Aerospace Engineering Commons^™

Artificial Intelligence-Assisted Inertial Geomagnetic Passive Navigation, Andrei Cuenca

Doctoral Dissertations and Master's Theses

In recent years, the integration of machine learning techniques into navigation systems has garnered significant interest due to their potential to improve estimation accuracy and system robustness. This doctoral dissertation investigates the use of Deep Learning combined with a Rao-Blackwellized Particle Filter for enhancing geomagnetic navigation in airborne simulated missions.

A simulation framework is developed to facilitate the evaluation of the proposed navigation system. This framework includes a detailed aircraft model, a mathematical representation of the Earth's magnetic field, and the incorporation of real-world magnetic field data obtained from online databases. The setup allows an accurate assessment of the performance …

Verification And Validation Of Robot Manipulator Adaptive Control With Actuator Deficiency, Sebastian Comeaux

Doctoral Dissertations and Master's Theses

This work addresses the joint tracking problem of robotic manipulators with uncertain dynamical parameters and actuator deficiencies, in the form of an uncertain control effectiveness matrix, through adaptive control design, simulation, and experimentation. Specifically, two novel adaptive controller formulations are implemented and tested via simulation and experimentation. The proposed adaptive control formulations are designed to compensate for uncertainties in the dynamical system parameters as well as uncertainties in the control effectiveness matrix that pre-multiplies the control input. The uncertainty compensation of the dynamical parameters is achieved via the use of the desired model compensation–based adaptation, while the uncertainties related to …

Stochastic Point Process Modeling For Engineering Applications, Samarth Motagi

Doctoral Dissertations and Master's Theses

Hawkes model or self-exciting point process model is a branching point process model. The model classifies the dataset of discrete events to background and offspring events. It has been used to study interconnected events in many fields, but relatively little work exists in applying these concepts to engineering problems. In our research, we use a self-exciting point process model for two engineering applications: (a) To identify secondary crashes from a given traffic data and (b) To quantify the agglomeration state and size of nanoparticles from computationally generated carbon nanotube microstructure using stochastic percolation model and experimentally generated titanium nanoparticle microstructures. …

Deep-Learning Based Multiple-Model Bayesian Architecture For Spacecraft Fault Estimation, Rocio Jado Puente

Doctoral Dissertations and Master's Theses

This thesis presents recent findings regarding the performance of an intelligent architecture designed for spacecraft fault estimation. The approach incorporates a collection of systematically organized autoencoders within a Bayesian framework, enabling early detection and classification of various spacecraft faults such as reaction-wheel damage, sensor faults, and power system degradation.

To assess the effectiveness of this architecture, a range of performance metrics is employed. Through extensive numerical simulations and in-lab experimental testing utilizing a dedicated spacecraft testbed, the capabilities and accuracy of the proposed intelligent architecture are analyzed. These evaluations provide valuable insights into the architecture's ability to detect and classify …

Development Of A Constellation Simulator For A 5g/Iot Mission Planning System, Franco Criscola

Doctoral Dissertations and Master's Theses

The advancement of 5G and Internet-of-Things technologies has presented new challenges for telecommunications providers. One of the challenges is integrating these technologies with present networks. A solution has been found in low-Earth orbit satellite constellations. On one hand, this method increases coverage and reduces costs, but on the other it raises new problems like how to efficiently manage large constellations of spacecraft. This thesis introduces the Constellation Management System, developed in collaboration with i2Cat foundation. This novel tool is composed of two modules: the simulator and the scheduler. The former propagates satellite motion and computes visibility events to various targets …

Comparative Evaluation Of Propulsive Power Transmission Technologies For High-Speed Vertical Takeoff And Landing (Hsvtol) Cargo Aircraft, Xinyu Yang

Doctoral Dissertations and Master's Theses

Designing High-Speed Vertical Takeoff and Landing (HSVTOL) cargo aircraft capable of both low downwash velocity hovering and high subsonic speed cruising presents a significant engineering challenge. This challenge, stemming from conflicting design requirements, has been substantially influenced by recent technological advancements, which have offered greater flexibility in rotor placement. Consequently, this has led to the emergence of innovative mission-specific designs that hold the potential to outperform traditional concepts. The central objective of this study is to evaluate the benefits of modern technologies for VTOL cargo aircraft and assess their performance relative to baseline VTOL aircraft. The results of this comparative …

Six-Degree-Of-Freedom Optimal Feedback Control Of Pinpoint Landing Using Deep Neural Networks, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua

Student Works

Machine learning regression techniques have shown success at feedback control to perform near-optimal pinpoint landings for low fidelity formulations (e.g. 3 degree-of-freedom). Trajectories from these low-fidelity landing formulations have been used in imitation learning techniques to train deep neural network policies to replicate these optimal landings in closed loop. This study details the development of a near-optimal, neural network feedback controller for a 6 degree-of-freedom pinpoint landing system. To model disturbances, the problem is cast as either a multi-phase optimal control problem or a triple single-phase optimal control problem to generate examples of optimal control through the presence of disturbances. …

Flying To Net Zero With Sustainable Atos; Changing Cultures​, Eva Maleviti

Publications

What is Sustainability?

• World Commission on Environment and Development’s (WCED) 1987 Brundtland Report ‘’Our Common Future’’.
• Help world nations towards sustainable development.

17 Sustainable Development Goals

• The start of all industries are the 17 SDGs
• Aviation can address the 15 SDGs
• Net zero target suggest reduction of aviation emissions up to 21.2 Gt CO2

Orbital Debris Mitigation: Exploring Cubesat Drag Sail Technology, Robinson Raphael

Student Works

In an era marked by remarkable advancements in space exploration and research, the advent of satellite technology has contributed accordingly to the lives of people here on Earth. Through applications that tie into broadband connectivity, weather forecasting, disaster management, etc., the occupancy in orbital domains like Low-Earth Orbit (LEO) only continues to grow. However, the presence of orbital debris emerges as a significant concern, posing threats to both operational satellites and future space missions. Resulting as a consequence due to decades of activities since the launch of Sputnik 1 in 1957, as more countries ventured into space so did the …

State Space Modeling And Estimation Of Flexible Structure Using The Theory Of Functional Connections, Carlo Lombardi, Riccardo Bevilacqua

Student Works

In this work, we present a novel method to model the dynamics of a continuous structure based on measurements taken at discrete points. The method is conceived to provide new instruments to address the problem of flexible dynamics modeling in a spacecraft, where an effective mathematical representation of the non-rigid behavior of the is of critical importance in the design of an effective and reliable attitude estimation and control system. Both the measurements and the model that describes the structure can be affected by uncertainty. The purpose of the developed method is to estimate the position and the velocity of …

Using Machine Learning To Predict Hypervelocity Fragment Propagation Of Space Debris Collisions, Katharine Larsen, Riccardo Bevilacqua

Student Works

The future of spaceflight is threatened by the increasing amount of space debris, especially in the near-Earth environment. To continue operations, accurate characterization of hypervelocity fragment propagation following collisions and explosions is imperative. While large debris particles can be tracked by current methods, small particles are often missed. This paper presents a method to estimate fragment fly-out properties, such as fragment, velocity, and mass distributions, using machine learning. Previous work was performed on terrestrial data and associated simulations representing space debris collisions. The fragmentation of high-velocity fragmentation can be modeled by terrestrial fragmentation tests, such as static detonations. Recently, stereoscopic …

Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua

Student Works

The ability to certify systems driven by neural networks is crucial for future rollouts of machine learning technologies in aerospace applications. In this study, the neural networks are used to represent a fuel-optimal feedback controller for two different 3-degree-of-freedom pinpoint landing problems. It is shown that the standard sum-ofsquares Lyapunov candidate is too restrictive to assess the stability of systems with fuel-optimal control profiles. Instead, a parametric Lyapunov candidate (i.e. a neural network) can be trained to sufficiently evaluate the closed-loop stability of fuel-optimal control profiles. Then, a stability-constrained imitation learning method is applied, which simultaneously trains a neural network …

Interfacial Thermomechanical Behavior Of Hybrid Carbon Fibers, Sriraj Srihari

Doctoral Dissertations and Master's Theses

The carbon fiber/epoxy interface is of great importance in composite design due to its load transfer mechanisms from the weak epoxy to the stronger fiber. Improving the strength of the interface reduces the risk of failure at the interface and improves the load transfer to the fiber. In this study, two types of nano-species ZnO nanowires and nickel-based metal organic frameworks were grown on carbon fibers to improve the interfaces. The interfacial mechanics of the enhanced fibers are evaluated using nanoindentation studies. Composite samples with Aeropoxy matrix and vertically aligned fibers are fabricated for this purpose. A Bruker TI-980 TriboIndenter …

Online Aircraft System Identification Using A Novel Parameter Informed Reinforcement Learning Method, Nathan Schaff

Doctoral Dissertations and Master's Theses

This thesis presents the development and analysis of a novel method for training reinforcement learning neural networks for online aircraft system identification of multiple similar linear systems, such as all fixed wing aircraft. This approach, termed Parameter Informed Reinforcement Learning (PIRL), dictates that reinforcement learning neural networks should be trained using input and output trajectory/history data as is convention; however, the PIRL method also includes any known and relevant aircraft parameters, such as airspeed, altitude, center of gravity location and/or others. Through this, the PIRL Agent is better suited to identify novel/test-set aircraft.

First, the PIRL method is applied to …

Rigid Body Constrained Motion Optimization And Control On Lie Groups And Their Tangent Bundles, Brennan S. Mccann

Doctoral Dissertations and Master's Theses

Rigid body motion requires formulations where rotational and translational motion are accounted for appropriately. Two Lie groups, the special orthogonal group SO(3) and the space of quaternions H, are commonly used to represent attitude. When considering rigid body pose, that is spacecraft position and attitude, the special Euclidean group SE(3) and the space of dual quaternions DH are frequently utilized. All these groups are Lie groups and Riemannian manifolds, and these identifications have profound implications for dynamics and controls. The trajectory optimization and optimal control problem on Riemannian manifolds presents significant opportunities for theoretical development. Riemannian optimization is an attractive …

A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu, Irene Moulitsas

Journal of Aviation/Aerospace Education & Research

This paper proposes a classification approach for flight delays using Bidirectional Long Short-Term Memory (BiLSTM) and Long Short-Term Memory (LSTM) models. Flight delays are a major issue in the airline industry, causing inconvenience to passengers and financial losses to airlines. The BiLSTM and LSTM models, powerful deep learning techniques, have shown promising results in a classification task. In this study, we collected a dataset from the United States (US) Bureau of Transportation Statistics (BTS) of flight on-time performance information and used it to train and test the BiLSTM and LSTM models. We set three criteria for selecting highly important features …

Predicting Dynamic Fragmentation Characteristics From High-Impact Energy Events Utilizing Terrestrial Static Arena Test Data And Machine Learning, Katharine Larsen, Riccardo Bevilacqua, Omkar S. Mulekar, Elisabetta L. Jerome, Thomas J. Hatch-Aguilar

Student Works

To continue space operations with the increasing space debris, accurate characterization of fragment fly-out properties from hypervelocity impacts is essential. However, with limited realistic experimentation and the need for data, available static arena test data, collected utilizing a novel stereoscopic imaging technique, is the primary dataset for this paper. This research leverages machine learning methodologies to predict fragmentation characteristics using combined data from this imaging technique and simulations, produced considering dynamic impact conditions. Gaussian mixture models (GMMs), fit via expectation maximization (EM), are used to model fragment track intersections on a defined surface of intersection. After modeling the fragment distributions, …

Multiple Uncertain Robot Manipulator Control For A Modular System, Thitiphun Vongkunghae

Doctoral Dissertations and Master's Theses

Modular systems have gained significant attention in various domains due to their flexibility, scalability, and adaptability. These systems consist of multiple interconnected modules that can be combined and reconfigured to achieve desired functionalities. The modular approach offers numerous advantages, including ease of maintenance, reduced downtime, and cost-effectiveness. However, designing effective distributed control strategies for modular systems presents unique challenges. Specifically, modular systems that consist of robot manipulators are subject to non-linear unknown terms as well as unknown effects. This thesis focuses on developing and designing a distributed model reference adaptive controller for a robotic modular system that is subject to …

The Influence Of Mixing Duct Length And Phase Of Flight On Wall Temperatures Of A Rocket Based Combined Cycle Engine In Ejector And Air-Augmented Modes, Jonathan Grow

Doctoral Dissertations and Master's Theses

Rocket Based Combined Cycle (RBCC) engines have been theorized as a possible means of powering launch vehicles and high-speed atmospheric vehicles. By incorporating aspects of both air-breathing and rocket propulsion, RBCC engines promise up to a 230 % increase in specific impulse over traditional chemical rocket propulsion by entraining a secondary flow of atmospheric air and mixing it with the exhaust of a rocket motor. Students within the Embry-Riddle Future Space Explorers and Developers Society (ERFSEDS) identified a
problem of excessive heating and structural failure of the mixing duct during launch and transonic flight of a student-built flight test vehicle. …

Adaptive Control Allocation For Unmanned Aerial Vehicles With Model Uncertainties, Eren Sarioglu

Doctoral Dissertations and Master's Theses

Model uncertainties and effector degradation carry risks to weaken the performance of any aerial system and endanger operation during flight. To this end, over-actuated aerial systems are used in flight operations to take precautions for possible incidents, which may result in improper control or a fall of the aerial vehicle. Adaptive control and adaptive control allocation methods are effective solutions for over-actuated uncertain aerial vehicles to overcome these phenomena because of their ability to estimate unknown effects. In this work, a literature search for control allocation methods is first revealed. An adaptive control allocation solution is introduced and implemented for …

Neural Network Models For Generating Synthetic Flight Data, Nathaniel Sisson

Doctoral Dissertations and Master's Theses

Flight test data is a valuable resource used in many aerospace applications. However, procuring a sufficiently large database of flight test data poses several challenges. Nominal flight tests can be expensive and time-consuming and require much post-processing depending on the availability of sensors and the quality of the sensor output. Flight test performed outside of nominal flight conditions, or flight tests in which failures are introduced, add to the inherent risk and danger associated with flight tests. The most popular alternative to flight test, numerical simulations, may fail to fully capture all non-linear behavior. While flight tests will always be …

Modeling, Control, And Hardware Development Of A Thrust-Vector Coaxial Uav, Andrew North

Doctoral Dissertations and Master's Theses

This thesis introduces a unique thrust vector coaxial unmanned aerial vehicle (UAV) configuration and presents a comprehensive investigation encompassing dynamics modeling, hardware design, and controller development. Using the Newton-Euler method, a dynamic model for the UAV is derived to gain in-depth insights into its fundamental flight characteristics. A simple thrust model is formulated and modified by comparing it with data obtained from vehicle testing. The feasibility of manufacturing such a vehicle is assessed through the development of a hardware prototype. Finally, a linear state feedback controller is designed and evaluated using the non-linear dynamics model. The results demonstrate successful validation …

In-Flight Testing & Verification Of An Adaptive Distributed Fault-Tolerant Control Architecture, Michael Budihartono

Doctoral Dissertations and Master's Theses

The interest in utilizing multi-agent systems (MAS) has increased in the aerospace industry. Its scalability, efficiency, robustness, fault tolerance, and cost-effectiveness make it ideal for performing real-world missions that require more than one agent. However, in completing the tasks, the multi-agent systems are still vulnerable to environmental disturbances, cyber-attacks, and hardware failures. Therefore, an adaptive distributed fault-tolerant control architecture is needed to minimize the impacts of the previously stated circumstances and ensure the mission can continue successfully.

This thesis describes the development of an experimental setup for testing and validating an adaptive consensus algorithm and a bio-inspired health management architecture. …

In-Situ Thermal And Deformation Characterization Of Additive Manufacturing Processes, Nicholas Phillips

Doctoral Dissertations and Master's Theses

Additive manufacturing (AM) is a rapidly growing industry with numerous applications in the aerospace industry such as aircraft parts and emergency tools on the International Space Station. Defects in additively manufactured structures, however, can waste a lot of time and money. Being able to monitor the manufacturing process for defects is one of the first steps which can be taken to mitigate these losses. This study focuses on the use of thermography in conjunction with deep learning to identify flaws during 3D printing of composite structures made using Onyx, a mixture of chopped carbon fiber and nylon, composite prints. In …

Online Estimation Of Unknown Parameters For Flexible Spacecraft, Nicolo Woodward

Doctoral Dissertations and Master's Theses

Attitude controls methods of highly flexible spacecraft have seen increased interest over the last decades thanks to the technological development of flexible solar panels and deploy-ables, which improves the capabilities of small satellites. However, a high-fidelity model of the flexible mode dynamics is hard to obtain in on-ground testing because not all modes of frequencies can be observed, complicating the controller design. Furthermore, plastic deformations due to long periods of storage of stowed flexible components could result in exciting frequencies outside of the designed controller’s bandwidth, leading to an uncontrollable system. This thesis proposes a method to develop a high-fidelity …

An Online Adaptive Machine Learning Framework For Autonomous Fault Detection, Nolan Coulter

Doctoral Dissertations and Master's Theses

The increasing complexity and autonomy of modern systems, particularly in the aerospace industry, demand robust and adaptive fault detection and health management solutions. The development of a data-driven fault detection system that can adapt to varying conditions and system changes is critical to the performance, safety, and reliability of these systems. This dissertation presents a novel fault detection approach based on the integration of the artificial immune system (AIS) paradigm and Online Support Vector Machines (OSVM). Together, these algorithms create the Artificial Immune System augemented Online Support Vector Machine (AISOSVM).

The AISOSVM framework combines the strengths of the AIS and …

Solar Sailing Adaptive Control Using Integral Concurrent Learning For Solar Flux Estimation, Luis Mendoza Zambrano

Doctoral Dissertations and Master's Theses

In the interest of exploiting natural forces for propellant-less spacecraft missions, this thesis proposes an adaptive control strategy to account for unknown parameters in the dynamic modeling of a reflectivity-controlled solar sail spacecraft. A Lyapunov-based control law along with integral concurrent learning is suggested to accomplish and prove global exponential tracking of the estimated parameters and states of interest, without satisfying the common persistence of excitation condition, which in most nonlinear systems cannot be guaranteed a priori. This involves estimating the solar flux or irradiance from the Sun to account for uncertainty and variation over time in this value. To …

Sustainable Atos - Flying To Net Zero, Eva Maleviti, Bettina Mrusek

Publications

Pathways to Net Zero- Targets

Improve fuel-efficiency by an average of 2% per year - 2020 to 2030

Reduction in total carbon dioxide emissions to net-zero by 2050.

After 2026 carbon allowances will be zero for EU.

The Role Of Slip System Activation On Ni-Based Superalloy High Temperature Fatigue, Alexandru Lopazan

Doctoral Dissertations and Master's Theses

Nickel-based superalloys are used extensively in the aviation industry, particularly in aircraft engine components. These materials are desirable due to their high strength, resistance to creep, corrosive environment, and high temperature. It has been well documented that material fatigue is characterized by material microstructure, type of loading, and other parameters. Currently, research into the effects of fatigue on complex materials like nickel-based superalloys is being pursued. Previous research has found that preconditioning of Inconel 718 samples at 700 ℃ with 1.0% strain led to an improved fatigue life. It has been suggested that this could be caused by the activation …

Impact Resistance Of Hybrid Metal-Organic Frameworks/Carbon Fibers Composites, Derek Isaac Espinosa Ramirez

Doctoral Dissertations and Master's Theses

The increase in the use of carbon fiber-reinforced polymers (CFRPs) composites in the aerospace industry generated the need of improving the properties and capabilities of these composites by adding nano-reinforcements to the carbon fibers, also called hybrid fiber reinforced polymer composites. In this study, the energy absorption due to impact at low speed will be tested and simulated in four configurations of CFRPs utilizing the same [0/90]_S layout throughout them.

The carbon fiber configurations used during this study are de-sized, acid-activated, metal-organic frameworks (MOF), and carbon nanotubes (CNTs). Nickel (II) Nitrate, Methylimidazole, and Methanol were used to grow the …