This thesis addresses the possibility of using a delay-on-ground concept in which flights with less than 1 hour flying time (often referred to as pop-up flights) absorb their arrival sequencing delay at the departure gate by being issued their Arrival Manager (AMAN)-scheduled time as a Required Time of Arrival (RTA) that is inserted into the Flight Management System (FMS). Due to their short duration these flights are currently often inserted into the AMAN sequence shortly before Terminal Manoeuvring Area (TMA) entry and thereby often need to absorb their arrival sequencing delay in the inefficient manner of airborne holding or vectoring close to the arrival airport. The literature review examines current operational procedures of AMANs and Departure Managers (DMANs), the current FMS RTA function and live trials in which the delay-on-ground concept was tested in real operations. A case study airport in Europe that has potential to benefit from the concept is identified. The performance of the delay-on-ground concept for the case study airport is then assessed by performing 180 fast-time Monte Carlo simulation runs. For each run the arrival flow to the case study airport and the departure flows from two medium-sized airports from which the pop-up flights originate are simulated. Each run represents an operational day and variations in departure/arrivals time is put into the timetables to simulate the variation in actual departure/arrival times resulting from operational factors normally encountered in day-to-day operations. An algorithm is written in Matlab to simulate an AMAN-DMAN cooperation in which pop-up flights are locked to the required departure times to meet their RTAs. It is shown that a significant reduction in airborne delay time and fuel consumption can be achieved at the case study airport by using the concept. It is also shown that it is possible to ensure that the pop-up flights depart at the required times to meet their RTAs without negatively affecting the departure sequences.

There is a need for a fuel-optimal required time of arrival (RTA) mode for aircraft flight management systems capable of enabling controlled time of arrival functionality in the presence of wind speed forecast uncertainty. A computationally tractable two-stage stochastic algorithm utilizing a data-driven, location-specific forecast uncertainty model to generate forecast uncertainty scenarios is proposed as a solution. Three years of Aircraft Communications Addressing and Reporting Systems (ACARS) wind speed reports are used in conjunction with corresponding wind speed forecasts from the Rapid Update Cycle (RUC) forecast product to construct an inhomogeneous Markov model quantifying forecast uncertainty characteristics along specific route through the national airspace system. The forecast uncertainty modeling methodology addresses previously unanswered questions regarding the regional uncertainty characteristics of the RUC model, and realizations of the model demonstrate a clear tendency of the RUC product to be positively biased along routes following the normal contours of the jet stream. A two-stage stochastic algorithm is then developed to calculate the fuel optimal stage one cruise speed given a required time of arrival at a destination waypoint and wind forecast uncertainty scenarios generated using the inhomogeneous Markov model. The algorithm utilizes a quadratic approximation of aircraft fuel flow rate as a function of cruising Mach number to quickly search for the fuel-minimum stage one cruise speed while keeping computational footprint small and ensuring RTA adherence. Compared to standard approaches to the problem utilizing large scale linear programming approximations, the algorithm performs significantly better from a computational complexity standpoint, providing solutions in fractional power time while maintaining computational tractability in on-board systems.