Statistical Damage Prognosis for In-Service Civil Structures against Hazards: Formulations and Applications
Publication: Journal of Engineering Mechanics
Volume 142, Issue 3
Abstract
This paper proposes an expectation-maximization (EM) algorithm embedded statistical damage prognosis paradigm for in-service civil structures against natural hazards. Being within the scope of structural health monitoring, damage prognosis examines the future safety performance of existing structures given relevant damage diagnosis results that reveal the current health condition of the structures under investigation. The damage diagnosis results, which constitute a prerequisite for a reasonably accurate damage prognosis, may in reality turn out to be incomplete owing to various on-site or off-site operation issues. Instead of working on measures to help preclude any data missingness event, this study focuses on exploring an innovative approach, namely for the purpose of damage prognosis striving to make the most of the damage diagnosis results that have become incomplete. The proposed EM algorithm embedded damage prognosis paradigm comprises two sets of procedures, i.e., prognosis validation and prognosis implementation, and each set of the procedures takes into account both the time invariant and time variant damage prognoses. The paradigm is first illustrated by using some meticulously constructed generic performance functions and then applied to some typical situations where existing civil structures are subjected to natural hazards.
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Published In
Journal of Engineering Mechanics
Volume 142 • Issue 3 • March 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Nov 15, 2013
Accepted: Apr 27, 2015
Published online: Sep 25, 2015
Discussion open until: Feb 25, 2016
Published in print: Mar 1, 2016
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