Passive Variable Friction Damper for Increased Structural Resilience to Multi-Hazard Excitations

Author(s):  
Austin Downey ◽  
MohammadKazem Sadoughi ◽  
Liang Cao ◽  
Simon Laflamme ◽  
Chao Hu

Structural control systems, including passive, semi-active and active damping systems, are used to increase structural resilience to multi-hazard excitations. While semi-active and active damping systems have been investigated for the mitigation of multi-hazard excitations, their requirement for real-time controllers and power availability limit their usefulness. This work proposes the use of a newly developed passive variable friction device for the mitigation of multi-hazard events. This passive variable friction device, when installed in a structure, is capable of mitigating different hazards from wind and ground motions. In wind events, the device ensures serviceability, while during earthquake events, the device reduces the building’s inter-story drift to maintain strength-based motion requirements. Results show that the passive variable friction device performs better than a traditional friction damper during a seismic event while not compromising any performance during wind events.

1995 ◽  
Vol 85 (1) ◽  
pp. 308-319 ◽  
Author(s):  
Jin Wang ◽  
Ta-Liang Teng

Abstract An artificial neural network-based pattern classification system is applied to seismic event detection. We have designed two types of Artificial Neural Detector (AND) for real-time earthquake detection. Type A artificial neural detector (AND-A) uses the recursive STA/LTA time series as input data, and type B (AND-B) uses moving window spectrograms as input data to detect earthquake signals. The two AND's are trained under supervised learning by using a set of seismic recordings, and then the trained AND's are applied to another set of recordings for testing. Results show that the accuracy of the artificial neural network-based seismic detectors is better than that of the conventional algorithms solely based on the STA/LTA threshold. This is especially true for signals with either low signal-to-noise ratio or spikelike noises.


2019 ◽  
Vol 188 ◽  
pp. 430-439 ◽  
Author(s):  
Austin Downey ◽  
Connor Theisen ◽  
Heather Murphy ◽  
Nicholas Anastasi ◽  
Simon Laflamme

2016 ◽  
Vol 24 (3) ◽  
pp. 159-165
Author(s):  
Ximing Xu ◽  
Maohai Fu ◽  
Zhaoxia Xu ◽  
Zhongyi Chen

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