Mavris, Dimitri N.

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Now showing 1 - 10 of 12
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    Sensitivity Analysis of the Overwing Nacelle Design Space
    (Georgia Institute of Technology, 2022-06-09) Mavris, Dimitri N. ; Ahuja, Jai ; Renganathan, S. Ashwin
    The overwing nacelle (OWN) concept refers to aircraft designs where the engine is installed above the wing. The OWN configuration offers several advantages over conventional underwing nacelle (UWN) vehicles, which include improved fuel burn and propulsive efficiencies due to the feasibility of ultra high bypass ratio turbofans, and reduced noise. However, a non-optimal OWN design can result in large transonic drag penalties that can potentially outweigh the aforementioned benefits. We study the OWN design problem from an aerodynamics and propulsion perspective, using the NASA common research model, a notional 90,000 pound thrust class turbofan model, and Reynolds–Averaged Navier-Stokes simulations. We first quantify the sensitivity of drag, lift, and pressure recovery to variations in engine location and power setting, and identify trends. Then, we perform aerodynamic design optimization of the wing and nacelle to determine OWN performance improvement from outer mold line refinement at a favorable engine installation location. A 20% reduction in drag is achieved for the optimized OWN configuration, highlighting the sensitivity of OWN aerodynamics to airframe contours. However, compared to the UWN baseline, the optimized OWN drag is 5% higher at the same lift and worsens significantly at higher lift.
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    Conceptual Design of Boundary Layer Ingesting Aircraft Capturing Aero-Propulsive Coupling
    (Georgia Institute of Technology, 2022-03-01) Ahuja, Jai ; Mavris, Dimitri N.
    The impacts of boundary layer ingestion on aircraft performance can be modeled using either a decoupled or a coupled approach. Several studies in literature have adopted the former, while some have shown differences between the two approaches for the performance analysis and design refinement of a sized aircraft. This study quantifies the consequences of ignoring aero-propulsive coupling at the aircraft sizing stage of conceptual design. To do so, a parametric and coupled aero-propulsive design methodology is used that leverages surrogate modeling to minimize the expense of computational fluid dynamics in generating estimates of the boundary layer ingestion performance impacts. The method is applied to the design and analysis of two aircraft in the 150 passenger class, with different engine locations. Discrepancies in block fuel burn estimates, as large as 2.15%, were found to occur by ignoring aero-propulsive interactions.
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    Modeling Framework for Identification and Analysis of Key Metrics for Trajectory Energy Management of Electric Aircraft
    (Georgia Institute of Technology, 2021-08) Beedie, Seumas M. ; Harris, Caleb ; Verberne, Johannes ; Justin, Cedric Y. ; Mavris, Dimitri N.
    To prepare for the upcoming entry into service of electric and hybrid-electric aircraft, regulators may have to update or develop new regulations and standards to ensure safe operations of these new vehicles. To ensure public acceptance, these vehicles need to demonstrate an equivalent level of safety consistent with existing regulations. However, the ability to fly in different modes (forward flight, vertical flight) and the different powertrain elements may require significant changes to regulations to ensure that an insightful representation of the usable energy is provided to flight crews. This requires an understanding of the major operational differences between conventional and electric aircraft, and how these differences impact the trajectories a vehicle can fly. For instance, there is no simple analog to fuel gauges for measuring the extractable energy available on board electric aircraft, as energy related metrics can vary with a range of variables, such as component temperatures, battery health, and environmental conditions. It is thus more complex for flight crews to gauge in real-time how much usable energy is available and to figure out which trajectories are feasible with respect to both energy and power. To assess the feasibility of trajectories and quantify the adequacy of novel energy tracking metrics and methodologies, a trajectory energy management simulation environment is implemented allowing the simulation of various energy metrics across a range of vehicles and missions. This allows decision makers and regulators to assess the importance of these metrics for safe operation across a wide variety of missions. The impact of ambient air temperature, battery state of health, and initial battery, motor, and inverter temperatures are assessed for a typical flight mission. It is concluded that state of health, ambient temperature, and initial battery temperature all had significant impacts on the final state of charge and amount of extractable energy. Additionally, at high ambient temperatures and in aggressive climbs, motor temperature limits and inverter temperature limits can sometimes be reached, further complicating the assessment of what can be done with the amount of energy stored on board. Proper management of these constraints is therefore crucial for optimizing trajectories with respect to energy metrics. Future work is proposed regarding further expansion of the framework simulating aircraft with vertical takeoff and landing capability, and flight-dynamics algorithms that will enable simulation of optimal energy mission profiles.
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    Aircraft Performance Model Calibration and Validation for General Aviation Safety Analysis
    (Georgia Institute of Technology, 2020-03) Puranik, Tejas G. ; Harrison, Evan D. ; Chakraborty, Imon ; Mavris, Dimitri N.
    Performance models facilitate a wide range of safety analyses in aviation. In an ideal scenario, the performance models would show inherently good agreement with the true performance of the aircraft. However, in reality, this is rarely the case: either owing to underlying simplifications or due to the limited fidelity of applicable tools or data. In such cases, calibration is required to fine-tune the behavior of the performance models. For point-mass steady-state performance models, challenges arise due to the fact that there is no obvious, unique metric or flight condition at which to assess the accuracy of the model predictions, as well as because a large number of model parameters may potentially influence model accuracy. This work presents a two-level approach to aircraft performance model calibration. The first level consists of using manufacturer-developed performance manuals for calibration, whereas the second level provides additional refinement when flight data are available. The performance models considered in this work consist of aerodynamic and propulsion models (performance curves) that are capable of predicting the non-dimensional lift, drag, thrust, and torque at any given point in time. The framework is demonstrated on two representative general aviation aircraft. The demonstrated approach results in models that can predict critical energy-based safety metrics with improved accuracy for use in retrospective safety analyses.
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    Identification of Instantaneous Anomalies in General Aviation Operations using Energy Metrics
    (Georgia Institute of Technology, 2019-12) Puranik, Tejas G. ; Mavris, Dimitri N.
    Quantification and improvement of safety is one of the most important objectives among the General Aviation community. In recent years, machine learning techniques have emerged as an important enabler in the data-driven safety enhancement of aviation operations with a number of techniques being applied to flight data to identify and isolate anomalous (and potentially unsafe) 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 and operations. In this paper, a novel method of identifying instantaneous anomalies for retrospective safety analysis in General Aviation using energy-based metrics is proposed. Each flight data record is processed by a sliding window across the multi-variate time series of evaluated metrics. A Gaussian Mixture Model using energy metrics and their variability within each window is fit in order to predict the probability of any instant during the flight being nominal. Instances during flights that deviate from the nominal are isolated to identify potential increased levels of risk. The identified anomalies are compared with traditional methods of safety assessment such as exceedance detection to highlight the benefits of the developed method. The methodology is demonstrated using flight data records from two representative aircraft for critical phases of flight.
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    A Framework for Electrified Propulsion Architecture and Operation Analysis
    (Georgia Institute of Technology, 2019-07) Cinar, Gokcin ; Garcia, Elena ; Mavris, Dimitri N.
    Purpose – The purpose of this paper was to create a generic and flexible framework for the exploration, evaluation and side-by-side comparison of novel propulsion architectures. The intent for these evaluations was to account for varying operation strategies and to support architectural design space decisions, at the conceptual design stages, rather than single-point design solutions. Design/methodology/approach – To this end, main propulsion subsystems were categorized into energy, power and thrust sources. Two types of matrices, namely, the property and interdependency matrices, were created to describe the relationships and power flows among these sources. These matrices were used to define various electrified propulsion architectures, including, but not limited to, turboelectric, series-parallel and distributed electric propulsion configurations. Findings – As a case study, the matrices were used to generate and operate the distributed electric propulsion architecture of NASA’s X-57 Mod IV aircraft concept. The mission performance results were acceptably close to the data obtained from the literature. Finally, the matrices were used to simulate the changes in the operation strategy under two motor failure scenarios to demonstrate the ease of use, rapidness and automation. Originality/value – It was seen that this new framework enables rapid and analysis-based comparisons among unconventional propulsion architectures where solutions are driven by requirements.
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    Multi-UAV Trajectory Optimization Utilizing a NURBS-Based Terrain Model for an Aerial Imaging Mission
    (Georgia Institute of Technology, 2019-05) Choi, Youngjun ; Chen, Mengzhen ; Choi, Younghoon ; Briceno, Simon ; Mavris, Dimitri N.
    Trajectory optimization precisely scanning an irregular terrain is a challenging problem since the trajectory optimizer needs to handle complex geometry topology, vehicle performance, and a sensor specification. To address these problems, this paper introduces a novel framework of a multi-UAV trajectory optimization method for an aerial imaging mission in an irregular terrain environment. The proposed framework consists of terrain modeling and multi-UAV trajectory optimization. The terrain modeling process employs a Non-Uniform Rational B-Spline (NURBS) surface fitting method based on point cloud information resulting from an airborne LiDAR sensor or other sensor systems. The NURBS-based surface model represents a computationally efficient terrain topology. In the trajectory optimization method, the framework introduces a multi-UAV vehicle routing problem enabling UAV to scan an entire area of interest, and obtains feasible trajectories based on given vehicle performance characteristics, and sensor specifications, and the approximated terrain model. The proposed multi-UAV trajectory optimization algorithm is tested by representative numerical simulations in a realistic aerial imaging environment, namely, San Diego and Death Valley, California.
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    Energy-Constrained Multi-UAV Coverage Path Planning for an Aerial Imagery Mission Using Column Generation
    (Georgia Institute of Technology, 2019-03) Choi, Younghoon ; Choi, Youngjun ; Briceno, Simon ; Mavris, Dimitri N.
    This paper presents a new Coverage Path Planning (CPP) method for an aerial imaging mission with multiple Unmanned Aerial Vehicles (UAVs). In order to solve a CPP problem with multicopters, a typical mission profile can be defined with five mission segments: takeoff, cruise, hovering, turning, and landing. The traditional arc-based optimization approaches for the CPP problem cannot accurately estimate actual energy consumption to complete a given mission because they cannot account for turning phases in their model, which may cause non-feasible routes. To solve the limitation of the traditional approaches, this paper introduces a new route-based optimization model with column generation that can trace the amount of energy required for all different mission phases. This paper executes numerical simulations to demonstrate the effectiveness of the proposed method for both a single UAV and multiple UAV scenarios for CPP problems.
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    Integrated Sizing and Optimization of Aircraft and Subsystem Architectures in Early Design
    (Georgia Institute of Technology, 2018-06) Rajaram, Dushhyanth ; Yu, Cai ; Chakraborty, Imon ; 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 the 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 (NSGA-II) algorithm 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 yields generations of nondominated designs in which substantially electrified subsystem architectures are found to predominate. As a first assessment of the impact of epistemic uncertainty on the results obtained, the optimization is rerun 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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    Multi-objective Optimization of Departure Procedures at Gimpo International Airport
    (Georgia Institute of Technology, 2018) Kim, Junghyun ; Lim, Dongwook ; Monteiro, Dylan Jonathan ; Kirby, Michelle ; Mavris, Dimitri N.
    Most aviation communities have increasing concerns about the environmental impacts, which are directly linked to health issues for local residents near the airport. In this study, the environmental impact of different departure procedures using the Aviation Environmental Design Tool (AEDT) was analyzed. First, actual operational data were compiled at Gimpo International Airport (March 20, 2017) from an open source. Two modifications were made in the AEDT to model the operational circumstances better and the preliminary AEDT simulations were performed according to the acquired operational procedures. Simulated noise results showed good agreements with noise measurement data at specific locations. Second, a multi-objective optimization of departure procedures was performed for the Boeing 737-800. Four design variables were selected and AEDT was linked to a variety of advanced design methods. The results showed that takeoff thrust had the greatest influence and it was found that fuel burn and noise had an inverse relationship. Two points representing each fuel burn and noise optimum on the Pareto front were parsed and run in AEDT to compare with the baseline. The results showed that the noise optimum case reduced Sound Exposure Level (SEL) 80-dB noise exposure area by approximately 5% while the fuel burn optimum case reduced total fuel burn by 1% relative to the baseline for aircraft-level analysis.