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Aerospace Systems Design Laboratory (ASDL)
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ItemA Categorical Model for Airport Capacity Estimation Using Hierarchical Clustering(Georgia Institute of Technology, 2017-12) Cinar, Gokcin ; Jimenez, Hernando ; Mavris, Dimitri N.Motivated by the need for very inexpensive, easily updated, first-order-accurate estimates of airport capacity required in system-wide analyses, we propose a novel approach to generate a predictive categorical model. The underlying hypothesis tested in this work is that for the same weather conditions airports with a similar runway configuration and fleet mix will have similar capacities. Accordingly, if airport categories with known capacity are defined a-priori on the basis of similarity in fleet mix and runway configuration, then a membership function to the set of categories essentially constitutes a predictive model. We test this hypothesis by formulating and implementing such a model in order to examine its feasibility and discuss key practical considerations. Verification demonstrates model fit error within 4% with a categorical training set of 35 major United States airports. Validation against European airports for model representation error is limited by data availability but shown to be in the order of 7-10%. Results suggest that elemental runway configurations are the primary driver for categorical definition, and variations within each category can be associated to fleet mix variations. The implementation of the proposed method to generate other such models with different data sets is encouraged.
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ItemUtilizing Energy Metrics and Clustering Techniques to Identify Anomalous General Aviation Operations(Georgia Institute of Technology, 2017-01) Puranik, Tejas G. ; Jimenez, Hernando ; Mavris, Dimitri N.Among operations in the General Aviation community, one of the most important objectives is to improve safety across all flight regimes. Flight data monitoring or Flight Operations Quality Assurance programs have percolated in the General Aviation sector with the aim of improving safety by analyzing and evaluating flight data. Energy-based metrics provide measurable indications of the energy state of the aircraft and can be viewed as an objective currency to evaluate various safety-critical conditions. The use of data mining techniques for safety analysis, incident examination, and fault detection is gaining traction in the aviation community. In this paper, we have presented a generic methodology for identifying anomalous flight data records from General Aviation operations using energy based metrics and clustering techniques. The sensitivity of this methodology to various key parameters is quantified using different experiments. A demonstration of this methodology on a set of actual flight data records as well as simulated flight data is presented highlighting its future potential.
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ItemGeneral Aviation Approach and Landing Analysis using Flight Data Records(Georgia Institute of Technology, 2016-06) Puranik, Tejas G. ; Harrison, Evan D. ; Min, Sanggyu ; Jimenez, Hernando ; Mavris, Dimitri N.Ensuring a safe and stabilized approach and landing is one of the important objectives in General Aviation applications. This phase is one of the main phases during which accidents occur. A "nominal" or reference trajectory for General Aviation approach and landing operations is critical for flight instruction and retrospective safety assessments reliant on flight data records captured with on-board systems. While this is a more crisply defined area in commercial aircraft operations, it is not so well-defined in General Aviation. The different aspects that need to be considered in defining a nominal trajectory and provide analyses that can be carried out using flight data records are examined. Various ways of defining this nominal or reference approach trajectory are proposed with the eventual aim of using this in conjunction with energy-based methods and metrics to assess and enhance safety in General Aviation aircraft operations.
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ItemEnergy-Based Metrics for General Aviation Flight Data Record Analysis(Georgia Institute of Technology, 2016-06) Puranik, Tejas G. ; Harrison, Evan D. ; Min, Sanggyu ; Jimenez, Hernando ; Mavris, Dimitri N.Energy management and energy state awareness are important concepts in aircraft safety analysis. Many loss-of-control accidents can be attributed to poor energy management. Energy-based metrics provide a measurable quantity of the energy state of the aircraft and can be viewed as an objective currency to evaluate various safety-critical conditions. In this work, we have surveyed key energy-based metrics from various domains and identified the challenges of implementing these metrics for General Aviation operations. Modifications to existing metrics and definition of some new energy metrics are proposed. A methodology is developed that can be used to evaluate and visualize the energy metrics. These energy metrics can then be used to understand and enhance General Aviation aircraft safety using retrospective flight data analysis.