Statistical damage prognosis for in-service civil structures against hazards: formulations and applications

Wang, Vincent Z., Pease, Trent, and Robinson, Sean (2016) Statistical damage prognosis for in-service civil structures against hazards: formulations and applications. Journal of Engineering Mechanics, 142 (3).

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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.

Item ID: 44007
Item Type: Article (Research - C1)
ISSN: 1943-7889
Keywords: uncertainty quantification, structural health monitoring, damage prognosis, missing data, EM algorithm, bootstrap, natural hazards, earthquake loads, wind loads, reinforced concrete
Date Deposited: 06 Apr 2016 07:30
FoR Codes: 09 ENGINEERING > 0905 Civil Engineering > 090504 Earthquake Engineering @ 50%
09 ENGINEERING > 0905 Civil Engineering > 090506 Structural Engineering @ 50%
SEO Codes: 87 CONSTRUCTION > 8704 Construction Processes > 870401 Civil Construction Processes @ 50%
97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 50%
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