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Daniel Guggenheim School of Aerospace Engineering

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Author: Mavris, Dimitri N. × End date: 2022 × Start date: 2020 × search.filters.applied.f.isOrgUnitOfPublicationTitle: College of Engineering ×

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Zero-Emission Regional Aviation in Sweden

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.

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Maritime Autonomous System Design Methods and Technology Forecasting

2022-06 , Patel, Rohan , Hadley, Jack , Gabhart, Austin , Singla, Deepika , Wei, Xiao (Olin) , Grant, Jacob , Robertson, Nicole , Weston, Neil , Steffens, Michael , Mavris, Dimitri N.

As naval architects consider the construction of long-term autonomous maritime systems, the naval design process will be modified. The incorporation of reliability analysis in conceptual design is needed to enable systems incapable of in-theater maintenance. The use of reliability analysis is demonstrated with notional architecture, redundancy, and component requirement trades.

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Conceptual Design of Boundary Layer Ingesting Aircraft Capturing Aero-Propulsive Coupling

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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Impact of Adverse Weather on Commercial Helicopter Pilot Decision-Making and Standard Operating Procedures

2021-08 , Speirs, Andrew H. , Ramee, Coline , Payan, Alexia P. , Mavris, Dimitri N. , Feigh, Karen M.

Helicopter pilots face unique challenges with regard to adverse weather when compared to fixed-wing pilots. Rotorcraft typically operate at lower altitudes in off-field areas that are not always well covered by weather reporting stations. Although recent technological advances have increased the amount of weather data that pilots can access in the cockpit, weather remains a factor in 28% of fatal helicopter accidents. In this work, commercial helicopter pilots were surveyed and interviewed to better understand how they gather and process weather information, what the perceived limitations of current weather tools are, and how their decision-making process is affected by the information they gather and/or receive. Pilots were found to use a wide variety of weather sources for their initial go or no-go decision during the preflight phase, but use fewer weather sources in the cockpit while in-flight. Pilots highlighted the sparsity and sometimes inaccuracy of the weather information available to them in their prototypical operational domain. To compensate, they are forced to rely on local and experiential weather knowledge to supplement weather reports while still working to mitigate other external pressures. Based on the literature and on results from this work, recommendations are made to address the weather-related gaps faced by the rotorcraft community. This includes the installation of additional weather reporting stations outside of airports and densely populated areas, the further promotion of the HEMS tool to helicopter pilots in all industries, the development of weather tools capable of visualizing light precipitation such as fog, and the development of in-flight graphical displays that can help reduce the cognitive workload of interpreting weather information.

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Development of a Simulation Environment to Track Key Metrics to Support Trajectory Energy Management of Electric Aircraft

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.

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A Multi-Fidelity Approximation of the Active Subspace Method for Surrogate Models with High-Dimensional Inputs

2022-06 , Mufti, Bilal , Chen, Mengzhen , Perron, Christian , Mavris, Dimitri N.

Modern design problems routinely involve high-dimensional inputs and the active subspace has been recognized as a potential solution to this issue. However, the computational cost for collecting training data with high-fidelity simulations can be prohibitively expensive. This paper presents a multi-fidelity strategy where low-fidelity simulations are leveraged to extract an approximation of the high-fidelity active subspace. Both gradient-based and gradient-free active subspace methods are incorporated with the proposed multi-fidelity strategy and are compared with the equivalent single-fidelity method. To demonstrate the effectiveness of our proposed multi-fidelity strategy, the aerodynamic analysis of an airfoil and a wing are used to define two application problems. The effectiveness of the current approach is evaluated based on its prediction accuracy and training cost improvement. Results show that using a low-fidelity analysis to approximate the active subspace of high-fidelity data is a viable solution and can provide substantial computational savings, yet this is counterbalanced with slightly worse prediction accuracy.

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Emergency Planning for Aerial Vehicles by Approximating Risk with Aerial Imagery and Geographic Data

2022-01 , Harris, Caleb M. , Kim, Seulki , Payan, Alexia P. , Mavris, Dimitri N.

Urban Air Mobility and Advanced Air Mobility require the certification of novel electrified, vertical takeoff and landing, and autonomous aerial vehicles. These vehicles will operate at lower altitudes, in more dense environments, and with limited recovery abilities. Therefore, emergency landing scenarios must be considered broadly to understand the risks in some situations of flight failures. This work provides a preflight planning tool to assist these vehicles when emergency landing is required in crowded environments by fusing geographic data about the population, geometric data from lidar scans, and semantic data about land cover from aerial imagery. The Pix2Pix Conditional GAN is trained on Washington D.C. datasets to predict eight classifications at a 1m resolution. The information from this detection phase is transformed into a costmap, or riskmap, to use in planning the path to the safest landing locations. Multiple combinations of the cost layers are investigated in three test scenarios. The Rapidly Exploring Random Tree (RRT) algorithm efficiently searches for an alternative path that minimizes risk during emergency landing. The tool is demonstrated through three scenarios in the D.C. area. The objective is that the tool allows for the safe operation of UAM and AAM vehicles through crowded regions by providing confidence to the local population and federal regulators.

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Sensitivity Analysis of the Overwing Nacelle Design Space

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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Optimal Trajectory and En-Route Contingency Planning for Urban Air Mobility Considering Battery Energy Levels

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.

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Machine Learning Enabled Turbulence Prediction Using Flight Data for Safety Analysis

2021-09 , Emara, Mariam , dos Santos, Marcos , Chartier, Noah , Ackley, Jamey , Puranik, Tejas G. , Payan, Alexia P. , Kirby, Michelle R. , Pinon, Olivia J. , Mavris, Dimitri N.

The hazards posed by turbulence remain an important issue in commercial aviation safety analysis. Turbulence is among the leading cause of in-flight injury to passengers and flight attendants. Current methods of turbulence detection may suffer from sparse or inaccurate forecast data sets, low spatial and temporal resolution , and lack of in-situ reports. The increased availability of flight data records offers an opportunity to improve the state-of-the-art in turbulence detection. The Eddy Dissipation Rate (EDR) is consistently recognized as a reliable measure of turbulence and is widely used in the aviation industry. In this paper, both classification and regression supervised machine learning models are used in conjunction with flight operations quality assurance (FOQA) data collected from 6,000 routine flights to estimate the EDR (and thereby turbulence severity) in future time horizons. Data from routine airline operations that encountered different levels of turbulence is collected and analyzed for this purpose. Results indicate that the models are able to perform reasonably well in predicting the EDR and turbulence severity around 10 seconds prior to encountering a turbulence event. Continuous deployment of the model enables obtaining a near-continuous prediction of possible future turbulence events and builds the capability towards an early warning system for pilots and flight attendants.

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