In this study, an explainable seismic response surrogate model, which can be deemed valid from an engineering perspective, was developed. The model employs SincNet convolution to segment features by frequency band and an attention mechanism to …
This study presents a regularized Deep Kernel Learning (DKL) model for reliability analysis with high-dimensional uncertainties. Combining Deep Learning (DL) and Gaussian Process Regression (GPR), the model leverages DL for feature extraction and GPR …
Seismic fragility analysis of structures such as bridges must consider not only the uncertainties in the loads to which the structure is subjected, but also the uncertainties in the physical properties of the structure due to deterioration and other …
System fragility is required especially for the vulnerability assessment of existing bridges that configure transportation network as a structural system. Here, it is essential to consider not only variation of input ground motions but also the …
Real-time simulation of structures and structural members enables intuitive and immediate understanding of displacements and stresses, contributing to efficient decision making in design and maintenance. In this study, real-time simulation of …
The particle method does not require any computational grid and is an effective numerical method for simulating behaviors of the continuum mechanics. However, the computational cost is the issue to apply it to more complex physics or to the Monte …