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Daniel Guggenheim School of Aerospace Engineering
Daniel Guggenheim School of Aerospace Engineering
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ItemA Comprehensive Energy Monitoring Environment for District Energy Grid Systems(Georgia Institute of Technology, 2017-07) Lewe, Jung-Ho ; Duncan, Scott J. ; Song, Kisun ; Oh, Sehwan ; Solano, David ; Yarbasi, Efe Y. ; Ahuja, Jai ; Johnston, Hunter B. ; Mavris, Dimitri N.By conducting active meter monitoring and performance analysis for the buildings and the plants at the main campus of the Georgia Institute of Technology, it is possible for campus facilities managers to achieve significant efficiency improvements. A key challenge, however, is gathering and making sense of the large volumes of utilities data. In response, a comprehensive web-based building and plant energy-monitoring environment is presented that collects data from multiple energy grids. From the gathered data, particular attention is given to heating, cooling, and ventilation to assess building and ultimately campus energy performance through various analytics. First, techniques for data gathering, organization, and filtering are described, followed by several novel metrics and ways of visualizing them via a comparative method. Data filtering and classification strategies have also been implemented into a framework capable of evaluating a fleet of buildings with respect to a data-driven or model-driven baseline. The resulting monitoring system is shown to reduce the number of variables that campus managers of campus utilities and facilities need to track and make it more obvious where energy efficiency opportunities exist across a large fleet of buildings. Implications and future extensions of the monitoring platform are discussed.
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ItemSizing, Integration and Performance Evaluation of Hybrid Electric Propulsion Subsystem Architectures(Georgia Institute of Technology, 2017-06) Cinar, Gokcin ; Mavris, Dimitri N. ; Emeneth, Mathias ; Schneegans, Alexander ; Riediger, Carsten ; Fefermann, Yann ; Isikveren, AskinThis paper presents a methodology for the sizing and synthesis of power generation and distribution (PG&D) subsystems. The PG&D subsystem models developed in a previous work done by the authors were applied within a parallel hybrid electric propulsion architecture using the Dornier 328 as the baseline aircraft. The hybridization took place only during the cruise segment. Analyses were performed in Pacelab SysArc, a system architecture design tool, to assess the impact of different hybrid electric propulsion architectures and changing PG&D subsystem characteristics at aircraft and mission levels. To this end, sensitivity analysis was conducted to reveal the sensitivity to the subsystem level characteristics. Moreover, six different architectures were compared in terms of their mission level performance. These architectures included the PG&D subsystems with current state of the art technology, NASA 15-year technology goals and a more advanced battery technology. Although neither the current state of the art PG&D subsystems nor NASA 15-year technology goals were advanced enough to match the design range requirement of the baseline aircraft, some of the competing architectures met the practical range target while enjoying substantial amount of fuel reductions. Finally, it was observed that in order to reach a break-even point in terms of the design mission range, a battery specific energy of 5 kWh/kg was necessary for a 50% level of hybridization during cruise. In this work the Dornier 328 was used as a testbed, however the methodology can be generalized for all parallel hybrid electric propulsion applications.
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ItemIntegrated Sizing and Multi-objective Optimization of Aircraft and Subsystem Architectures in Early Design(Georgia Institute of Technology, 2017-06) Rajaram, Dushhyanth ; Cai, Yu ; Chakraborty, Imon ; Puranik, Tejas G. ; Mavris, Dimitri N.The aerospace industry's current trend towards novel or More Electric architectures results in some unique challenges for designers due to both a scarcity or absence of historical data and a potentially large combinatorial space of possible architectures. These add to the already existing challenges of attempting to optimize an aircraft design in the presence of multiple possible objective functions while avoiding an overly compartmentalized approach. This paper uses the Integrated Subsystem Sizing and Architecture Assessment Capability to pursue a multi-objective optimization for a Large Twin-aisle Aircraft and a Small Single-aisle Aircraft using the Non-dominated Sorting Genetic Algorithm II with parallel function evaluations. One novelty of the optimization setup is that it explicitly considers the impacts of subsystem architectures in addition to those of traditional aircraft-level design variables. The optimization yielded generations of non-dominated designs in which substantially electrified subsystem architectures were found to predominate. As a first assessment of the impact of epistemic uncertainty on the results obtained, the optimization was re-run with altered sensitivities for the thrust-specific fuel consumption penalties due to shaft-power and bleed air extraction. This analysis demonstrated that the composition of architectures on the Pareto frontier is sensitive to the secondary power extraction penalties, but more so for the Small Single-aisle Aircraft than the Large Twin-aisle Aircraft.
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ItemA Simulation-Based Framework for Structural Loads Assessment during Dynamic Maneuvers(Georgia Institute of Technology, 2017-06) Goron, Gael ; Duca, Ruxandra ; Sarojini, Darshan ; Shah, Somil R. ; Chakraborty, Imon ; Briceno, Simon ; Mavris, Dimitri N.Federal Aviation Regulations pertaining to structural integrity are key drivers in aircraft design and certification, and often involve critical loads occurring during dynamic maneuvers. In the context of increasing costs of testing and the general trend towards parametric design, there is a need for a more thorough consideration of such dynamic load cases earlier in the design process. In this work, a simulation framework is introduced to assess structural requirements stemming from such dynamic load conditions. Relevant aspects of the dynamics of the aircraft, the control system, and the pilot are modeled in order to simulate the maneuver and thereafter obtain inertial and aerodynamic loads on the empennage during the simulated maneuver. The loads are then translated into structural shear forces and bending moments through structural post-processing routines. This approach is demonstrated for the case of a representative business jet during the checked pitch maneuver. The analyses are repeated for three weight conditions and over the flight envelope for the aircraft from which the load cases resulting in the most constraining loads are determined.
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ItemIdentifying Instantaneous Anomalies in General Aviation Operations(Georgia Institute of Technology, 2017-06) Mavris, Dimitri N. ; Puranik, Tejas G.Quantification and improvement of safety is one of the most important objectives among the General Aviation community. In recent years, data mining techniques are emerging as an important enabler in the aviation safety domain with a number of techniques being applied to flight data to identify and isolate anomalous (and potentially unsafe) operations. There are two types of anomalies typically identified - flight-level (where the entire flight exhibits patterns deviating from nominal operations) and instantaneous (where a subset or few instants of the flight deviate significantly from nominal operations). 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 across a heterogeneous fleet of aircraft. In this paper, a novel method of identifying instantaneous anomalies for retrospective safety analysis using energy-based metrics is proposed. Each data record is split by sliding a moving window across the multi-variate series of evaluated energy metrics. A mixture of gaussian models is then used to perform clustering using the values of energy metrics and their variability within each window. The trained models are then used to identify anomalies that may indicate increased levels of risk. The identified anomalies are compared with traditional methods of safety assessment (exceedance detection).
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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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ItemAnomaly Detection in General Aviation Operations Using Energy Metrics and Flight Data Records(Georgia Institute of Technology, 2017) Puranik, Tejas G. ; 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, a generic methodology is presented for identifying anomalous flight data records from General Aviation operations in the approach and landing phase. Energy based metrics, identified in previous work, are used to generate feature vectors for each flight data record. Density-based clustering and one-class classification are then used together for anomaly detection using energy-based metrics. A demonstration of this methodology on a set of actual flight data records from routine operations as well as simulated flight data is presented highlighting its potential for retrospective safety analysis. Anomaly detection using energy metrics, specifically, is a novel application presented here.
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ItemDevelopment of Parametric Power Generation and Distribution Subsystem Models at the Conceptual Aircraft Design Stage(Georgia Institute of Technology, 2017-01) Cinar, Gokcin ; Mavris, Dimitri N. ; Emeneth, Mathias ; Schneegans, Alexander ; Fefermann, YannThe ongoing efforts to reduce aviation related greenhouse gas emissions and fuel burn have led to advancements in power generation and distribution (PG&D) subsystem technology. Due to the absence of historical data, PG&D subsystem models must be created from first-order analysis without compromising crucial information on their characteristics. This paper demonstrates the development of parametric, physics-based subsystem models such as battery, electric motor, power distribution and management system, and propeller speed reduction unit for rapid and low-cost sizing, simulation and analysis at early design stages. A special focus was put on rechargeable battery technology and implementing a dynamic (rather than steady-state) discharge behavior into the propulsion architecture. A methodology to integrate the developed subsystem models was presented. A sample application was also provided to demonstrate the combined capabilities of the models. To this end, the models were applied within a sample parallel hybrid electric architecture using Dornier 328 as a test bed. The subsystem behaviors under varying power requirements were then analyzed. Finally, the importance of having more dimensionality at the subsystem level at early design stages was highlighted by comparing the results of two different architectural choices.