Abstracts: 2013-2014


U.S. Civil Air Show Crashes, 1993 to 2013: Burden, Fatal Risk Factors, and Evaluation of a Risk Index for Aviation Crashes

Sarah-Blythe Ballard and Victor B. Osorio

This study provides new public health data about U.S. civil air shows. Risk factors for fatalities in civil air show crashes were analyzed. The value of the FIA score in predicting fatal out- comes was evaluated. With the use of the FAA’s General Aviation and Air Taxi Survey and the NTSB’s data, the incidence of civil air show crashes from 1993 to 2013 was calculated. Fatality risk factors for crashes were analyzed by means of regression methods. The FIA index was validated to predict fatal outcomes by using the factors of fire, instrument conditions, and away-from-airport location, and was evaluated through receiver operating characteristic (ROC) curves. The civil air show crash rate was 31 crashes per 1,000 civil air events. Of the 174 civil air show crashes that occurred during the study period, 91 (52%) involved at least one fatality; on average, 1.1 people died per fatal crash. Fatalities were associated with four major risk factors: fire [adjusted odds ratio (AOR) = 7.1, 95% confidence interval (CI) = 2.4 to 20.6, P < .001], pilot error (AOR = 5.2, 95% CI = 1.8 to 14.5, P = .002), aerobatic flight (AOR = 3.6, 95% CI = 1.6 to 8.2, P = .002), and off-airport location (AOR = 3.4, 95% CI = 1.5 to 7.5, P = .003). The area under the FIA score’s ROC curve was 0.71 (95% CI = 0.64 to 0.78). Civil air show crashes were marked by a high risk of fatal outcomes to pilots in aerobatic performances but rare mass casualties. The FIA score was not a valid measurement of fatal risk in civil air show crashes.

Identifying and Analyzing Atypical Flights by Using Supervised and Unsupervised Approaches

Sophine A. Clachar

Effective analysis of flight data is a prominent topic in the aviation industry, with flight data recorders containing vast amounts of information on flight safety violations and maintenance issues. A demand exists for innovative techniques to analyze flight data because predefined threshold criteria, such as exceedances, are often quite rigid and cannot encompass all types of safety issues. Further, the accumulation of flight data presents a big data problem, so that it is infeasible for humans to analyze the data manually in a reasonable time. Statistics show that many accidents and incidents in aviation are recurrent. Therefore, to mitigate potential safety issues, machine-learning algorithms can be trained to identify accident precursors. This research had two purposes. The first was to perform cluster analysis by using Kohonen self-organizing maps (SOMs) to identify unstable approaches that transpired at the Grand Forks, North Dakota, International Airport. The Cessna 172 model aircraft was used, and unsafe practices were identified without specifying predefined thresholds. The second purpose was to employ the analytical techniques asynchronously to address the big data problem. The validated results indicated that SOMs identified hard landings and unsafe low-level maneuvers and that some approaches that were high, fast, and steep would be harder to detect by using traditional flight safety analysis techniques.

Spatiotemporal Dynamics in Identification of Aircraft–Bird Strikes

Tara J. Conkling, James A. Martin, Jerrold L. Belant, and Travis L. DeVault

A primary concern for human-wildlife interactions is the potential impacts resulting from wildlife (primarily birds) collisions with aircraft. The identification of species responsible for collisions with aircraft is necessary so that airport management can develop effective strategies to reduce strikes with those species. Of particular importance in developing such strategies is the identification of regional, seasonal, and temporal patterns in collisions with unidentified bird species that may limit the effectiveness of regional habitat management to reduce bird strikes. The authors analyzed 105,529 U.S. civil aviation strike records from 1990 to 2012 in the FAA’s National Wildlife Strike Database to examine patterns of collisions involving unidentified birds. Factors that affected identification were airport certification class, FAA region, mass of struck species, state species richness (if damage was reported), and interactive effects between the last four factors. Identification varied by region and declined with increasing species richness; this identification was greater for general aviation (GA) airports and the mass of struck species, especially when damage was reported. Species identification might be improved by increasing reporting efforts relative to species richness, especially by GA airport managers and operations staff, who may have a higher propensity of reporting bird strikes, and by collecting more field-based data on avian populations. The results can provide guidance for the development of airport management and personnel training.

Airport Infrastructure Investment: Strategic Interaction or Strategic Allocation?

Jeffrey J. Eloff and Jeffrey P. Cohen

As the FAA forecasts air traffic growth for U.S. carriers to increase (by 90% in revenue passenger miles and by 50% in the number of handled air- craft) over the next 20 years, airports consequently will be subjected to problems associated with substantially increased levels of demand. One component of the solution is expected to come from further investments in improvements to airport infrastructure. Given current fiscal constraints, the inherent network structure of the National Airspace System, and the fact that delays and congestions propagate throughout the system, would it be more efficient for capital investments to be made in an integrated and intelligent fashion—one that serves to maximize the productivity of the entire system—rather than on an airport-by-airport basis? Therefore, the goals of this research were to understand current airport interactions and to provide a framework for quantifying how interactions spread through- out the network. These insights were uncovered by exploiting the network structure of the national airspace system in the framework of spatial econometric modeling. The data necessary to determine these relationships came from multiple sources: the Bureau of Transportation Statistics Schedule T-100 data on origin-destination pairs provided dynamic measures of connectivity, while FAA data on airport investments provided the necessary information to determine infrastructure investment patterns.

Quantifying the Performance of Warm-Mix Asphalt and Reclaimed Asphalt Pavement in Flexible Airfield Pavements

Maria Chiara Guercio and Leslie Myers McCarthy

Warm-mix asphalt (WMA) is a current paving technology that uses various techniques for producing and constructing asphalt at lower temperatures. The benefits associated with WMA range from reduced carbon dioxide emissions to extended paving seasons. The performance and the environmental benefits of WMA can be enhanced by the addition of reclaimed asphalt pavement (RAP) to the aggregate portion of the mix. This technology has been extensively used in the highway sector, but its use in the airfield sector has not been documented fully. Currently, asphalt mixtures used in the surfaces of airfield pavements are designed in accordance with the FAA P-401 specifications. This study quantified the performance of a WMA-RAP mixture compared with the standard FAA P-401. The asphalt mixture performance tester was used to test the mixtures for flow time and load cycles to failure so as to capture the rutting and fatigue cracking potentials of both mixtures. The laboratory data were used as input to the three-dimensional finite element analysis software ABAQUS, and the mechanical responses were deter- mined within the surface layer of the airfield flexible pavement section modeled to represent the section constructed at the FAA National Airport Pavement Test Facility. The Greenhouse Calculator for State Departments of Transportation, a product of NCHRP Project 25-25, was used to assess the environmental impacts of both mixtures. This study’s findings indicate that the laboratory and predicted performance of the WMA-RAP mixture are comparable to the performance of a standard FAA P-401 mixture. The cost and environmental benefits of the WMA-RAP mixture make this type of material a viable alternative to the standard FAA P-401 mixture.

Airfield Pavement Response Caused by Heavy Aircraft Takeoff: Advanced Modeling for Consideration of Wheel Interaction

Jaime A. Hernandez and Imad L. Al-Qadi

The effect of wheel configuration on critical airfield pavement responses during takeoff was calculated, and variables, usually omitted in conventional pavement analysis, were considered. The numerical analysis matrix consisted of two takeoff speeds, two inflation pressures, two pavement structures, and four wheel configurations. One of the pavement structures was built at the National Airport Pavement Test Facility and had been previously described in the literature. The method used in this study advanced current knowledge in two respects. First, the study examined not only the tensile strains at the bottom of the asphalt concrete (AC) layer (fatigue cracking) and vertical strain on top of the subgrade (rutting) but also the transverse surface strain (surface cracking) and vertical shear strains (near-surface cracking and rutting). Second, several assumptions about existing methods were advanced. These assumptions included (a) non- uniform three-dimensional contact stresses instead of uniform one-dimensional vertical stresses over a circular contact area, (b) viscoelastic and nonlinear material characterization for AC and granular material under high stress levels in lieu of a linear elastic model, and (c) load variation with time to reflect takeoff. Trans- verse surface strain and vertical shear strain in the sub- grade were most affected by wheel configuration. In addition, the variables had varying influence on pavement responses and wheel interaction. For instance, takeoff speed affected vertical strain on top of the subgrade but did not affect transverse surface strain. Tire inflation pressure modified wheel interaction for shear strain in the AC but not in the subgrade.

Evaluation of Pavement Preservation and Maintenance Activities at General Aviation Airports in Texas: Practices, Perceived Effectiveness, Costs, and Planning

Evan Humphries and Soon-Jae Lee

General aviation (GA) airports play an important role in the national transportation system by accommodating emergencies and providing for agricultural, recreational, and other operations. GA airports account for almost 90% of the airports in the Texas Airport System Plan. To protect their initial investment in asphalt and concrete pavements, GA airports are expected to perform routine pavement maintenance. For this case study of pavement maintenance practices at GA airports in Texas, GA airport managers were contacted and interviewed about treatments used at their facilities and about the process of having the work done. Respondents were asked to rank the effectiveness of specific maintenance treatments for asphalt and concrete pavements on a Likert-type scale, as well as marking type, retexturing methods, and rubber and contaminant removal methods. Information about the level at which pavement maintenance decisions were made, the process, and the additional data desired (specifically about pavements) was obtained through open-ended questions. The results show that crack sealing and slurry sealing are the two most commonly used maintenance treatments—in a reactive manner. The results also indicate that most GA airport managers rely on the Aviation Division of the Texas Department of Transportation or an engineering firm to manage the airfield pavement and do not take an active approach to implementing routine preventive maintenance. This reliance was the result of two factors: (a) level of knowledge, of both the airport managers and those approving funding, and (b) availability of funding. Opportunities for cooperation and education to address deficiencies exist within the current system.

Airport Traffic and Metropolitan Economies: Determinants of Passenger and Cargo Traffic

Paulos Ashebir Lakew

While controlling for the unique and unobserved characteristics of cities, this paper assesses the impact of urban size, employment, and income on air traffic. Previous studies have established links between the socioeconomic characteristics of cities and the volume of passenger and cargo traffic enplaned at their airports. Using the variations of population, employment, and income across urban areas, researchers have found that passenger enplanements have been proportional to city size and that they have increased with income and service sector employment. However, most earlier work relied on cross-section methods that ignored city-specific differences that may have influenced the drivers of air traffic. This paper is based on a 10-year quarterly panel of city-level economic and traffic measures, from which a city fixed-effects model is estimated. Thus, the results presented here shed light on the within-city effects that population, employment composition, and the average wage have on traffic and provide new insights into the determinants of air travel and goods movement. Controlling for the unobserved features of a metropolitan area, the paper confirms that passenger and cargo enplanements are proportional to population. Service sector employment and higher wages, indicating white-collar jobs, continue to induce both passenger and cargo transport, while a city’s share of employment in manufacturing (blue-collar) jobs mostly affects cargo traffic. Further- more, the fixed-effects results show that passenger enplanements exhibit more sensitivity to the proportion of urban workers providing non-tradable services than to the share of workers in tradable service jobs.

Is Your Flight Really on Time? Analysis of the Timing of Flight Delay Announcements by U.S. Airlines

Richard Penn, Laurie A. Garrow, and Jeffrey P. Newman

The majority of studies on airline delays have been based on databases that contain information only about the final delay outcome associated with a flight; that is, did a flight arrive early or late at the gate and, if so, by how many minutes? This paper uses a database from Flight Stats that contains information on the timing of airline notifications of delays to customers. Specifically, the delay notification strategies of six U.S. airlines are compared, and the timing and accuracy of their delay forecasts are analyzed with data from 2010. Results show that airlines use different delay notification strategies. AirTran and Southwest announce delays more frequently throughout the flight departure process, whereas American Airlines, American Eagle, Delta, and JetBlue announce the majority of their delays in two distinct periods before departure. Results also indicate that “no news is bad news” in the sense that the closer to departure that a delay is first announced, the more likely it is to be a long delay. An assessment of forecasting accuracy reveals that the majority of airlines consistently under forecast delays; the two notable exceptions are JetBlue and AirTran. The timing and accuracy of delay forecasts has important implications for airports, particularly as it relates to their ability to develop contingency plans for irregular operations.