A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
Monitoring structural damage is extremely important for sustaining and preserving the
service life of civil structures. While successful monitoring provides resolute and staunch …
service life of civil structures. While successful monitoring provides resolute and staunch …
Earthquake risk assessment of building structures
BR Ellingwood - Reliability Engineering & System Safety, 2001 - Elsevier
During the past two decades, probabilistic risk analysis tools have been applied to assess
the performance of new and existing building structural systems. Structural design and …
the performance of new and existing building structural systems. Structural design and …
Assessing the seismic behavior of structures controlled with a novel elastoplastic-tuned mass damper inerter considering the effects of soil-structure interactions
In this paper, an elastoplastic-tuned mass damper inerter (PTMDI) is introduced, and its
practical advantages under soil-structure interaction are investigated. For this purpose, a …
practical advantages under soil-structure interaction are investigated. For this purpose, a …
Ground motion duration effects on nonlinear seismic response
The study presented in this paper addresses the question of which nonlinear demand
measures are sensitive to ground motion duration by statistical analyses of several case …
measures are sensitive to ground motion duration by statistical analyses of several case …
The pan-European Engineering Strong Motion (ESM) flatfile: compilation criteria and data statistics
Abstract The Engineering Strong-Motion (ESM) flatfile is a parametric table which contains
verified and reliable metadata and intensity measures of manually processed waveforms …
verified and reliable metadata and intensity measures of manually processed waveforms …
Deep convolutional generative adversarial networks for the generation of numerous artificial spectrum‐compatible earthquake accelerograms using a limited number …
Deep learning (DL) methodologies have been recently employed to solve various civil and
earthquake engineering problems. Nevertheless, due to the limited number of reliable data …
earthquake engineering problems. Nevertheless, due to the limited number of reliable data …
Effects of near-fault and far-fault ground motions on nonlinear dynamic response and seismic damage of concrete gravity dams
S Zhang, G Wang - Soil Dynamics and Earthquake Engineering, 2013 - Elsevier
As the forward directivity and fling effect characteristics of the near-fault ground motions,
seismic response of structures in the near field of a rupturing fault can be significantly …
seismic response of structures in the near field of a rupturing fault can be significantly …
Vision-oriented machine learning-assisted seismic energy dissipation estimation for damaged RC beam-column connections
After a seismic event, damage quantification is necessary for safety evaluation, collapse
proximity judgment, and measurement of the residual seismic capacity of the joints. Machine …
proximity judgment, and measurement of the residual seismic capacity of the joints. Machine …
Computer-vision and machine-learning-based seismic damage assessment of reinforced concrete structures
Seismic damage assessment of reinforced concrete (RC) structures is a vital issue for post-
earthquake evaluation. Conventional onsite inspection depends greatly on subjective …
earthquake evaluation. Conventional onsite inspection depends greatly on subjective …
PhyMDAN: Physics-informed knowledge transfer between buildings for seismic damage diagnosis through adversarial learning
Automated structural damage diagnosis after earthquakes is important for improving
efficiency of disaster response and city rehabilitation. In conventional data-driven …
efficiency of disaster response and city rehabilitation. In conventional data-driven …