Aerospace Engineering Commons^™

Damage Control Measures In Composites: Focus On Damage Tolerance Of Aerospace Structures, Kais Jribi

Doctoral Dissertations and Master's Theses

Barely Visible Impact Damage (BVID) in composite materials presents a stealthy yet significant risk to structural integrity, particularly challenging due to its elusive nature. The approach adopted here diverges from traditional methodologies, focusing on the novel application of Digital Image Correlation (DIC) to map surface area changes during in-situ Compression After Impact (CAI) tests. This technique allows for an in-depth analysis of planar strains along the x and y axes, shedding light on the material's behavior under stress.

A pivotal advancement lies in developing a method for precisely identifying when BVID-induced delamination recommences. By meticulously analyzing strain pattern deviations along …

Farmer Perceptions Of Land Cover Classification Of Uas Imagery Of Coffee Agroecosystems In Puerto Rico, Jose Cabrera, Blake Neal, Kevin Adkins, Ronny Schroeder, Gwendolyn Klenke, Shannon Brines, Nayethzi Hernandez, Kevin Li, Riley Glancy, Ivette Perfecto

Publications

Highly diverse agroecosystems are increasingly of interest as the realization of farms’ invaluable ecosystem services grows. Simultaneously there has been an increased use of uncrewed aerial systems (UAS) in remote sensing as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UAS and the attention on agroecosystems, there exists an opportunity to assess UAS practicality in highly biodiverse settings. In this study, we utilized UAS to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and …

Going Airborne: Kent State's Pioneering Leap Into Integrated Advanced Air Mobility, Jason T. Lorenzon

National Training Aircraft Symposium (NTAS)

This proposal centers on the development of a Concept of Operations in Advanced Air Mobility (AAM). Kent State University's College of Aeronautics and Engineering is poised to pioneer the integration of drones and electric Vertical Takeoff and Landing (eVTOL) systems, bridging the gap between its campus and airport by transporting students and faculty the 3NM distance from campus to the airport and back by a UAV. Beyond a standard research initiative, this proposal signifies a groundbreaking effort to reshape the landscape of educational aeronautics and Advanced Air Mobility and Urban Air Mobility. Our overarching goal is to transcend conventional boundaries …

Cubesat Reaction Wheel Attitude Control Platform System Architecture, Justin Hartland

Beyond: Undergraduate Research Journal

In the classroom, physics behind spacecraft attitude dynamics and controls is abstract and difficult to comprehend. It is common that students struggle to develop the connection between the math they learn and how it can be applied in the real world. The goal of this project is to design and manufacture a 1U, 3U, and 6U CubeSat testbed for autonomous control systems utilizing reaction wheels. The testbed will include three separate reaction wheels each mounted on its own respective axis to control the attitude in 3 degrees of freedom. The end goal of the CubeSat Control Platform is to be …

Immersive Framework For Designing Trajectories Using Augmented Reality, Joseph Anderson, Leo Materne, Karis Cooks, Michelle Aros, Jaia Huggins, Jesika Geliga-Torres, Kamden Kuykendall, David Canales, Barbara Chaparro

Publications

The intuitive interaction capabilities of augmented reality make it ideal for solving complex 3D problems that require complex spatial representations, which is key for astrodynamics and space mission planning. By implementing common and complex orbital mechanics algorithms in augmented reality, a hands-on method for designing orbit solutions and spacecraft missions is created. This effort explores the aforementioned implementation with the Microsoft Hololens 2 as well as its applications in industry and academia. Furthermore, a human-centered design process and study are utilized to ensure the tool is user-friendly while maintaining accuracy and applicability to higher-fidelity problems.

Experimental Analysis Of The Integrated High-Lift Propulsor, Robert W. Deters, Byron Ward, Shreyas Narsipur

Publications

Wind tunnel testing was conducted to evaluate the performance of the Integrated High Lift Propulsor (IHLP), a novel Distributed Electric Propulsion (DEP) system. The IHLP integrates traditional Krueger flap/slat elements with a Distributed Electric Propulsion design, enhancing high lift performance and cruise efficiency compared to conventional pylon-mounted DEP configurations. Starting from a baseline configuration determined from pretest Computational Fluid Dynamics (CFD) analyses, a parametric study was performed to determine the influence on the aerodynamic characteristics (𝐶𝑙 , 𝐶𝑥, and 𝐶𝑚). The study involved variations in flap settings, slat angles, overlap, propeller tilt, and propeller position. The impact of Reynolds number, …

On Progress In Exploring Controlled Viscous Limit-Cycle Oscillations In Modified Glauert Airfoil, Ethan Deweese, Lap Nguyen, Erik Vataker, William Mackunis, Vladimir Golubev, Ron Efrati, Oksana Stalnov

Publications

The paper reports on the progress in the development of a novel robust, nonlinear flow control technology that employs an array of synthetic-jet actuators (SJAs) embedded in 2-DOF, elastically mounted, optimized Modified Glauert (MG) airfoil design in order to control limit cycle oscillations (LCO) at low subsonic flow regimes. The focus here is on the conceptual design of the wind energy harvesting system that employs, e.g., a piezoelectric device to extract energy from plunging LCO, with the closed-loop controller being capable to sustain the required LCO amplitudes over a wide range of wind speeds. The current high-fidelity studies first include …

Experimental Environmental Profiles And Sloshing Dynamics Aboard Zero-G Aircraft, Pedro J. Llanos, Sathya Gangadharan, Kevin Crosby

Publications

This study presents the results of a parabolic flight experiment to study the sloshing dynamics of the magneto-active propellant management device experiment. This device utilizes a magnetoactive membrane and magnets located external to the tank to effectively damp the liquid free surface motion. This research work establishes a benchmark with sloshing analytical formulation and sensor calibration methods that can be used to characterize future research parabolic flights while providing important environmental profiles measured during flight, such as accelerations, pitch angle, velocity, temperature, total volatile content, carbon dioxide, relative humidity, magnetic field, and radiation. Correlation between these flight variables and the …

Interpersonal Skills In A Sociotechnical System: A Training Gap In Flight Decks, Kimberly Perkins Atp, Fraes, Sourojit Ghosh, Crystal Hall Phd

Journal of Aviation/Aerospace Education & Research

This research analyzed the perceptions of interpersonal skills on established aviation safety models, Crew Resource Management (CRM), and Threat and Error Management (TEM) using feedback from industry pilots. The flight deck is a sociotechnical system where much research has focused on the technical aspect, whereas we spotlight its socio aspect. The aviation industry must invest in training pilots on interpersonal skills to enhance safety through increased efficacy of safety models integrated throughout existing training programs. A 34-question survey was disseminated across both commercial and business aviation pilots (N=822). We explored three research questions regarding pilots’ perceived training on interpersonal skills …

Evaluating The Effectiveness Of Game-Based Virtual Reality In Satellite Ground Control Operations Education And Training, Lana Laskey, Joseph R. Keebler, Paul M. Cairns, Geovanny Lopez

International Journal of Aviation, Aeronautics, and Aerospace

There is increased global demand for satellite amenities such as navigation, communications, weather reporting, disaster management, agricultural operations, or humanitarian assistance. The growing demand for satellite technology amplifies the need for highly trained satellite operators. Traditional simulation training methods typically utilize two-dimensional computer displays. However, training approaches involving game-based instruction and immersive virtual reality have shown benefits when integrated with complex disciplines and may provide an advanced training alternative for satellite operators. Game-based instruction enhances user motivation and cognitive engagement, while immersive virtual reality promotes user presence and prolonged cognitive engagement. The combination of these two training methods, noted as …

Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard Ph.D., Austin T. Walden Ph.D., Paul J. Thomas Ph.D.

Journal of Aviation/Aerospace Education & Research

Increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations: 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) developing an embedded machine learning framework. Data cleanup and …

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 …

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 …

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 …

Metal Organic Framework Modifications Of Structural Fibers, Marwan Al-Haik

Publications

A reinforced carbon composite can include a carbon sub­strate and a metal organic framework bonded to the carbon substrate. For example, a reinforced carbon composite can include a first layer, a second layer, and a resin adhered to the first layer and the second layer. The first layer can include a carbon substrate and a metal organic framework bonded to the carbon substrate. The second layer can include a carbon substrate and a metal organic framework bonded to the carbon substrate.

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 …

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 …

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. …

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 …

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, …

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. …

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 …

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 …