A3IR-CORE at Purdue University: An Innovative Partnership Between Faculty, Students, and Industry

Economic realities have begun to motivate public higher education institutions to reexamine their roles in the overall educational process and the associated funding mechanisms that are extant. Such reexamination typically includes both the public/private funding mix and the degree to which a workforce-oriented focus should be employed across curricula. Partnerships between academia and industry are a potential answer to the questions thereby raised, and while such partnerships are nothing new, related structural innovations can improve educational and employment outcomes for students. Industry-sponsored institutional research centers can play a major role in facilitating these partnerships. Once such center, the recently-developed Advanced Aviation Analytics Institute for Research (A³IR-CORE), is focused on addressing operational challenges within the aviation industry by actively involving both graduate and undergraduate student researchers working closely with faculty mentors in a highly-collaborative multidisciplinary environment. This article describes the structure and function of the Institute and provides an early glimpse of the positive student educational and employment outcomes that have thus far been achieved

Measurement of Airport Operations Using a Low-Cost Transponder Data Receiver and Collection Unit

Accurate counts of aircraft operations at unmonitored or partially-monitored general aviation airports are important due to their role in the allocation of funds for airport development and improvement. While the Federal Aviation Administration annually invests approximately $1B in small commercial and general aviation airports, fewer than 270 of these 2,950 airports have either full- or part-time air traffic personnel available to register operations counts. Aircraft operations at airports with limited personnel may be counted using temporary acoustic, pneumatic, or video devices, and observations from contract staff. The related sample sizes are inherently small, leading to inaccuracies in the extrapolation of long-term totals. In some cases, the counts may simply be estimated unscientifically by airport managers. Data from aircraft transponders, critical for the safe and efficient management of airspace, may also be used to accurately count airport operations. This data may be collected by a receiver and analyzed with appropriate algorithms. While a majority of the data records (Basic Mode S and Mode C) do not include aircraft positions, a small portion (Extended Mode S) contain position information from which aircraft distances may be directly computed. This dissertation describes a method by which these known distances may be used to calibrate an adaptive digital filter that can be used to estimate distances for the remainder of the aircraft that do not transmit position information. The resulting distance estimates, which exhibit an average error of 0.77 nm per transponder record within 5.0 nm of the receiver, may then be used in conjunction with aircraft altitude and other parameters to identify and register airport operations. Over 16 million data records from three receiver installations at two general aviation airports with collection periods varying from eight to 180 days were used to evaluate the algorithms. The automated operations counts were compared with official air traffic control tower counts obtained from the FAA’s Air Traffic Activity Data System (ATADS) database. A 180-day evaluation found the algorithm provided counts within 2.2% of 52,750 operations; shorter-term comparisons were accurate to within 10% of the FAA counts. The method therefore appears to be an effective and inexpensive means of establishing accurate operations counts at airports with limited personnel

An Analysis of Airline Quality Rating Components Using Bayesian Methods

The Airline Quality Rating, a unique metric that is of interval scale and is comparable across carriers and time periods, is a quantitative evaluation of the quality of U.S. domestic air carriers based on data that is collected and published by the U.S. Bureau of Transportation Statistics. One may gain insight into the relationship of the AQR metric to the carriers to which it is applied by grouping those carriers and examining the effects of the resulting groupings on the four individual factors that comprise the AQR. This study used Bayesian hierarchical modeling techniques to examine the differences between three carrier groupings (legacy, low-cost, and regional) on a longitudinal basis over a period of six years. Based on the results of a Bayesian two-way analysis of variance (BANOVA), results showed significant differences between the mishandled baggage, denied boardings, and customer complaints of the data sets. Thus, sufficient evidence was found to support the premise that different econometric models are needed to broaden stride ins air carrier service quality improvements. Based on the results of the Bayesian two-way analysis of variance, credible differences in on-time arrivals, mishandled baggage, and customer complaints were indicated. These results imply a rejection of the null hypothesis, Ho, for those data sets. There were no credible differences indicated between legacy, regional, and low-cost carriers regarding the denied boarding data set, implying a failure to reject the null hypothesis in that particular case

Recommendations For Improvement Of Collegiate Flight Training Operational Efficiency Through Guided-Inquiry Inductive Learning

Efficiency in higher education has increasingly come under scrutiny as student debt levels continue to increase and the quantification of the value provided to students by colleges remains elusive. Collegiate flight training operations are especially subject to such scrutiny, due to their expense and to continued below-average entry-level salaries in the airline industry. This research examines an inductive learning approach combined with a flipped classroom, whereby aviation management students in a large Midwestern collegiate aviation program analyzed the operational efficiency of their primary flight training operation and recommend potential solutions and means of implementation. Such an approach provides multiple benefits. The resulting improvement in scheduling efficiency results in better use of existing capacity, and can be utilized to allow additional students to matriculate in the program, subsequently reducing student fees for all enrolled students by spreading fixed costs over a wider customer base. In addition, the management students participated in the development and implementation planning of empirical solutions to the problem, thereby addressing a call from industry to incorporate practical projects in the classroom to achieve greater comprehension and retention of subject matter. A number of alternative assessment methods (Frank & Barzilai, 2004), including semi-structured student interviews, surveys, peer evaluations, and analysis of deliverables, were utilized, and these indicated that classroom engagement and subject matter retention was improved by the delivery methods that were employed