Kushal Moolchandani

Impact of Development Rates of Future Aircraft Technologies on Fleet-Wide Environmental Emissions

To mitigate the environmental impact of aviation while still allowing for growth in air transportations, various organizations – such as NASA – have set goals for advancing technologies that reduce the impact of aircraft on the environment. Meeting these goals would improve the environmental performance of an individual aircraft; however, the environmental impact of air transportation is a fleet-level effect that depends on the combined operation of all aircraft with their associated technologies. Economic factors, like fuel price, also impact aviation emissions, because economic factors drive air transportation demand and drive airline fleet composition. This paper analyzes the sensitivity of environmental metrics to the entry-into-service (EIS) dates of various potential new aircraft and to the penetration rate of these new aircraft into the fleet. The studies also incorporate three potential fuel price change scenarios. The results suggest insights in two areas. First, the level of (carbon) emissions is sensitive to EIS dates of new technology aircraft only during a short period after the introduction; later EIS dates lead to airlines upgauging their fleet to maximize profit. Second, high fuel price reduces demand, which reduces emissions, especially on short routes where alternative modes of ground transport likely exist.

Assessment of the Effect of Aircraft Technological Advancement on Aviation Environmental Impacts

This paper studies the evolution of fleet-level emi ssions from aviation under different scenarios of aircraft technology availability and f uel price variation. The aim is to assess the efficacy of introducing advanced technology aircraf t as a means to reduce total emissions while still serving increasing passenger travel dem and. Particularly, this paper explores the potential existence of an effect in the aviation in dustry similar to the so-called the Jevons’ Paradox, in which the profit-seeking airline modele d here uses a larger number of more fuelefficient aircraft so that the increasing number of flights overwhelms the fuel efficiency gains of the individual aircraft. Simulation results conf irm that, while advanced technology aircraft would improve the emissions efficiency of the airline fleet, the advance technology alone would not be sufficient to reduce total fleet -wide CO 2 emissions. This finding implies the need for other initiatives (e.g., operations ch anges, alternate fuels, and carbon policies) to provide incentives to airlines to reduce CO 2 emissions.

Modeling Airline Decisions on Route Planning Using Discrete Choice Models

We propose a model for the airlines’ decisions on route planning, i.e., the decision on selecting which route to add and delete, using discrete choice random-utility theory. The central hypothesis is that a discrete choice model can effectively model the airlines’ decisions on route selection , and thereby help model the evolution of the air transportation network. We first model the airlines’ utility function as a linear function of decision variables with interaction effects. The decision of route selection is then modeled using a binary choice model derived from the utility function. The preferences for each variable in the utility function are estimated using historical datasets. Advantages of this approach include the ability to use statistical techniques to quantitatively construct decision models as well as to account for the uncertainty in unobserved attributes of the decision model. The proposed model helps predict the airlines’ decisions on routes addition and deletion which affect the network topology of air transportation and its future evolution. This capability can be beneficial to other stakeholders, such as Federal Aviation Administration, who may need to make their decisions in response to those made by the airlines, but do not have access to the airlines’ true decision models.

Modeling Airlines’ Decisions on City-Pair Route Selection Using Discrete Choice Models

An approach based on the discrete choice random-utility theory is presented to model airlines’ decisions of strategically adding or deleting city-pair routes. The approach consists of methods for i...

Scientific Foundations for Systems Engineering: Challenges and Strategies

There is an increasing realization of the need for fundamental research in the science of systems engineering. The International Council on Systems Engineering vision document calls for theoretical foundations for systems architecting, systems design and systems understanding. During a recent NSF workshop, a number of knowledge areas ranging from mathematics, information sciences, physical sciences, systems science to human and social sciences were identified as possible sources from which the scientific foundation of systems engineering can be enhanced. However, the primary challenge facing the community lies in orchestrating the breadth and diversity of the many knowledge areas into a cohesive foundation. This paper briefly surveys systems science-related efforts across multiple application domains. The specific objectives in this paper are to present a classification of initiatives for developing foundations for systems engineering, and to discuss the challenges, and potential strategies forward, associated with systems science research. The classification is discussed using two case examples — the Internet and the air transportation system. Through these examples, some of the key research challenges and strategies are exemplified.Copyright

Assessing Effects of Aircraft and Fuel Technology Advancement on Select Aviation Environmental Impacts

The ability to simultaneously assess airline operations, economics, and emissions would help evaluate the progress toward reduction of aviation’s environmental impact as outlined in the NASA Environmentally Responsible Aviation program. Furthermore, assessment of aircraft utilization by airlines would guide future policies and investment decisions on technologies most urgently required. This paper describes the development of the Fleet-Level Environmental Evaluation Tool, which is a computational simulation tool developed to assess the impact of new aircraft concepts and technologies on aviation’s impact on environmental emissions and noise. This tool uses an aircraft allocation model that represents the airlines’ profit-seeking operational decisions as a mixed-integer programming problem. The allocation model is embedded in a system-dynamics framework that mimics the economics of airline operations, models their decisions regarding retirement and acquisition of aircraft, and estimates market demand growt...

A Model of Aircraft Retirement and Acquisition Decisions Based On Net Present Value Calculations

This paper discusses a model of airlines’ fleet planning decisions. In this model, aircraft retirement decisions are based on the net present value of potential new versus existing aircraft, and new aircraft acquisition decisions are based on the expected market demand to be satisfied in the future years. The model runs through three scenarios of passenger demand and aircraft technology evolution, and the results obtained show a comparison of effects of airline decision-making on their fleet composition and the environmental impact.

Airline Competition in Duopoly Market and its Impact on Environmental Emissions: A Game Theory Approach

The Fleet-Level Environmental Evaluation Tool (FLEET) is a simulation tool developed to assess the impact of new aviation technologies and policies on fleet-level environmental metrics of CO2 and NOx emissions and noise. Previous work with FLEET simulated the operations of a ‘benevolent monopoly’ airline in the US domestic and US-originating international air transportation network. This paper presents a newly developed capability to capture the more realistic case of airline competition, though still in abstract form via modeling competition between two typical airlines: a legacy carrier and a low-cost carrier. The resulting duopoly model is described and the simulation results are first compared to the prior monopoly model and then explored under various scenarios on fuel price levels.