Recent work by researchers from the University of Buffalo has shown the value of continuing to preserve and provide access to legacy data from NEES through the DesignSafe Data Depot. Seyed Omid Sajedi and Xiao Liang (2019) repurposed shake table experimental data from “Seismic Performance Assessment and Retrofit of Non-Ductile RC Frames with Infill Walls” (Shing et. al. 2007) to evaluate the effectiveness of a structural health monitoring framework they developed. This framework identifies the existence, probable location, and severity of damage in a structure following an earthquake, and has the potential to provide information about building damage accurately, dependably, and quickly for the affected communities. The researchers found that reusing the data was important to inform their own understanding of accurately simulating real signals, and to develop benchmarks to evaluate structural health with ML/AI models. They found a new interest and want to continue research in vibration-based structural health monitoring.
Sajedi, S.O. and Liang, X. (2019) “A Data-Driven Framework for Near Real-Time and Robust Damage Diagnosis of Building Structures.” Structural Control and Health Monitoring, 27(3), e2488, https://doi.org/10.1002/stc.2488.
Shing et al. 2007 “Seismic Performance Assessment and Retrofit of Non-Ductile RC Frames with Infill Walls” www.designsafe-ci.org/data/browser/public/nees.public/NEES-2007-0422.groups
Structural Health Monitoring Framework
Predicting Wind Pressure Coefficients
Integrated seismic response predictions
Hysteretic finite element model of structural beams
Synergic use of Sentinel-1 and Sentinel-2 data for automatic detection of earthquake-triggered landscape changes
Seismic Response of Cut and Cover Tunnels
Development and validation of a field wind engineering instrument to understand thunderstorm wind loading on structures
Wind Effects on Elevated Buildings
Observed Hurricane Damage to Manufactured Homes
Statistical models for shear wave velocity profiles
Basin Effects and Limitations of 1D Site Response Analysis from 2D Numerical Models of the Thorndon Basin
Quantitative modeling of residential building disaster recovery and effects of pre- and post-event policies