Simulating airline operational responses to environmental constraints

This dissertation describes a model that predicts airline flight network, frequency and fleet changes in response to policy measures that aim to reduce the environmental impact of aviation. Such airline operational responses to policy measures are not considered by existing integrated aviation-environment modelling tools. By not modelling these effects the capability of the air transport system to adjust under changing conditions is neglected, resulting in the forecasting of potentially misleading system and local responses to constraints. The model developed follows the overriding principle of airline strategic decision making, i.e., airline profit maximisation within a competitive environment. It consists of several components describing different aspects of the air transport system, including passenger demand forecasting, flight delay modelling, estimation of airline costs and airfares, and network optimisation. These components are integrated into a framework that allows the relationships between fares, passenger demand, infrastructure capacity constraints, flight delays, flight frequencies, and the flight network to be simulated. Airline competition is modeled by simulating a strategic game between airlines competing for market share, each of which maximizes its own profit. The model is validated by reproducing historical passenger flows and flight frequencies for a network of 22 airports serving 14 of the largest cities in the United States, using 2005 population, per capita income and airport capacities as inputs. The estimated passenger flows and flight frequencies compare well to observed data for the same network (the R2 value comparing flight segment frequencies is 0.62). After validation, the model is applied to simulate traffic growth and carbon dioxide and nitrogen oxide emissions within the same network from 2005 to 2030 under a series of scenarios. These scenarios investigate airline responses to (i) airport capacity constraints, (ii) regional increases in costs in the form of landing fees, and (iii) major reductions in aircraft fuel burn, as would be achieved through the introduction of radically new technology such as a blended wing body aircraft or advanced open rotor engines. The simulation results indicate that, while airport capacity constraints may have significant system-wide effects, they are the result of local airport effects which are much greater. In particular, airport capacity constraints can have a significant impact on flight delays, passenger demand, aircraft operations, and emissions, especially at congested hub airports. If capacity is available at other airports, capacity constraints may also induce changes in the flight network, including changes in the distribution of connecting traffic between hubs and the distribution of true origin-ultimate destination traffic between airports in multi-airport systems. Airport capacity constraints are less likely to induce any significant increase in the size of aircraft operated, however, because of frequency competition effects, which maintain high flight frequencies despite reductions in demand in response to increased flight delays. The simulation results also indicate that, if sufficiently large, regional increases in landing fees may induce significant reductions in aircraft operations by increasing average aircraft size and inducing a shift in connecting traffic away from the region. The simulation results also indicate that the introduction of radically new technology that reduces aircraft fuel burn may have only limited impact on reducing system CO2 emissions, and only in the case where the new technology can be taken up by the majority of the fleet. The reason for this is that the reduced operating costs of the new technology may result in an increase in frequency competition and thus aircraft operations. In conclusion, the modelling of airline operational responses to environmental constraints is important when studying both the system and local effects of environmental policy measures, because it captures the capability of the air transport system to adjust under changing conditions.This work was supported by the Engineering and Physical Sciences Research Council and the Natural Environment Research Council [grant number EP/D060001/1]

Discretion and street-level bureaucracy theory : a case study of local authority social work

This thesis is a critical examination of social work discretion within adult Social Services. The topic is explored through a critical analysis of Lipsky's examination of discretion within street-level bureaucracies. The thesis first outlines Lipsky's analysis of discretion and subsequent research within the street-level bureaucracy perspective, identify the limited analysis of the role of managers and the influence of professionalism on discretion as areas for further consideration. The thesis explores debates about management control and professionalism with regards to social workers' discretion, and how these relate to the continuing relevance of Lipsky's work on discretion. Two key alternative accounts of discretion in contemporary social work are identified: domination managerialism, arguing that managers have achieved control over social work and have extinguished discretion; and the discursive managerialism perspective, which sees managerial control and professional discretion intersecting in different ways in different settings. The thesis examines these arguments in terms of their descriptions of different regimes of discretion, that is: how discretion is characterised; claims about the nature of management control; and the role of professional status. These issues are examined through a study of an older persons team and a mental health team within the same local authority. The study suggests that 'management' is not monolithic, but is an internally differentiated group, and that local managers exercise significant discretion themselves and contribute to practitioner discretion. Furthermore, professionalism as a formal principle, in structuring discretion continues to be significant, but to different degrees in the two different teams. The thesis concludes that the street-level perspective is useful in identifying limitations on managers' ability to control discretion. However) this perspective is also criticised as offering a limited account and neglecting the role of managers and professionalism in explaining the nature of social work discretion in Social Services

Functional programming framework for GRworkbench

The software tool GRworkbench is an ongoing project in visual, numerical General Relativity at The Australian National University. Recently, the numerical differential geometric engine of GRworkbench has been rewritten using functional programming techniques. By allowing functions to be directly represented as program variables in C++ code, the functional framework enables the mathematical formalism of Differential Geometry to be more closely reflected in GRworkbench . The powerful technique of `automatic differentiation' has replaced numerical differentiation of the metric components, resulting in more accurate derivatives and an order-of-magnitude performance increase for operations relying on differentiation

Analyzing Double Delays at Newark Liberty International Airport

When weather or congestion impacts the National Airspace System, multiple different Traffic Management Initiatives can be implemented, sometimes with unintended consequences. One particular inefficiency that is commonly identified is in the interaction between Ground Delay Programs (GDPs) and time based metering of internal departures, or TMA scheduling. Internal departures under TMA scheduling can take large GDP delays, followed by large TMA scheduling delays, because they cannot be easily fitted into the overhead stream. In this paper we examine the causes of these double delays through an analysis of arrival operations at Newark Liberty International Airport (EWR) from June to August 2010. Depending on how the double delay is defined between 0.3 percent and 0.8 percent of arrivals at EWR experienced double delays in this period. However, this represents between 21 percent and 62 percent of all internal departures in GDP and TMA scheduling. A deep dive into the data reveals that two causes of high internal departure scheduling delays are upstream flights making up time between their estimated departure clearance times (EDCTs) and entry into time based metering, which undermines the sequencing and spacing underlying the flight EDCTs, and high demand on TMA, when TMA airborne metering delays are high. Data mining methods (currently) including logistic regression, support vector machines and K-nearest neighbors are used to predict the occurrence of double delays and high internal departure scheduling delays with accuracies up to 0.68. So far, key indicators of double delay and high internal departure scheduling delay are TMA virtual runway queue size, and the degree to which estimated runway demand based on TMA estimated times of arrival has changed relative to the estimated runway demand based on EDCTs. However, more analysis is needed to confirm this

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper

Responses to airport delays : a system study of Newark International Airport

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2002.Includes bibliographical references (p. 119-121).Airport delays are a significant problem in the United States air transportation system. Between 1997 and 2000 the number of flights delayed increased by between 20 and 25% per year, despite only a 3 to 5% increase in enplanements per year. Newark International Airport (EWR), one of New York City's primary airports, is one of the airports in the United States most impacted by delays. Newark had the highest percentage of operations delayed in 1999, and was second only to LaGuardia Airport in 2000. Nearly 85% of delays at Newark are caused by adverse weather impacting the airport. Because of limited capacity and a very full schedule operated at the airport, when adverse weather impacts the airport departure operations are severely delayed. Despite this, unlike the national average, delays at Newark have not increased significantly since 1998. This indicates that the airlines, air traffic control (ATC), and the Port Authority of New York and New Jersey have successfully adapted. On June 29, 2000, a research team from MIT visited Newark Airport to identify the key problems and assess the effectiveness of any adaptations made. Results of this study indicate that airspace capacity limitations downstream of the airport become a primary flow constraint at the airport, and that when these constraints occur they are the source of most surface delays. Responses to the delays at Newark have been both tactical and strategic. Key tactical ATC responses examined include the application of restrictions; re-routing with the help of the National Playbook; the use of decision-aiding tools; improved inter-facility communication; and utilization of runway 11-29. Key strategic ATC responses examined include the formation of the Air Traffic Control System Command Center, and the New York airspace redesign. A number of tactical airline responses to delays were also examined, including cancellation of low priority flights and the transfer of the passengers to ground transportation; pre-sequencing of departures; and improved access to information. Key strategic responses examined include changes to the schedule operated at the airport, and particularly flattening out of the banks operated; a new fleet, which requires less maintenance and has greater dispatch reliability; and improved relations with the FAA and Port Authority of New York and New Jersey. After examination of the problems at the 10 most delayed airports in the United States, the applicability of the key responses identified at Newark to these airports was also examined in detail. Those airports for which the most responses were identified to be applicable were Atlanta, San Francisco, Philadelphia and Dallas/Fort Worth. Those responses identified to be most applicable to other airports were the further extension of the National Playbook to other regions, the use of decision aiding tools, airspace redesign, pre-sequencing of departures, and a decrease in the number of operations at the airport. A policy analysis was completed for each of these responses.by Antony David Evans.S.M

Using Machine-Learning to Dynamically Generate Operationally Acceptable Strategic Reroute Options

The newly developed Trajectory Option Set (TOS), a preference-weighted set of alternative routes submitted by flight operators, is a capability in the U.S. traffic flow management system that enables automated trajectory negotiation between flight operators and Air Navigation Service Providers. The objective of this paper is to describe and demonstrate an approach for automatically generating pre-departure and airborne TOSs that have a high probability of operational acceptance. The approach uses hierarchical clustering of historical route data to identify route candidates. The probability of operational acceptance is then estimated using predictors trained on historical flight plan amendment data using supervised machine learning algorithms, allowing the routes with highest probability of operational acceptance to be selected for the TOS. Features used describe historical route usage, difference in flight time and downstream demand to capacity imbalance. A random forest was found to be the best performing algorithm for learning operational acceptability, with a model accuracy of 0.96. The approach is demonstrated for an historical pre-departure flight from Dallas/Fort Worth International Airport to Newark Liberty International Airport