Convolutional neural network for identifying effective seismic force at a DRM layer for rapid reconstruction of SH ground motions
We introduce a novel data‐informed convolutional neural network (CNN) approach that
utilizes sparse ground motion measurements to accurately identify effective seismic forces in …
utilizes sparse ground motion measurements to accurately identify effective seismic forces in …
Physics-informed neural networks for parameter estimation in blood flow models
Background: Physics-informed neural networks (PINNs) have emerged as a powerful tool for
solving inverse problems, especially in cases where no complete information about the …
solving inverse problems, especially in cases where no complete information about the …
Level-Set and learn: convolutional neural network for classification of elements to identify an arbitrary number of voids in a 2D solid using elastic waves
We present a new convolutional neural network (CNN)-based element-wise classification
method to detect a random number of voids with arbitrary shapes in a two-dimensional (2D) …
method to detect a random number of voids with arbitrary shapes in a two-dimensional (2D) …
Deep learning application for nonlinear seismic ground response prediction based on centrifuge test and numerical analysis
Ground response analysis under earthquakes is a critical part of earthquake engineering.
Experimental or numerical techniques are commonly applied to implement seismic soil …
Experimental or numerical techniques are commonly applied to implement seismic soil …
A 2D equivalent linear inversion model of bedrock motions in a layered transversely isotropic half-space
P Zhang, J Liang, Z Ba - Engineering Analysis with Boundary Elements, 2024 - Elsevier
Inversion is the process that evaluates input motion on the bedrock from surface motions,
primarily for use as input excitation for site seismic response or soil-structure interaction …
primarily for use as input excitation for site seismic response or soil-structure interaction …
[PDF][PDF] Generalization of the Deep Learning Model for Natural Gas Indication in 2D Seismic Image Based on the Training Dataset and the Operational Hyper …
LFM Sepulveda - 2024 - maxwell.vrac.puc-rio.br
Luis Fernando Marin Sepulveda Generalization of the Deep Learning Model for Natural Gas
Indication in 2D Seismic Image Based on Page 1 Luis Fernando Marin Sepulveda …
Indication in 2D Seismic Image Based on Page 1 Luis Fernando Marin Sepulveda …
Vibration Attenuation Law of Dynamic Compaction in Miscellaneous Fill Site
J ZHU, Y YU, J ZHENG, B DONG, Y WANG… - Available at SSRN … - papers.ssrn.com
Vibrations generated during dynamic compaction impose adverse consequences,
significantly compromising the structural integrity and stability. Quantifying the relative …
significantly compromising the structural integrity and stability. Quantifying the relative …