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NASA researchers are developing surface optimization algorithms and a concept of operations for an airport surface traffic management tool called Spot And Runway Departure Advisor (SARDA). As part of this research, the SARDA scheduling algorithms have been adapted to work at several capacity-constrained airports. Adapting the SARDA scheduling algorithms to airports with dissimilar geometries and operational characteristics requires a careful study of the trade-offs between competing optimization objectives and conflicting constraints. This paper presents three trade-off studies, which were performed using a fast-time simulation of the Charlotte Douglas International airport (CLT). The first study explores a trade-off between minimizing system-wide delay and allocating delay equitably among flights. The equitable delay allocation objective was achieved through a simple scheduler formulation modification. The second study focuses on a tradeoff between minimizing system-wide delay and employing an aggressive gate holding strategy. The scheduler’s gate holding strategy was managed by adding a new departure queue duration scheduling parameter to control how long departures are allowed to wait in the runway queue. The third study explores the effectiveness of controlling how aircraft merge together in the ramp area in order to achieve a departure sequence which maximizes throughput. This study was motivated by CLT’s distinctive airport geometry, which forces departures to merge together in the ramp area to form departure sequences prior to reaching the runway. The paper describes and summarizes the results of these three studies.

Inefficient surface traffic management may lead to congested taxiways, long departure queues, and excess delay in the air transportation system. To address this problem, NASA researchers have developed optimization algorithms and a concept of operations for an airport surface traffic management tool called the Spot and Runway Departure Advisor (SARDA). Past SARDA research efforts have been focused on the Dallas/Fort Worth International airport. This paper describes the development of SARDA-like schedulers for managing the traffic at an operationally dissimilar airport―Charlotte Douglas International airport, and presents the results of a fast-time simulation-based benefits assessment. Fasttime simulations were conducted to test the benefits of optimized scheduling over a baseline model of current-day operations. In the fast-time simulations, it was observed that optimization schedulers reduced movement area delays by up to 3.1 minutes per departure on average, as compared to the baseline simulation. The movement area delay savings translated to shorter movement area taxi-out times and an average reduction in fuel burn and emissions of approximately 24% per departure. The overall trend observed in the total delay (gate delay + ramp delay + movement area delay) comparison indicated the optimization schedulers were not able to reduce total delay, and runway throughput comparisons suggested the optimization schedulers had little to no effect on throughput.

NASA Ames Research Center is developing a concept for managing flight operations on airport surfaces. The goal of the concept, named the Spot and Runway Departure Advisor (SARDA), is to reduce delays, emissions, noise, and fuel consumption. In 2010, human-inthe-loop simulations of the SARDA concept were conducted. Results showed that for the 2008 heavy traffic scenario SARDA reduced departure delays and fuel consumption, while imposing little impact on perceived controller workload. The 2008 normal traffic scenario did not show measurable benefits. The human-in-the-loop simulations analyzed only two traffic scenarios and were costly. To efficiently expand the research of SARDA so that it included analysis of more traffic scenarios, adaptation to more airports, and investigation of changes to the concept, a fast-time simulation capability was needed. This paper documents the first attempt at fast-time simulation analysis of the SARDA concept. A fast-time simulation of traffic at Dallas/Fort Worth International Airport being autonomously managed by a delay-optimal runway scheduler was conducted. Although the simulation was meant to analyze the benefits of the SARDA concept, there were differences between how traffic was managed in the fast-time simulation and the human-in-the-loop simulations. The differences were due to difficulties adapting the delay-optimal scheduler from the human-inthe-loop simulations to the fast-time simulation and lack of capabilities of the airport operations model. The main differences were that the human-in-the-loop simulations included runway crossings in the optimal departure schedules, while the fast-time simulation did not, and the human-in-the-loop simulations controlled flights at the spot, while the fasttime simulation controlled flights at the gate. Results of the delay-optimal fast-time simulation showed benefits for the 2008 normal traffic schedule. It produced 8% less average taxi time and 40% fewer stops than a simulation controlled by a first-come-firstserved scheduler. However, the delay-optimal simulation had the same average delays as the first-come-first-served simulation. In terms of equity of flight delays, the worst delayed flight in the delay-optimal simulation had one and a half minutes more delay than the worst delayed flight in the first-come-first-served simulation.

The ability to keep flights away from weather hazards while maintaining aircraft-to- aircraft separation is critically important. The Advanced Airspace Concept is an automation concept that implements a ground-based strategic conflict resolution algorithm for management of aircraft separation. The impact of dynamic and uncertain weather avoidance on this concept is investigated. A strategic weather rerouting system is integrated with the Advanced Airspace Concept, which also provides a tactical weather avoidance algorithm, in a fast time simulation of the Air Transportation System. Strategic weather rerouting is used to plan routes around weather in the 20 minute to two-hour time horizon. To address forecast uncertainty, flight routes are revised at 15 minute intervals. Tactical weather avoidance is used for short term trajectory adjustments (30 minute planning horizon) that are updated every minute to address any weather conflicts (instances where aircraft are predicted to pass through weather cells) that are left unresolved by strategic weather rerouting. The fast time simulation is used to assess the impact of tactical weather avoidance on the performance of automated conflict resolution as well as the impact of strategic weather rerouting on both conflict resolution and tactical weather avoidance. The results demonstrate that both tactical weather avoidance and strategic weather rerouting increase the algorithm complexity required to find aircraft conflict resolutions. Results also demonstrate that tactical weather avoidance is prone to higher airborne delay than strategic weather rerouting. Adding strategic weather rerouting to tactical weather avoidance reduces total airborne delays for the reported scenario by 18% and reduces the number of remaining weather violations by 13%. Finally, two features are identified that have proven important for strategic weather rerouting to realize these benefits; namely, the ability to revise reroutes and the use of maneuvers that start far ahead of encountering a weather cell when rerouting around weather.

Closed-loop air traffic flow management algorithms based on the predictive modeling and strategic planning capabilities of a medium-fidelity air traffic simulation software are described. The methodology extracts the state and intent of every the aircraft in the airspace, propagates the trajectories in the air traffic simulation over a specified timehorizon according to one or more traffic flow management modes, and returns the performance metrics to be used in decision making. The approach has a human-in-the-loop mode and a fully automatic flow control mode of operation. In the human-in-the-loop mode, the air traffic simulation software is used to create traffic flow control options for the user who then selects the control actions to be implemented. In the automatic flow control mode, the user chooses the flow control objectives, and an iterative optimization scheme performs the decision making process. Selected flow control decisions are then used to modify the aircraft flight plans. Traffic flow modes currently implemented include Ground Stop and Ground Delay Programs, Miles-in-Trail Restrictions, Playbook Routing, Coded Departure Routes and Re-routing around Flow Constrained Areas. Performance of the model-based traffic flow management algorithms are demonstrated in a high fidelity air traffic simulation for several flow control scenarios.

ठA study analyzing the economic and safety impacts of different flight routing methods in the National Airspace System is presented. It compares filed flight routes, wind-optimal routes, and great-circle routes. Routing differences are measured by flight time, fuel burn, sector count, and number of conflicts. Wind-optimal routes exhibit on average approximately one percent less flight time and fuel burn than filed flight routes. In addition, they produce an average of 13 less conflicts in Class A airspace (18,000 feet and above). All three routing methods are qualitatively equivalent in terms of sector count distribution. These results agree with earlier studies, which investigated some combinations of these types of routes and metrics. The contribution of this paper is that it consistently compares the three routing methods across the United States using the four metrics.

A new approach for modeling airport surfaces and terminal airspace, collectively referre d to as terminal areas, and traffic movement is presented. The approach supports description of the geometry of gates, taxiways, and arrival and departure routes with multiple levels of fidelity. Each terminal area model consists of a set of nodes and link s that the user connects to form a network. Nodes model gates, taxi intersections, runway thresholds, metering fixes, and other points of interest. Links model taxiways, departure and arrival routes, and aircraft transit from one node to the next. In addit ion to modeling the geometry of terminal areas, the approach supports evaluation of alternative concepts for managing terminal area traffic. Models of these concepts are decoupled, via an interface, from those of terminal areas and traffic movement. The in terface contains a set of generic functions that can be used by models of any air traffic management concept to monitor and to control aircraft passing through terminal areas.

The Airspace Concept Evaluation System (ACES) is a non-real-time, computer simulation of local, regional and national aircraft operations from gate departure to gate arrival. The overarching objective is to provide a flexible National Airspace System (NAS) simulation and modeling environment that can assess the impact of new NAS tools, concepts, and architectures, including those that represent a significant departure from the existing NAS operational paradigm. Two of the major development goals of ACES are the ability to configure simulations that target specific analysis needs and the ability to model the interactions of the numerous command and control entities that are part of current NAS operations and in future operational concepts. ACES development has been ongoing for several years, with the first version of ACES, Build 1, being delivered in March 2003. The most recent version of ACES, Build 4, was released in December 2005. This paper serves as overview to the features and capabilities of ACES Build 4 and the ways it differs from previous versions. A number of tools for preparing ACES scenarios and analyzing ACES outputs are also described to give potential users an understanding of how ACES can be used.

This paper investigates the effect on the National Airspace System of reducing air traffc controller workload by automating conflict detection and resolution. The Airspace Concept Evaluation System is used to perform simulations of the Cleveland Center with conventional and with automated conflict detection and resolution concepts. Results show that the automated conflict detection and resolution concept significantly decreases growth of delay as traffic demand is increased in en-route airspace.

Geometry, aero/aerothermal, trajectory, and thermal protection selection and sizing tools are linked together in a collaborative engineering environment to form a multidisciplinary analysis model of a reusable launch vehicle performing atmospheric entry. This entry model can determine the effects of vehicle shape and trajectory on the aerothermal environment that must be endured by the thermal protection system. The aerothermal environment in turn determines the size and weight of the thermal protection system required by the vehicle. The importance of interdisciplinary coupling on the design of the vehicle thermal protection system is demonstrated for a wing-body vehicle. Results of a parametric study of the influence of wing thickness on maximum cross-range and thermal protection weight are reported. Difficulties encountered with trajectory optimization are discussed.

This paper develops a near-optimal guidance law for generating minimum fuel, time, or cost fixed-range trajectories for supersonic transport aircraft. The approach uses a choice of new state variables along with singular perturbation techniques to time-scale decouple the dynamic equations into multiple equations of single order (second order for the fast dynamics). Application of the maximum principle to each of the decoupled equations, as opposed to application to the original coupled equations, avoids the two point boundary value problem and transforms the problem from one of a functional optimization to one of multiple function optimizations. It is shown that such an approach produces well known aircraft performance results such as minimizing the Brequet factor for minimum fuel consumption and the energy climb path. Furthermore, the new state variables produce a consistent calculation of flight path angle along the trajectory, eliminating one of the deficiencies in the traditional energy state approximation. In addition, jumps in the energy climb path are smoothed out by integration of the original dynamic equations at constant load factor. Numerical results performed for a supersonic transport design show that a pushover dive followed by a pullout at nominal load factors are sufficient maneuvers to smooth the jump.

Optimal re-entry trajectories are generated for reusable launch vehicles which minimize: (i) the heat absorbed at the vehicle surface, (ii) the lower surface temperature, and (iii) the heat absorbed by the internal structure. The approach uses the energy state approximation technique and a finite control volume heat transfer code coupled to a flight path integration code. These trajectories are compared to the optimal re-entry trajectory minimizing the integrated convective heat rate to determine which trajectory produces the minimum internal structural temperatures for a given thermal protection system. Three different thermal protection systems are considered: tile, blanket, and metallic.