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Aerospace Systems Design Laboratory (ASDL)

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https://hdl.handle.net/1853/70744

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Daniel Guggenheim School of Aerospace Engineering

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1135

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Now showing 1 - 10 of 10

Zero-Emission Regional Aviation in Sweden

(International Council of the Aeronautical Sciences (ICAS), 2022-11) Sorrentino, Robert T. ; Parello, Romain C. ; Delage, Martin ; Justin, Cedric Y. ; Mavris, Dimitri N. ; Jouannet, Christopher ; Amadori, Kristian

Regional air operations, which can be defined as the transportation of passengers using smaller aircraft over short distances, have been overlooked in recent years by airlines focusing on high volume and profitable routes between large airports. Despite this shift of focus, the airport infrastructure still exists in many smaller communities between which demand for air travel exists. The emergence of new air vehicles designed for shorter routes could stimulate efficient and profitable operations, especially if they leverage currently underutilized and paid-for airports. However, new regional air operations need to be sustainable to be successful in a world striving for a carbon-neutral future, especially since air travel over short distances can be substituted by other means of transportation with a smaller environmental footprint such as cars, trains, or buses. Many different paths are envisioned to reach zero-emission goals. These range from technology advancements to new powertrain configurations, and from new transportation policies to new emission offsetting schemes. It is however not clear how these different paths interact and how solutions could be optimally combined. Analyses are therefore required to estimate future demand for air travel and to assess the feasibility of zero-emission regional aviation with the objective to support decision-making about viable and sustainable paths for new regional air operations. The developed modeling environment is implemented in Sweden and allows for an environmental assessment of various scenarios. Significant untapped demand is uncovered between smaller markets, and given fuel and energy consumption for these operations, it is likely that sustainable advanced regional air mobility will be possible in Sweden provided technology transitions can be made.
Development of a Simulation Environment to Track Key Metrics to Support Trajectory Energy Management of Electric Aircraft

(Georgia Institute of Technology, 2022-07) Verberne, Johannes ; Beedie, Seumas M. ; Harris, Caleb ; Justin, Cedric Y. ; Mavris, Dimitri N.

Growing concerns worldwide about anthropogenic climate change are leading to significant research in ways to reduce greenhouse gas emissions. Technologies are investigated to improve the overall energy efficiency of flying vehicles, and among these, new powertrain technologies less reliant on fossil fuels are especially promising. Concurrently, the expected growth of new market segments, such as urban air mobility and regional air mobility where vehicles are envisioned to operate over densely populated areas, will lead to increased scrutiny regarding the vehicle emissions and the vehicle safety. In this context, significant research has been carried out in the field of electric and hybrid-electric aircraft propulsion. Driven by significant strides made by the automotive industry regarding electric battery technology, the aspirational goal of useful electric flight is now within reach. Significant challenges nonetheless remain regarding the certification of these new vehicles to ensure an equivalent level of safety. Indeed, the behavior of electric powertrains is more complex than that of traditional powertrains and features additional thermal and ageing constraints that need to be contended with. Moreover, the ability of many of these vehicles to fly both on their wing or on their rotors brings another level of sophistication that will increase the workload of flight crews. Combined, these might adversely impact the safety of flight. This research aims to elucidate some of these challenges by providing insights into the behavior and idiosyncracies of new electrified vehicles and by identifying visual cues that should be provided to flight crews to support safe decisionmaking in the cockpit. Besides these visual cues, we explore functionalities that a Trajectory Energy Management system could feature to improve flight safety by providing insights into the management of stored usable energy and by monitoring critical parameters of electrified powertrains. This paper includes two use-cases in which the functionality of the Trajectory Energy Management system is explored for pre-flight planning and in-flight diversion decisionmaking applications.
Optimal Trajectory and En-Route Contingency Planning for Urban Air Mobility Considering Battery Energy Levels

(Georgia Institute of Technology, 2022-06) Kim, Seulki ; Harris, Caleb ; Justin, Cedric Y. ; Mavris, Dimitri N.

Urban Air Mobility (UAM) is an electric propelled, vertical takeoff and landing (eVTOL) aircraft envisioned for transporting passengers and goods within metropolitan areas. Planning UAM flights will not be easy as unexpected wind turbulence from high-altitude structures may impact the vehicles operating at a low altitude. Furthermore, considering the short travel time of the UAM, smart and safe decision-making will be challenging, particularly in off-nominal situations that force the aircraft to divert to an alternate destination instead of landing at the initially planned destination. To overcome these challenges, this research proposes automated pre-flight and in-flight contingency planning systems to assist in both normal and irregular UAM operations. A planner in the pre-flight planning system optimizes an aerial trajectory between the scheduled origin and destination, avoiding restricted high-level structures and estimating energy levels. In the contingency planning system, an in-flight replanner produces several optimal trajectories from where the diversion is declared to each alternate destination candidate. A diversion decision-making tool then scores a list of candidates and selects the best site for diversion. Real-world operational scenarios in the city of Miami are presented to demonstrate the capability of the proposed framework.
Trajectory Energy Management Systems for eVTOL Vehicles: Modeling, Simulation and Testing

(Georgia Institute of Technology, 2022) Wilde, Markus ; Kish, Brian ; Senkans, Emils ; Kanchwala, Tahir ; Beedie, Seumas M. ; Harris, Caleb ; Verberne, Johannes ; Justin, Cedric Y. ; Merkt, Juan

The rise of electric aircraft propulsion methods, the increased use of automated and integrated flight control systems, and the envisioned use of personal Vertical Takeoff and Landing (VTOL) vehicles in urban environments lead to novel technical and regulatory challenges for aircraft manufacturers, certification authorities and operators. The combination of electric propulsion, where energy reserves and powertrain performance are highly sensitive to the environment, and VTOL, where the aircraft cannot simply glide to an emergency landing, generates the need for Trajectory Energy Management (TEM). The TEM task involves the manipulation of flight and propulsion controls to achieve a planned flight profile. The TEM system must provide the pilot or automated control system with guidance cues to achieve a planned flight profile, to maintain an energy-optimal trajectory, to avoid deviations from the flight plan causing increases in energy and power consumption, and to mitigate the risk of energy completion. As the pilot must manage both the energy source and flight dynamics energy state, the TEM system must provide sufficient information to the pilot, so that the pilot can perform the mission. This research is intended to define some requirements for energy management such that the pilot can safely accomplish an intended profile and land with enough energy reserves. These requirements must be defined based on prototype algorithm development, simulation results, and flight test data.
Modeling and Simulation of Novel Electric/Hybrid Electric Multicopter Architectures for Urban Air Mobility

(Georgia Institute of Technology, 2021-08) Demers Bouchard, Etienne ; Verberne, Johannes ; D’Arpino, Matilde ; Ozcan, Metin ; Porpora, Francesco ; Gladin, Jonathan C. ; Patel, Srujal ; Justin, Cedric Y. ; Mavris, Dimitri N.

This paper introduces a dynamic simulation environment developed for novel multi-copter aircraft architectures. The development is motivated by the need to better understand the safety implications of architectural design choices and to provide a formal reliability assessment framework for new Vertical Take-Off and Landing (VTOL) concepts able to consider various airframe and subsystems dynamic behavior. The concepts of interests are different multi-copters configurations investigated by NASA and featuring either electric, hybrid electric, or turboshaft driven powertrains. The simulation environment is a timemarching dynamic simulator formulated using physics-based subsystem models for the batteries, electric motors, turboshaft engines and electric generators. Identified fault modes are integrated into the subsystem models for subsequent use during reliability assessments. The impacts of subsystem faults are propagated to the vehicle flight dynamic response for analysis of their impact on the ability of the vehicle to sustain safe operations. Detailed features of the electric quadrotor model are provided to illustrate the simulation capabilities. Some faults are inserted on the different aircraft in hover and the subsystems behavior is successfully propagated at the vehicle level.
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.
Parametric Design, Manufacturing and Simulation of On-Demand Fixed Wing UAVs

(Georgia Institute of Technology, 2021-01-04) Chitale,Yash H. ; Justin, Cedric Y. ; Mavris, Dimitri N.

As the market for Unmanned Aerial Vehicles (UAVs) continues to expand, an unfulfilled need has been identified for tailor-made solutions leveraging an end-to-end process for the design and manufacture of the vehicle. The use of computer aided design combined with new manufacturing techniques allows small UAVs to be parametrically sized and quickly prototyped and deployed. This parametrization technique can be used throughout the entire design process to create optimized, attritable, on-demand solutions that can be adapted to evolving customer requirements. High-level requirements are mapped to quantitative design constraints and an automated process uses these constraints to design and manufacture a vehicle within a specified amount of time. The proposed framework is demonstrated with the generation of a fixed wing UAV solution for the detection and tracking of wildlife in remote areas. National Parks seek to prevent illegal poaching but often lack either the resources to monitor endangered animals, or the budget to purchase UAVs specially designed for wildlife tracking. First, mission requirements are identified and define a design space from which an optimal design point is selected. This design point sizes a UAV model, which is then optimized to minimize manufacturing time with the objective to yield a ready-to-fly solution within 48 hours. A flight simulation of the mission is then performed to ensure that the vehicle will fly as designed. Structural limitations of the UAV are accounted for and linked to parameters of the flight control algorithm to ensure that the UAV can safely fly its mission.
A Data-Driven Approach using Machine Learning to Enable Real-Time Flight Path Planning

(Georgia Institute of Technology, 2020-06) Kim, Junghyun ; Briceno, Simon ; Justin, Cedric Y. ; Mavris, Dimitri N.

As aviation traffic continues to grow, most airlines are concerned about flight delays, which increase operating costs for the airlines. Since most delays are caused by weather, pilots and flight dispatchers typically gather all available weather information prior to departure to create an efficient and safe flight plan. However, they may have to perform in-flight re-planning because weather information can significantly change after the original flight plan is created. One potential issue is that weather forecasts being currently used in the aviation industry may provide relatively unreliable information and are not accessible fast enough so that it challenges pilots to perform in-flight re-planning more accurately and frequently. In this paper, we propose a data-driven approach that uses an unsupervised machine learning technique to provide a more reliable and up-to-date area of convective weather. To evaluate the proposed methodology, we collect the American Airlines flight (AA1300) information and actual weather-related data on October 6th, 2019. Preliminary results show that the proposed methodology provides a better picture of the nearby convective weather activity compared to the most well-known convective weather product.
Optimal Siting of Sub-Urban Air Mobility (sUAM) Ground Architectures using Network Flow Formulation

(Georgia Institute of Technology, 2020-06) Venkatesh, Nikhil ; Payan, Alexia P. ; Justin, Cedric Y. ; Kee, Ethan C. ; Mavris, Dimitri N.

Air Mobility (AM) operating models have steadily made their way into public conscience over the past decade due to increased research activity pioneered by large technology corporations such as Uber and Amazon. Estimates concur that there are around 250 startup businesses with 22 major players working on such technologies with over $25 billion dollars in venture capital funding in 2017[1]. Given the meteoric rise of Air Mobility as one of the leading 21st century disruptive technologies, research effort across the spectrum of functions that can make AM concepts a reality are burgeoning - ranging from vehicle design to operations planning. More specifically, research efforts within the operations planning space deal with service route identification, ground infrastructure (such as charging stations and ports) placement and others. To this effect, the present study seeks to evaluate the feasibility and tractability of a formalized optimization method towards the siting of "vertiports" - ground infrastructure that aids the embarkation and disembarkation of AM commuters - as applied to a Sub-Urban Air Mobility (sUAM) operating model. Mixed-Integer Programming (MIP) formulations offer qualified benefits over other heuristic methods and the authors are confident of their relative performance given the proven track record of such methods in solving generalized facility location problems (GFLP). In this study, two optimization problems were considered: capacitated vertiport siting, where any vertiport considered would need to adhere to capacity constraints; and uncapacitated vertiport siting, where any vertiport considered does not have any capacity limit and can service unlimited demand. Results indicate that a network flow formulation using an MIP methodology is able to adequately place vertiports for sUAM business operations to satisfy demand flows associated with home-work commute.
Power optimized battery swap and recharge strategies for electric aircraft operations

(Georgia Institute of Technology, 2020-06) Justin, Cedric Y. ; Payan, Alexia P. ; Briceno, Simon I. ; German, Brian J. ; Mavris, Dimitri N.

Electric propulsion for commuter air transportation is becoming promising because of significant strides in battery specific energy and motor specific power. Energy storage and rapid battery recharge remain nonetheless challenging owing to the significant energy and power requirements of even small aircraft. By modifying algorithms developed in the field of scheduling theory, we propose power optimized and power-investment optimized strategies for electric aircraft battery swaps and recharges. Several aspects are considered: electric energy expenditures, capital expenditures, and flight schedule integrity. The first strategy optimizes the swaps and recharges to minimize the peak-power draw from the grid and to reduce electric energy expenditures. The second strategy optimizes the swaps and recharges to minimize electricity expenditures and capital expenditures associated with battery and charger procurement. In both cases, the optimization is decomposed into two simpler problems. The first is a recharge schedule feasibility analysis given a number of chargers and batteries, which is based on a network flow representation of the battery swap and recharge. The second is a recharge schedule generation given a number of chargers and batteries. Both strategies are applied to the operations of two commuter airlines and are contrasted with a benchmark non-optimized power-as-needed strategy. Promising results are obtained with up to 61% reduction in peak-power draw and up to 25% reduction in electricity costs.