Person:

Mavris, Dimitri N.

Permanent Link

https://hdl.handle.net/1853/71501

Associated Organization(s)

Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering

Organizational Unit

Aerospace Systems Design Laboratory (ASDL)

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Publication Search Results

Now showing 1 - 10 of 321

A Modeling and Simulation Approach to Assessing the Impacts of Accessibility Solutions in the Air Travel System of Systems

(Georgia Institute of Technology, 2025-01) Ergan, Tuna ; Al Atik, Lin ; Lavanchy, Santiago Garcia ; Lewis, Kayley J. ; Kallou, Evanthia ; Garcia, Elena ; Mavris, Dimitri N.

Air travel can be a complicated experience for travelers in a busy and hectic environment, and these difficulties are heightened significantly for disabled passengers. The ability to quickly and safely get from one destination to another is complicated by conditions that cause these passengers to require accessibility accommodations or outside assistance. Although solutions that would make air travel accessible and inclusive for all are needed, the shortcomings of airports, budgets of stakeholders, or even the demographics of travelers vary greatly. This study aims to design and develop a decision-making framework, supported by a stochastic simulation of air travel system of systems, to understand the interactions between various stakeholders and model potential accessibility solutions. Through the direct visualization and exploration of the decision outcomes, airlines, airports, and aircraft manufacturers will be equipped to make informed choices regarding which solutions to prioritize implementing and to what extent for the benefit of both disabled and able-bodied passengers. The ability to use this discrete event simulation model of air travel systems, calibrated to Atlanta Hartsfield-Jackson International Airport and several other airports of various sizes, for decision-making is demonstrated with various case studies throughout this paper.
Performance Assessment and Mission-Based Optimization for Next-Generation Single-Aisle Aircraft Conceptual Design

(Georgia Institute of Technology, 2025-01) Patel, Dev P. ; Ergan, Tuna ; Cai, Yu ; Gladin, Jonathan C. ; Mavris, Dimitri N.

This paper presents a comprehensive conceptual design study for the next generation of single-aisle passenger transport, focusing on reducing fuel burn and noise through optimization around mission-based parameters. While much of the industry’s efforts have centered on advanced configurations unlikely to be developed and certified soon, this study emphasizes the importance of optimizing conventional aircraft designs to bridge the gap until their arrival. Technologies expected to mature by 2035 are identified and infused into a large single-aisle aircraft to establish a baseline, primarily because the largest market share among other classes of vehicles, followed by optimization driven by mission-based parameters. 2035 technologies alone resulted in a 19.8% reduction in block fuel for the default design range. Reducing the cruise Mach number and incorporating natural laminar flow further decreased the fuel burn by 8.2%. The reduced range optimization yielded an additional fuel saving of up to 4.1%, though the returns diminish with decreasing range. Overall, the total fuel burn reduction compared to the 2018 Technology Reference Aircraft is estimated to range from 29.2% to 30.8%. This work highlights the potential for significant efficiency improvements in next-generation civil aviation while leveraging mature technologies until the arrival of novel configurations.
Fleet-Level and Global Emissions Impact Analysis of Mission-Optimized Next-Generation Single-Aisle Aircraft

(Georgia Institute of Technology, 2025-01) Ergan, Tuna ; Parashar, Akshiti ; Xie, Jiacheng ; Kirby, Michelle R. ; Mavris, Dimitri N.

With mounting concerns over environmental sustainability, the aviation industry faces pressure to reduce its carbon footprint, not only by redesigning aircraft with advanced technologies and materials but also by exploring new avenues like operations-based optimization. This paper supports these efforts by presenting a comprehensive fleet-level analysis for shortrange single-aisle aircraft entering service around 2035, assessing potential global carbon emission reductions through reduced and optimized cruise speed and design range. Using multiple operational scenarios based on vehicles optimized for different and shorter ranges, the impact of introducing new short-range vehicles into future fleets on fuel burn is compared to the present. Although an aircraft’s fuel consumption decreases with a reduced design range due to a smaller vehicle size and thrust requirement, the reduced design range also limits the number of operations the aircraft can cover. The variants that have the largest impact on global and in-class fuel burn were shown to be the ones sized for a design range closest to covering most or all of the existing missions but without going over. The fleet analysis results provide insights for determining the optimal mission profile for the conceptual design of the next-generation single-aisle aircraft.
Towards a Framework for Modeling and Simulating Complex Enterprises: The Case of an Academic Research Laboratory

(Georgia Institute of Technology, 2024-01) Lepez Da Silva Duarte, Noe ; Fischer, Olivia J. Pinion ; Mavris, Dimitri N.

This paper presents an initial exploration into a comprehensive, reusable, and scalable approach to enterprise architecture modeling and simulation, with a significant emphasis on the use of SysML. Through a case study of a large academic research laboratory, the research delineates the application of UAF and SysML models with diverse simulation methodologies, prioritizing the seamless transfer and enhanced visualization of SysML model data. A key contribution of this study is the incorporation of ontologies and graph databases through Neo4j, offering a robust framework for representing and querying complex SysML data. By juxtaposing traditional tools, such as SimPy, with Neo4j, the research underscores the effectiveness of graph databases in presenting a clearer, more intuitive visualization. While the presented simulation serves primarily as a proof-of-concept, it sheds light on the complexities of enterprise dynamics. The potential for richer, more detailed simulations that harness the full capability of these tools beckons further exploration in subsequent research endeavors.
A Reduced Order Modeling Approach to Blunt-Body Aerodynamic Modeling

(Georgia Institute of Technology, 2024-01) Dean, Hayden V. ; Decker, Kenneth ; Robertson, Bradford E. ; Mavris, Dimitri N.

Blunt-body entry vehicles display complex flow phenomena that results in dynamic instabilities in the low supersonic to transonic flight regime. Dynamic stability coefficients are typically calculated through parameter identification and trajectory regression techniques using both physical test data and Computational Fluid Dynamics (CFD) simulations. This methodology can generate dynamic stability coefficients, but the resulting data points are limited, and have high degrees of uncertainty due to the nature of data reduction methods. With increased computational capabilities, new methods for dynamic stability quantification have been explored that seek to leverage the high-dimensional aerodynamic data produced from CFD simulations to compute dynamic stability behavior and address the limitations of linearized aerodynamics. The objective of this work is to advance the quantification of dynamic stability behavior of blunt-body entry vehicles by leveraging high-fidelity CFD data through Reduced Order Modeling (ROM). ROMs are capable of leveraging high-fidelity aerodynamic data in a cost effective manner by finding a low-dimensional representation of the Full Order Model (FOM). ROMs based on Proper Orthogonal Decomposition (POD) have shown success in recreating CFD analyses of parametric ROM applications and time-varying ROM applications. Results of this research demonstrated success in constructing two ROMs of a notional blunt-body entry vehicle to recreate heatshield and backshell pressure distributions from forced oscillation trajectories. The ROM was more successful at reconstructing the heatshield pressure distribution, with challenges arising in predicting the chaotic response of backshell latent coordinates.
Optimal Deployment Strategies for Cislunar PNT+C Architectures

(Georgia Institute of Technology, 2024-01) Gabhart, Austin ; Drosendahl, Madilyn ; Robertson, Bradford E. ; Steffens, Michael J. ; Mavris, Dimitri N.

Cislunar operations are expected to rise dramatically within the next decade, requiring a comparable increase in PNT and communications services. However, current PNT systems are at capacity and need to be augmented to serve a cislunar space domain, specifically in the form of novel cislunar PNT architectures. This paper studies the problem of the deployment of PNT and communications satellites, specifically, the problem of deployment strategies spanning multiple stages over extended periods of time. A set of stage definitions will be determined along with areas of potential user activity. A novel application of the hidden gene genetic algorithm to the constellation optimization problem is presented. A design space exploration is presented with comparisons of circular and elliptical constellations. Optimization results from the first stage are also provided. It is shown that acceptable performance can be achieved with a low number of deployed satellites and that strong trade-offs exist between performance and stability.
Framework for Assessment of Technology Maturation Using Uncertainty Quantification

(Georgia Institute of Technology, 2024-01) Johnston, Hunter B. ; Cox, Adam ; Baker, Adam ; Mavris, Dimitri N.

The results in this paper come from a project to develop an Uncertainty Quantification (UQ) framework to assist researchers in technology development and maturation. This framework aims to re-frame technology maturation as a process of reducing quantifiable uncertainty instead of completing requirements on a Technology Readiness Level (TRL) scale. The framework provided in this paper uses Bayesian statistics to redefine the technology maturation task as a process of reducing uncertainty in system inputs and outputs. This framework is powered by the calculation of a Variance Reduction Potential (VRP) for each system inputs that relates how much how uncertainty in the system-level outputs are related to the uncertainty in the system inputs. This variance reduction potential can be estimated by simulating the system of interest. This allows for researchers to determine which variables are the most important to test before any testing has actually been done. This framework empowers researchers to gain as much information on their system as possible before spending resources on physical testing rounds, making research and development of new systems more efficient.
Unsteady Aerodynamic Uncertainty Quantification of a Blunt-Body Entry Vehicle in Free-Flight

(Georgia Institute of Technology, 2024-01) Willier, Brenton J. ; Hickey, Alexandra M. ; Robertson, Bradford E. ; Mavris, Dimitri N.

The design process of blunt-body entry vehicles balances atmospheric heating and drag to ensure crucial payloads can safely traverse through entry, descent, and landing. However, the blunt shape leads to a chaotic recirculating wake. Currently, uncertainties in the vehicle design process are captured through scalars and multipliers, and these conservative estimations lead to over-engineered vehicles, reduced payload capacity, and less accurate landings. To supplement the data gathered through physical testing, CFD-in-the-loop free-flight trajectories can be simulated throughout the flight regime. While CFD performance has improved significantly, the number of cases required to produce a meaningful sample for an uncertainty analysis remains computationally intense. Parametric uncertainty can be captured with traditional uncertainty methods like Monte Carlo analysis. However, the non-parametric uncertainty due to the unsteady nature of the chaotic wake has yet to be studied for free-flight analysis. This paper presents and implements an ensemble sampling initialization approach to determine the impact of unsteady wake structures imparted on CFD-in-the-loop data produced using replicated trajectory simulations. To enable this data generation, the Genesis vehicle gridding process is detailed, along with an overview of the free-flight CFD simulation setup for a supersonic flight regime. While running a static unsteady simulation, ten flow fields were saved at various times to capture different instantaneous structures in the wake. After initializing identical free-flight simulations with the ten different flow fields, results of vehicle aerodynamic angles, aerodynamic force and moment coefficients, inertial velocity, and vehicle trajectory in multiple reference frames showed identifiable trends with diverging behavior. The uncertainty on these variables due to unsteady flow is also quantified throughout the motion. It is concluded that this aspect of uncertainty must be carefully considered when CFD-in-the-loop is used to model the flight characteristics of a blunt-body vehicle.
Analysis of Infrastructure to Support a Future Space Economy

(Georgia Institute of Technology, 2024-01) Roohi, Zayn A. ; Robertson, Bradford E. ; Mavris, Dimitri N.

Beginning with the Artemis-I mission in late 2022, NASA is embarking upon a series of increasingly complex missions to establish a permanent presence on the surface of the Moon, potentially leading to manned Mars missions within the next few decades. Several private companies have also announced that they have begun work on space tourism projects with the goal of launching within this same time-frame. Supporting this expansion will require advanced space logistics and the development of dedicated space-based supply chains in order to reduce cost and increase resiliency. Previous research has focused on studying the impact that a specific technology, vehicle, or type of infrastructure has on supporting a single space campaign or mission; this paper takes a wider view by examining the impact that several types of infrastructure concepts together will have on the entire set of operations that could take place within the next decade. Lunar in-situ resource utilization, space depots, and space tugs are considered as infrastructure concepts, and a Lunar space station, Lunar habitat, Earth space stations, and Mars missions are considered as the operations to support. A time expanded mixed-integer nonlinear programming model is used to solve traditional network flow and supply chain problems, the results of which are used to propose future resupply missions and supply chain architectures.
A Trade-off Environment to Support Tabletop Exercises for the Selection of Cislunar Architectures

(Georgia Institute of Technology, 2024-01) Introne, Stephanie ; Hawkins, Jacob ; Balchanos, Michael ; Mavris, Dimitri N.

Developing cislunar architectures involves the consideration of many components, and evaluating these architectures requires the consideration of many varied perspectives. The process for making space exploration decisions has become increasingly complicated as interactions amongst participants have become both more impactful and more fraught. There are many additional considerations when conducting this type of analysis, including the context in which the architecture would be operating or the impact of the many assumptions that need to be made. One way to begin to tackle decision-making processes for cislunar architectures is through the development of a tabletop exercise that allows users to see how choices impact the resultant campaign scheduling in real-time, rather than the typical timelines of weeks to months for additional analysis. A tabletop environment brings stakeholder prioritization and interaction to schedule optimization, and contextualizes the decision-making through the use of scenarios. This tabletop tool enables users to compare architectures more quickly than through traditional methods, which could lead to more interactive studies, where different stakeholders are able to participate since new analyses can be run in real-time, or the exploration of more unconventional architectures since there is not the same level of investment needed to obtain results.