Each year, the Daniel Guggenheim School of Aerospace Engineering graduates between 30 and 40 doctoral students - each with unique contributions to make in research, academia, industry, and the evolution of the discipline itself. On this page, we provide links to their abstracts and their published dissertations. We're also introducing Next Gen Ideas, a video series in which our doctoral candidates will have ~ 3 minutes to explain research that took them years to produce. (No one ever said aerospace engineering was easy.) Click on the video above to get started.
Dissertations are sorted by academic year.
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2022 - 2023 Doctoral Dissertations
| Name | Ph.D. Title | Abstract | Advisor |
|---|---|---|---|
| Tony John | "Nonlinear Dynamics of Coupled Thermoacoustic Modes in the Presence of Noise" | This work investigates the dynamics of nonlinearly coupled thermoacoustic modes in the presence of noise. The dynamics of a single linearly unstable thermoacoustic mode has been extensively studied in literature. In the presence of a saturating type nonlinearity, a linearly unstable mode grows and in most cases saturate to a limit cycle. | Prof. Tim Lieuwen |
| Hang Woon Lee | Design and Operations of Satellite Constellations for Complex Regional Coverage |
Fueled by recent technological advancements in small and capable satellites, satellite constellations are now shaping the new era of space commercialization creating new forms of services that span from Earth observations to telecommunications and navigation. With the mission objectives becoming increasingly complex, a new paradigm in the design and operations of satellite constellations is inevitable to make a system cheaper and more efficient. | Prof. Koki Ho |
| Fanruiqi Zeng | "Autonomous Vehicles: Trajectory Planning and Routing in the Era of Advanced Air Mobility" | Advanced air mobility (AAM) is a revolutionary concept that enables on-demand air mobility, cargo delivery, and emergency services via an integrated and connected multimodal transportation network. In the era of AAM, highly autonomous vehicles (AVs) are envisioned as the primary tool for transporting people and cargo from point A to point B. | Prof. John-Paul Clarke |
| Joseph Nathaniel Robinson | "Rotor Fatigue Life Prediction and Design for Revolutionary Vertical Lift Concepts" | Despite recent technological advancements, rotorcraft still lag behind their fixed-wing counterparts in the areas of flight safety and operating cost. Both must be addressed to ensure the continued competitiveness of vertical lift aircraft. Lifecycle costs and accident rates are strongly driven by scheduled replacement or failure of flight-critical components. | Prof. Dimitri Mavris |
| Jaein Lim | "Generalized Heuristic Search Algorithms with Applications to Motion Planning and Multi-Agent Path Finding" | This thesis investigates novel ways of leveraging generalized interpretations of heuristics to solve complex motion planning problems with completeness and bounded suboptimality guarantees. A set of heuristic search algorithms is developed to utilize relaxed notions of relevancy to more efficiently solve path planning, motion planning and multi-agent path finding problems. | Prof. Panagiotis Tsiotras |
| Ameya Ravindra Behere | "A Reduced Order Modeling Methodology for the Parametric Estimation and Optimization of Aviation Noise" | The successful mitigation of aviation noise is one of the key enablers of sustainable aviation growth. Technological improvements for noise reduction at the source have been countered by increasing number of operations at most airports. There are several consequences of aviation noise including direct health effects, effects on human and non-human environments, and economic costs. Several mitigation strategies exist including reduction of noise at source, land-use planning and management, noise abatement operational procedures, and operating restrictions. | Prof. Dimitri N. Mavris |
| Fatma Karagoz | "MBSE Enabled Conceptual Framework for Product Family and Platform Design" | In recent decades, competition in the global marketplace and demands for product variety have driven the need for different approaches to product design where strategies that help achieve high variety and growth while maintaining economies of scale and system complexity gained significant importance. Product family design is a complex problem by nature: the number of dimensions of the problem is high and there is a need to design and manage multiple products and their inter-dependencies simultaneously. | Prof. Dimitri N. Mavris |
| Marcus Aloysius Pereira | "Scalable and Safe Deep Learning Architectures for Stochastic Optimal Control Using Forward-Backward Stochastic Differential Equations" | Stochastic Optimal Control (SOC) in continuous-time requires solving the Hamilton-Jacobi-Bellman (HJB) equation which suffers from the well-known curse-of-dimensionality. Instead of directly attempting to solve the HJB, one can obtain probabilistic representations of the solution via the Nonlinear Feynman-Kac lemma which relates the unique solution of the HJB to a system of Forward-Backward Stochastic Differential Equations (FBSDEs). | Prof. Evangelos Theodorou |
| Caleb Harris | "A Framework for Offline Risk-aware Planning of Low-altitude Aerial Flights During Urban Disaster Response" | Disaster response missions are dynamic and dangerous events for first responders. Active situational awareness is critical for first responders’ decision-making, and in recent years unmanned aerial assets have successfully extended the quality and range of data collection from sensors. However, literature and industry lack a systematic investigation of the algorithms and datasets for aerial system trajectory planning that optimizes mission performance and guarantees mission success. | Prof. Dimitri Mavris |
| Zachary Ernst | "A Controller Development Methodology Incorporating Unsteady, Coupled Aerodynamics and Flight Control Modeling for Atmospheric Entry Vehicles" | Atmospheric entry vehicle aerodynamics, flight dynamics, and control mechanisms are inherently coupled and unsteady. The state-of-the-art disciplinary models used for Mars entry vehicle simulation do not directly account for these time-dependent interactions, resulting in increased model fidelity uncertainty that can negatively affect controller performance. | Prof. Dimitri Mavris |
| Askar Kazbekov | "Inter-Scale Energy Transfer in Turbulent Premixed Combustion" | Turbulent premixed combustion is widely used for energy conversion in power generation and propulsion devices. However, our understanding of the underlying fluid dynamics, combustion, and their interaction is still incomplete. The complexity of turbulent combustion arises from the non-linear, multi-scale, and multi-physics nature of the problem, which involves interactions between fluid dynamic and chemical processes across a myriad of length and time scales. | Prof. Adam M. Steinberg |
| Akshay Prasad | "A Methodology to Enable Concurrent Trade Space Exploration of Space Campaigns and Transportation Systems" | Space exploration campaigns detail the ways and means to achieve goals for our human spaceflight programs. Significant strategic, financial, and programmatic investments over long timescales are required to execute them, and therefore must be justified to decision makers. To make an informed down-selection, many alternative campaign designs are presented at the conceptual-level, as a set and sequence of individual missions to perform that meets the goals and constraints of the campaign, either technical or programmatic. | Prof. Dimitri Mavris |
| HyunKi Lee | "Runway Safety Improvements Through A Data Driven Approach for Risk Flight Prediction and Simulation" |
Runway overrun is one of the most frequently occurring flight accident types threatening the safety of flights. Sensors have been improved with recent technological advancements and allow data collection during flights. The recorded data helps to better identify the characteristics of runway overruns. The improved technological capabilities and the growing air traffic led to increased momentum for reducing flight risk using artificial intelligence. | Prof. Dimitri Mavris |
| Tristan Sarton du Jonchay | "Simulation Frameworks for the Design and Operations of On-Orbit Servicing Infrastructures Dedicated to Geosynchronous Satellites with Uncertain Demand" | From telecommunications to weather monitoring, Geosynchronous (GEO) satellites represent a critical infrastructure supporting a multitude of terrestrial markets. This, however, comes at the cost of large capital expenditures to manufacture, insure, and launch these large spacecrafts to their remote orbits. | Prof. Koki Ho |
| Andrew Kendall | "A Methodology for the Design and Operational Safety Assessment of Unmanned Aerial Systems" | Efforts are underway to introduce Unmanned Aerial Systems (UAS) into routine cargo operations within the National Airspace System (NAS). Such systems have the potential to increase transport system flexibility by mitigating crew scheduling constraints and extending operations to remote locations. | Prof. John-Paul Clarke |
| Ziyi Wang | "Sampling-based Dynamic Optimization: Theory, Analysis and Applications" | This thesis focuses on sampling-based optimization for dynamical systems. We systematically investigate three main perspectives on sampling-based dynamic optimization, namely Stochastic Search, Variational Inference and Variational Optimization. | Dr. Evangelos Theodorou |
| Esma Karagoz | "MM-ADM: A Model-Based Approach to Multidisciplinary Design to Support Automated Decision-Making" | Design and development of complex engineered systems in the aerospace industry have been facing challenges in terms of managing ever increasing complexity. Due to this complexity, engineering design problems become ill-defined by nature; in other words, as the design problem is gradually solved, it becomes better understood with formal specifications. | Prof. Dimitri Mavris |
| Olatunde Sanni | "Microscopic Analysis of many Optimizing Air Vehicles Using High-Performance Computing" |
The operational success of an air traffic system (ATS) depends on air traffic policies. These policies balance the trade-off between safety and performance. Stringent policies stifle rewards, and lenient policies can lead to loss of life and property. | Prof. Eric Feron |
| Ziyi Wang | "Sampling-based Dynamic Optimization: Theory, Analysis and Applications" | This thesis focuses on sampling-based optimization for dynamical systems. We systematically investigate three main perspectives on sampling-based dynamic optimization, namely Stochastic Search, Variational Inference and Variational Optimization. We compare between the perspectives and against state-of-the-art sampling-based dynamic optimizers. | Prof. Evangelos Theodorou |
| Esma Karagoz | "MM-ADM: A Model-Based Approach to Multidisciplinary Design to Support Automated Decision-Making" | Design and development of complex engineered systems in the aerospace industry have been facing challenges in terms of managing ever increasing complexity. Due to this complexity, engineering design problems become ill-defined by nature; in other words, as the design problem is gradually solved, it becomes better understood with formal specifications. | Prof. Dimitri Mavris |
| Olatunde Sanni | "Microscopic Analysis of many Optimizing Air Vehicles Using High-Performance Computing" | The operational success of an air traffic system (ATS) depends on air traffic policies. These policies balance the trade-off between safety and performance. Stringent policies stifle rewards, and lenient policies can lead to loss of life and property. Air traffic management (ATM) research explores this trade-off. Unsurprisingly, this research area has been limited by the human-in-the-loop because human pilots and air traffic controllers (ATCs) are difficult to predict and expensive to model. | Prof. Eric Feron |
| Toshinobu Watanabe | Pixel Inverse Depth Parameterization, Theory and Application | This research seeks to improve upon inverse depth parameterization (IDP), a standard method used to represent spatial coordinates of feature points in map estimation. If the original measurement noise is Gaussian, the IDP can linearize the estimation process and maintain the Gaussian distribution. However, the initialization of IDP is heuristic, not analytic, due to the coordination characteristic. | Prof. Eric Johnson and Prof. JVR Prasad |