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FAA Joint University Program
On Air Transportation Research

Quarterly Review Meeting

Fall 2013
Thursday, Nov. 14 and Friday, Nov. 15

Massachusetts Institute of Technology
Department of Aeronautics and Astronautics

77 Massachusetts Avenue
Cambridge, MA 02139-4307

Draft Agenda and Abstracts


Thursday, Nov. 14 – room35-520
12:30 - 1:00 PM Sign in
1:00 – 2:30 PM MIT Research Activities - Prof. R. John Hansman

2:30 - 2:45 PM BREAK
2:45 - 5:500 PM MIT Research Activities - Prof. R. John Hansman

6:30 - 9:00 PM Dinner at Local Restaurant

Friday, Nov. 15 - Room 35-520
8:30 AM - 9:00 AM Coffee and pastries
9:00 - 10:30 AM Ohio University Research Activities - Prof. Wouter Pelgrum

10:30 – 12:00 PM Princeton University Research Activities – Prof. Luigi Martinelli

12:00 – 12:30 PM Principal Investigators’ Meeting


Massachusetts Institute of Technology

Implication of†Inconsistencies†between†Flight†Crew†Mental†Model†and†System State†in†Aircraft†System†Failure†Situations
Sathya Silva
Pilot error has been named the leading cause of aircraft accidents for decades; in 2010, 73% of the 1243 fixed wing general aviation accidents had pilot related causes†(AOPA Air Safety Institute, 2011). It is possible to explain some occurrences of pilot error as inconsistencies between the pilot†mental model†and actual state of the system. With the increase in automation technology, it is possible that these inconsistencies could become more prevalent depending on the design of human-automation interface.† In order to investigate the implications of errors in the pilot†mental†model†of aircraft system, analysis will be conducted to determine how prevalent the problem is and determine effective mitigation strategies.†The purpose of this research is to improve the pilotís ability to manage aircraft failures, the effects of which could resonate throughout worldwide aviation safety.
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Examining Potential Growth Areas in the Automation and Control of Small UAVs
Matthew Rabe
This presentation will outline potential areas for improving the effectiveness of small UAVs. Specifically how can we reduce the operational workload to enable 1:1 (human : machine) control, and also reduce the training burden necessary to effectively employ these systems. For effective use of a US Army small UAV, two operators each with months of training experience are required. This is a heavy cost for relatively static tasks and a system that already includes a good deal of automation. How can we optimize this system through an improved operator interface and tradeoffs between manual and autonomous tasks?
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The Development and Performance of a Flexible, Scalable Airframe Construction System for UAVs
Tony Tao
The competitive economics and ever-complicating requirements of aircraft manufacturing have, over the years, created a design landscape that heavily focuses on optimality and high performance. Practically, however, this strategy of producing highly-optimized, high-complexity aircraft has resulted in unsustainable cost escalation in both the aircraft design cycle and in cost-per-unit manufacturing. To address this problem, a new design and manufacturing architecture was devised and tested. The architecture was designed to produce aircraft suitable to three different missions with different size, speed, and operational requirements, from a large endurance-focused sensing mission to a small backpack-able UAV. The architecture is designed for UAVs, but is scalable to larger-scale manufacturing. The architecture is based on scalable molding, variable layup schedules, COTS components for structural members, and a flexible structural system. Three aircraft were manufactured, flight-tested, and their flight performance evaluated to determine the feasibility of the flexible architecture and the system cost accrued by the flexibility.
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Evaluating the Benefits and Operational Feasibility of Delayed Deceleration Approaches (DDA)
Tamas Kolos-Lakatos
Delayed Deceleration Approaches (DDA) can reduce fuel burn and emissions by keeping the aircraft in a clean aerodynamic configuration for as long as possible during approach. This requires maintaining a higher airspeed and delaying flap deployment compared to standard approaches. Previous studies estimated a 30-40% fuel burn saving potential based on operational flight data. Although DDA can provide significant benefits, there are also barriers to implementation at some locations. This study aims to identify DDA opportunities with high cost saving potential and to explore the implementation of DDA into current and future operational concepts.
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Airline Network Fuel Burn Reduction using Cruise Altitude Optimization
Luke Jensen
Rising oil prices have caused fuel to become an increasingly important component of airline operating costs. Certain operational adjustments present opportunities for short-term cost relief. Cruise phase operations constitute the majority of airliner flight time, compounding even incremental reductions in fuel burn rate to provide substantial cost benefit when applied on a network scale.  While the advantage of reducing lateral track distance is well-established, airspace constraints increase the complexity of implementation for this type of optimization. Another possible improvement involves adjustment of speed and/or altitude to reach optimal cruise conditions given a fixed lateral track. This presentation aims to quantify the benefits pool for optimization of cruise altitude in United States domestic operations. A simulation has been developed that combines historical radar tracks, weather data, and aircraft performance models along with weight-estimation heuristics to calculate fuel burn on a flight-specific basis. This analysis procedure is used for a system-wide analysis of cruise efficiency in current operations and to quantify the impact of cruise altitude optimization.
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Models of Multi-agent Distributed Cognition in Air Traffic Control
Aleksandra Stankovic
Effective real-time decision-making in air traffic control depends on the cooperation of several agents, each with different “mental model” representations of the system’s state. Previous research has sought to elucidate the mental representations used by air traffic controllers by examining strategies for the reduction of cognitive complexity through structure-based abstraction (Histon, 2008). However, this work did not address the affect that interactions between actors in the system, including pilots and other controllers, may have on these mental representations, and so a more comprehensive model that can accommodate for multiple agents and the dynamics between them is necessary. This project aims to address this need by building upon the existing understandings to create a novel, empirically testable conceptual framework of information processing in a multi-agent air traffic control system. The observational basis for this theoretical model will be discussed, and possible research projects to validate this framework will be proposed for discussion.
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Ohio University

UAS in the NAS: A System Safety Assessment
Jessica Belzer
With the recent approval of two UAS for civilian use in the National Airspace, comes the reality of the need for integration. Manned and unmanned aircraft will now share the same volumes of airspace (beginning with Class G), for which safety conditions must be upheld. Under manned aircraft operations, certain implicit assumptions exist that must be made explicit and translatable into the unmanned aircraft context. A safety assessment of failure modes and recovery strategies allows for identification of assumptions, and areas of weakness in accommodating a remotely piloted aircraft operating out of line of sight.
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Impact of Ground Multipath on Terrestrial Communication and Navigation
Kuangmin Li & Adam Naab-Levy
UHF radio links between terrestrial stations and airborne targets are challenged by, among others, terrain obstruction and ground multipath. This severely impacts the effective range of ground-to-air communication with, for example, UAS and the performance of terrestrial radio navigation solutions. This presentation shows recently-collected flight-test data with severe ground multipath, qualitative modeling techniques that explain the observed phenomena, and signal processing techniques that enable the deconstruction of the received signal into the direct and multipath components to allow for detailed propagation analysis. Furthermore, various mitigation strategies are discussed that limit the impact of ground multipath on communication and navigation performance. 
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Princeton University

Aerodynamic models for flight in upset conditions
Mark Lohry
The Common Research Model, an aircraft geometry representative of a modern airliner, is used to study aerodynamic behavior at high angle of attack and during a range of unsteady maneuvers. The lift and moments on the aircraft differ strongly from steady flight conditions based on the rate and amplitude of the maneuvers. The aerodynamic effects of these maneuvers are then reduced to simplified first-order models based on deviation from steady state behavior. These models give close agreement with the computationally-expensive unsteady CFD data, allowing for fast and accurate prediction of aerodynamic loads during maneuvers.
» download presentation

Uncertainty quantification for wing icing using polynomial chaos expansions
Anthony DeGennaro
The formation and accretion of ice on the leading edge of a wing can be detrimental to airplane performance. Complicating this reality is the fact that even a small amount of uncertainty in the shape of the accreted ice may result in a large amount of uncertainty in aerodynamic performance metrics (e.g., stall angle of attack). In this talk, we first present a brief survey of the literature concerning the physics of wing icing, with the intention of giving a certain amount of intuition for the physical process. Next, we focus on using the techniques of Polynomial Chaos Expansions (PCE) to analyze wing icing uncertainty. The first application involves using PCE to quantify icing uncertainty much more quickly than traditional methods (e.g., Monte Carlo). The second application involves using Bayesian inference as a means to predict the ice shape using only a series of indirect, noisy measurements.



For additional information, please contact:
Sally Chapman-
email-sallyc@mit.edu
Phone (617) 253-4926 • Fax (617) 253-4196


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comments and questions to sallyc "at" mit.edu