A discrete-event simulation tool for airport deicing activities: Dallas-Fort Worth International Airport

Abstract

Aircraft deicing/anti-icing fluids (ADFs) are applied to remove and prevent icing on aircraft during taxi and takeoff. The Dallas-Fort Worth (DFW) International Airport uses deicing pads for deicing activities that collect and contain the spent deicing fluids for proper treatment or disposal. Local waterways receive ADF as “drip and shear” during the aircraft taxi on the runway and then takeoff. The glycol-based ADF serves as a nutrient for bacteria that grow exponentially, deplete dissolved oxygen (DO) from receiving waterways, and subsequently kill aquatic life. In this paper, we present a data-driven discrete-event simulation modeling process developed in collaboration with DFW Airport to assess aircraft assignment strategies to deicing pad locations by monitoring impact on DO. Our process consists of the following phases: (1) Data Collection, (2) Probability Distribution Modeling, and (3) State Transition Modeling. Both Phases (2) and (3) utilized data mining approaches, including treed regression and variable selection via false discovery rate. Detailed implementation of these phases is described for the DFW Airport case study, and the DFW Airport deicing activities simulation tool framework is presented. The actual data and simulation results were compared in terms of the DO levels in airport receiving waterways to verify the model validity after implementing the proposed model for DFW. Thus, the proposed model can be implemented by airports to control and minimize the adverse environmental effects resulting from deicing activities by optimizing the aircraft assignment to the pad locations.

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