Resilience Modeling for Quantifying Air-Traffic Disruption and Recovery under strong Storm

Abstract

Air traffic can easily be disrupted by various kinds of external disturbances. When it is disrupted, management actions should be taken to bring it back to a normal state. In order to find a desired management action, resilience is a key property which allows us to predict how complex social system would be recovered after disruption. In this paper, disrupted air traffic caused by a severe storm will be modeled from the perspective of resilience engineering. We will construct both static and dynamic models for describing disruption and recovery of air traffic under a strong storm. Then numerical simulations will be done with variety of parameter sets including stochastic terms. The model parameters will be optimized so that the model can describe empirical data. Mathematical properties of our model will also be studied for investigating further possibility of analysis. The results of this paper can be applied to Viability Theory to find an optimal management action. When thinking of optimal management action, practical operations should also be considered since our research is rather theoretically.