Resilience is a concept encompassing both the system ability to survive perturbating events which may lead to a disruption of its operations, and the rapidity in restoring system capacity after the disruptive event has occurred. While the concept of resilience has been dealt with from a number of different perspectives and in different contexts, from supply chains to networked utilities to civil infrastructures and building, research about resilience estimation of industrial facilities is lacking. In this paper a quantitative method to assess plant resilience is developed with reference to process plants and disruptive events represented by natural events such as earthquakes. The proposed method is easy to apply and amenable to both deterministic and probabilistic analysis. It provides a direct estimation of capacity loss after the disruptive event, and the time trend of recovery as well as the related economic loss. Therefore, it may provide a decision making support to facility planners and emergency managers in the process industry.
Caputo, A.C., Paolacci, F. (2017). A method to estimate process plants seismic resilience. In American Society of Mechanical Engineers, Pressure Vessels and Piping Division (Publication) PVP (pp.V008T08A023). American Society of Mechanical Engineers (ASME) [10.1115/PVP2017-65464].
A method to estimate process plants seismic resilience
Caputo, Antonio C.
;Paolacci, Fabrizio
2017-01-01
Abstract
Resilience is a concept encompassing both the system ability to survive perturbating events which may lead to a disruption of its operations, and the rapidity in restoring system capacity after the disruptive event has occurred. While the concept of resilience has been dealt with from a number of different perspectives and in different contexts, from supply chains to networked utilities to civil infrastructures and building, research about resilience estimation of industrial facilities is lacking. In this paper a quantitative method to assess plant resilience is developed with reference to process plants and disruptive events represented by natural events such as earthquakes. The proposed method is easy to apply and amenable to both deterministic and probabilistic analysis. It provides a direct estimation of capacity loss after the disruptive event, and the time trend of recovery as well as the related economic loss. Therefore, it may provide a decision making support to facility planners and emergency managers in the process industry.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
