitive to noise …
methods currently in place for prediction of such damage are conservative, sensitive to noise …