RISK-BASED LIFE-CYCLE OPTIMAL MANAGEMENT OF INFRASTRUCTURE UNDER MULTI-HAZARDS WITH EMPHASIS ON RESILIENCE AND SUSTAINABILITY

Abstract eng:
The condition and safety of civil infrastructure systems (CIS) around the world are degrading at an alarming rate due to a variety of deteriorating mechanisms, including aging, environmental stressors, man-made hazards (e.g., blasts and fires) and natural hazards (e.g., earthquakes, hurricanes, and scour). Consequently, improving the condition and safety of deteriorating CIS is a key concern worldwide. Life-cycle optimal management is widely recognized as an effective tool for maximizing the cost-effectiveness of implementing intervention actions that improve condition and safety, and extend the service life of deteriorating infrastructure systems. The performance of (CIS) under multi-hazards may be represented by a variety of indicators. Approaches for their life-cycle management involving reliability performance indicators consider uncertainties associated with loads, resistance, and modeling, but are not able to account for the consequences incurred from failure. Risk-based indicators provide the means to combine the probability of structural failure with the consequences associated with this event. Several risk approaches within a generalized life-cycle optimization framework will be presented. Furthermore, methodologies considering resilience and sustainability as performance indicators are discussed. The incorporation of sustainability in the life-cycle performance assessment and management procedures allows for the effective integration of economic, social, and environmental aspects. The approach presented provides optimal multi-objective intervention strategies allowing for risk- and sustainability-informed decisions regarding structures, networks, and interdependent infrastructure systems under multi-hazards during their lifetime. Acknowledgements. The support from the National Science Foundation through grants CMS-0639428 and CMMI-1537926 and the U.S. Office of Naval Research award N00014-16-1-2299 is gratefully acknowledged. The opinions and conclusions presented in this paper are those of the author and do not necessarily reflect the views of the sponsoring organizations.

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