A Data-driven Building Seismic Response Prediction Framework:
نام عام مواد
[Thesis]
نام نخستين پديدآور
SUN, HAN
عنوان اصلي به قلم نويسنده ديگر
from Simulation and Recordings to Statistical Learning
نام ساير پديدآوران
Wallace, John W.
وضعیت نشر و پخش و غیره
تاریخ نشرو بخش و غیره
2019
یادداشتهای مربوط به پایان نامه ها
کسي که مدرک را اعطا کرده
Wallace, John W.
امتياز متن
2019
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
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.
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )