Prognosis and life-cycle assessment based on SHM information
D.M. Frangopol, Lehigh University, USA
S. Kim, Korea Hydro & Nuclear Power Co., Ltd, Republic of Korea
Abstract:
Efficient prognosis based on structural health monitoring (SHM) information can improve the accuracy associated with structural performance assessment and prediction, and lead to more rational life-cycle management of civil infrastructure systems. This chapter deals with the statistical and probabilistic aspects for efficient prognosis using SHM data. The concepts of the statistics of extremes and decision analysis are employed for cost-effective monitoring planning considering availability of monitoring data and performance prediction error. In order to quantify this ...
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