A Data-driven Building Seismic Response Prediction Framework:

منو

" A Data-driven Building Seismic Response Prediction Framework: "
SUN, HAN Wallace, John W.

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	898564
Doc. No	:	TL4b56h24z
Main Entry	:	Wong, Alana
Title & Author	:	A Data-driven Building Seismic Response Prediction Framework:\ SUN, HANWallace, John W.
Date	:	2019
student score	:	2019
Abstract	:	Structural seismic resilience society has been grown rapidly in the past three decades. Extensive probabilistic techniques have been developed to address uncertainties from ground motions and building systems to reduce structural damage, economic loss and social impact of buildings subjected to seismic hazards where seismic structural responses are essential and often are retrieved through Nonlinear Response History Analysis. This process is largely limited by accuracy of model and computational effort. An alternative data-driven framework is proposed to reconstruct structure responses through machine learning techniques from limited available sources which may potentially benefit for “real-time” interpolating monitoring data to enable rapid damage assessment and reducing computational effort for regional seismic hazard assessment. It also provides statistical insight to understand uncertainties of seismic building responses from both structural and earthquake engineering perspective.
Added Entry	:	SUN, HAN
Added Entry	:	UCLA