Physical Sciences and Mathematics Commons^™

Space Radiation Assessment And Mitigation: Meeting The Growing Demand For Shielding Solutions By Enhancing Models And Exploring Novel Shielding Opportunities, M. Laura Sorgi Johann

Doctoral Dissertations and Master's Theses

The rapid growth of satellite technology and the increasing presence of vulnerable technology and human life in space have highlighted the need for improved shielding materials. Industry standard protocols for shielding are being pushed to their limits as we gain a deeper understanding of the harsh space environment and as chip sizes approach the scale of radiation wavelengths. Furthermore, the commercialization of space is attracting interest from industries such as pharmaceuticals and semiconductor crystal growing, as they explore the potential benefits of zero-gravity production environments. However, the eagerness to develop lighter shielding and the lack of consideration for existing tools …

An Integrated Space Test Lexicon: A Taxonomy For The Integrated Test And Evaluation Of Space Systems, Stephen Tullino, Andrew Keys, Robert A. Bettinger, Amy M. Cox, David R. Jacques

Faculty Publications

The proposed Integrated Space Test Lexicon is intended to amalgamate the numerous definitions of integrated (IT or IT&E), development test (DT or DT&E), and operational test (OT or OT&E) into unified, service-wide definitions, aligned with the Space Test Enterprise Vision. Refining such definitions will help distill the core characteristics of these fundamental test types to first identify space system activities composing what is traditionally known as DT and OT, then to provide a means of how these activities fit into the IT paradigm and support space system development. In forging a common understanding of how DT and OT support space …

Optimization Of A Plate Beam System For Energy Harvesting Using A Piezoelectric Material, Jose Manuel Almendros Espantaleon

Doctoral Dissertations and Master's Theses

With a continuously growing demand for power, driven by the need to reduce our environmental footprint, this research provides an examination of the potential of energy harvesting with smart materials technology and its practical applications. The energy harvesting system considered here works on generating energy through vibrations of a piezoelectric material beam which will undergo sustained vibrations due to flow of air over its surface. It is assumed that sustained limit cycle oscillations of this system will occur at the flutter velocity. This research creates an optimization framework to obtain the best values of parameters that will result in the …

New Frontier In Race For Deep Space Exploration: Lunar Water Resources, Yong Wei, Honglei Lin, Fei He, Hui Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Deep space exploration has become the commanding heights of science and technology competition. Since the beginning of the 21st century, China has successfully completed the lunar exploration missions of “orbiting, landing, and returning” in just twenty years, and upgraded to a new roadmap of “survey, construction, and utilization”. Meanwhile, lunar exploration worldwide has shown a trend towards normalization and commercialization. The research on lunar water resources has sparked widespread interest and intense competition among countries and space agencies, marking a new focus in human’s deep space exploration. The exploration of lunar water can help reveal crucial processes in the formation …

Winning Battle For Key And Core Technologies In Emerging Fields—Inspiration Based On 863 Program Related Projects, Guangzu Bai, Li Li, Hongfei Meng, Qiang Wang, Xiaoyang Cao, Anrong Liu, Bo Cheng, Mimi Zhan, Jing Li, Leiei Cui, Xiangwan Du

Bulletin of Chinese Academy of Sciences (Chinese Version)

Emerging technology fields have become the main battleground for strategic competition among major powers today, with key and core technologies serving as crucial approach in shaping a nation’s international competitive advantage. This study, from the perspective of national strategy, profoundly understands the significant importance of winning the key and core technology battle in emerging fields. Based on this understanding, it starts with a comparison between the implementation background of the 863 Program and the current reality. It systematically summarizes valuable experiences from projects aimed at advancing key and core technologies in emerging fields, and puts forward reflections and suggestions for …

Planetary Exploration Via Fully Automatic Topological Structure Extraction Using Adaptive Resonance, Jonathan Kissi

Electronic Thesis and Dissertation Repository

Renewed interest in Solar System exploration, along with ongoing improvements in computing, robotics and instrumentation technologies, have reinforced the case for remote science acquisition systems development in space exploration. Testing systems and procedures that allow for autonomously collected science has been the focus of analogue field deployments and mission planning for some time, with such systems becoming more relevant as missions increase in complexity and ambition. The introduction of lidar and laser scanning-type instruments into the geological and planetary sciences has proven popular, and, just as with the established image and photogrammetric methods, has found widespread use in several research …

A Comprehensive Investigation Of The Influence Of Geometric Structure On The Shape Memory Performance Of Nafion, Jade Thomas

Mechanical Engineering Undergraduate Honors Theses

While perfluorosulfonic acid (PFSA) membranes have primarily been used in fuel cells due to their chemical, thermal, and mechanical stability, one PFSA, Nafion, boasts two unique characteristics: a broad glass transition (~55 °C to 130 °C) and a temperature-persistent electrostatic network. The combination of these two characteristics endows Nafion with exceptional shape memory properties – the ability of a material to morph and transform into pre-programmed shapes when exposed to an external stimulus – with enhanced permanent shape memorization, and a potentially near-infinite number of temporary shape memorization. This study focused on expanding the base of knowledge surrounding Nafion’s shape …

Blade Design And Validation Of Hydrokinetic Turbine To Harvest Water Current Energy, Setare Sadeqi

University of New Orleans Theses and Dissertations

The innovative aspect of this research lies in the careful integration of cutting-edge technologies throughout the entire process of designing, fabricating, and testing the carbon fiber propeller for the 3-bladed horizontal axis ocean current turbine (OCT). SolidWorks software played a pivotal role in the initial design phase, enabling a meticulous and precise modeling of the propeller's geometry. The utilization of SolidWorks allowed for a detailed exploration of various design parameters, ensuring that the propeller's structure and form were optimized for performance in ocean current conditions. Moving beyond the realm of virtual design, the choice of carbon fiber as the fabrication …

Towing Tank Trials Of Hydrokinetic Turbine Scale Model To Support Marine Energy System Verification, Shahab Rouhi

University of New Orleans Theses and Dissertations

In response to the escalating demand for sustainable energy solutions and the critical reevaluation of conventional fossil fuels due to environmental concerns, this dissertation embarks on a comprehensive exploration of hydrokinetic energy as a promising alternative. The study delves into the underexplored domain of hydrokinetic energy, leveraging innovative methodologies for effective utilization and harnessing, particularly through the development and investigation of hydrokinetic turbines.

In the realm of hydrokinetic energy conversion, our research has exclusively concentrated on horizontal-axis turbines, distinct from other turbine configurations. Noteworthy is the adaptation of a conventional horizontal-axis wind turbine for water currents, revealing enhanced performance through …

Analysis Of Additively Manufactured Inconel 718 Combustion Behavior In Promoted Oxygen Environments, Dominic George Dieguez

Open Access Theses & Dissertations

Promoted combustion testing is a vital tool for engineers to establish the combustion and flammability characteristics of materials (metallic or otherwise) in oxygen enriched environments. Historically, much of the established data for metallic promoted combustion has been with regards to materials in their cast and wrought forms. However, with the emergence of additive manufacturing as a preferred method of fabrication, the need exists to evaluate how metals in that form behave. Recent testing has demonstrated that even if a metal or alloy is nominally the same with regards to chemistry, flammability between samples in the wrought form can differ significantly …

A Comprehensive Investigation Of The Influence Of Geometric Structure On The Shape Memory Performance Of Nafion, Jade Thomas

Physics Undergraduate Honors Theses

While perfluorosulfonic acid (PFSA) membranes have primarily been used in fuel cells due to their chemical, thermal, and mechanical stability, one PFSA, Nafion, boasts two unique characteristics: a broad glass transition (~55 °C to 130 °C) and a temperature-persistent electrostatic network. The combination of these two characteristics endows Nafion with exceptional shape memory properties – the ability of a material to morph and transform into pre-programmed shapes when exposed to an external stimulus – with enhanced permanent shape memorization, and a potentially near-infinite number of temporary shape memorization. This study focused on expanding the base of knowledge surrounding Nafion’s shape …

Machine Learning-Based Gps Jamming And Spoofing Detection, Alberto Squatrito

Doctoral Dissertations and Master's Theses

The increasing reliance on Global Positioning System (GPS) technology across various sectors has exposed vulnerabilities to malicious attacks, particularly GPS jamming and spoofing. This thesis presents an analysis into detection and mitigation strategies for enhancing the resilience of GPS receivers against jamming and spoofing attacks. The research entails the development of a simulated GPS signal and a receiver model to accurately decode and extract information from simulated GPS signals. The study implements the generation of jammed and spoofed signals to emulate potential threats faced by GPS receivers in practical settings. The core innovation lies in the integration of machine learning …

Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy

Computer Science Faculty Research & Creative Works

Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …

Development Of On-The-Fly Quasi-Steady State Approximation For Chemical Kinetics In Cfd, Abhinav Balamurugan

Doctoral Dissertations and Master's Theses

This study analyzes the feasibility of On-The-Fly Quasi-Steady-State Approximation (OTF-QSSA) application for solving chemical kinetics within Computational Fluid Dynamics (CFD) simulations, aiming to reduce the computational demand of detailed mechanisms. An algorithm that dynamically identifies and designates Quasi-Steady-State (QSS) species at specific grid locations and instances during the simulation was developed. With this information, our method pseudo-delays the advancement of concentrations for these QSS species—effectively setting their rate of concentration change to zero for a set number iteration before updating using the detailed mechanism and thereby omitting the computationally intensive processes typically required for their calculation during those skipped iteration. …

Application Of The Fokker-Planck Equation For Quantifying Initial Condition Uncertainty Of Reversible Dynamic Systems, Troy S. Newhart

Mechanical & Aerospace Engineering Theses & Dissertations

Characterizing the behavior of dynamic systems requires the inclusion of initial conditions to propagate behavior forward in time. More realistic representations of system behavior quantify uncertainty about the initial conditions to assess sensitivity, reliability, and other stochastic response parameters. In many engineering applications, the uncertain initial conditions may be unknown given a desired response. This research applies the Fokker-Planck equation to reversible dynamic systems of select multi-dimensional nonlinear differential equations as a means for predicting the uncertainty about initial conditions. An alternating directions implicit numerical scheme is used to numerically solve the Fokker-Planck equation for both forward and reversed equations …

A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes

Graduate Industrial Research Symposium

The genetic perturbations caused by spaceflight on biological systems tend to have a system-wide effect which is often difficult to deconvolute it into individual signals with specific points of origin. Single cell multi-omic data can provide a profile of the perturbational effects, but does not necessarily indicate the initial point of interference within the network. The objective of this project is to take advantage of large scale and genome-wide perturbational datasets by using them to train a tuned machine learning model that is capable of predicting the effects of unseen perturbations in new data. Perturb-Seq datasets are large libraries of …

Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor

Faculty Publications

Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …

Extraterrestrial Life: The Possibility Of A Human-Alien Interaction, Ariana M. Piscoya

CAFE Symposium 2024

We all have heard of at least one case where someone assured having seen a flying extraterrestrial object. There are thousands of thousands of videos we can find online that “prove” the existence of aliens. In the hypothetical case where aliens are really out there, why haven't we been able to talk to them and look at them face-to-face? A human-extraterrestrial interaction has not yet been achieved for two reasons. First, alien energy is much more powerful than that of humans, so it would require thousands of thousands of years for the human race to develop a technology able to …

An Enhanced Deep Autoencoder For Flight Delay Prediction, Desmond B. Bisandu Phd, Dan Andrei Soviani-Sitoiu Msc, Irene Moulitsas Phd

Journal of Aviation/Aerospace Education & Research

Accurate and timely flight delay prediction cannot be overemphasized because of the ever-increasing demand for air travel and its importance in deploying intelligent transportation systems. Nonetheless, there has not been a universal solution to the problem, as more intelligent flight decision systems are required for the aviation industry's future growth. Existing flight delay classification and prediction approaches are mainly shallow traffic models and do not satisfy many applications in the real world. Our motivation to rethink the deep architecture model for predicting flight delays emanates from the problem. In this research, we proposed a technique that modified stacked autoencoder architecture …

Applications Of Ai/Ml In Maritime Cyber Supply Chains, Rafael Diaz, Ricardo Ungo, Katie Smith, Lida Haghnegahdar, Bikash Singh, Tran Phuong

School of Cybersecurity Faculty Publications

Digital transformation is a new trend that describes enterprise efforts in transitioning manual and likely outdated processes and activities to digital formats dominated by the extensive use of Industry 4.0 elements, including the pervasive use of cyber-physical systems to increase efficiency, reduce waste, and increase responsiveness. A new domain that intersects supply chain management and cybersecurity emerges as many processes as possible of the enterprise require the convergence and synchronizing of resources and information flows in data-driven environments to support planning and execution activities. Protecting the information becomes imperative as big data flows must be parsed and translated into actions …

Autonomous Strike Uavs In Support Of Homeland Security Missions: Challenges And Preliminary Solutions, Meshari Aljohani, Ravi Mukkamala, Stephan Olariu

Computer Science Faculty Publications

Unmanned Aerial Vehicles (UAVs) are becoming crucial tools in modern homeland security applications, primarily because of their cost-effectiveness, risk reduction, and ability to perform a wider range of activities. This study focuses on the use of autonomous UAVs to conduct, as part of homeland security applications, strike missions against high-value terrorist targets. Owing to developments in ledger technology, smart contracts, and machine learning, activities formerly carried out by professionals or remotely flown UAVs are now feasible. Our study provides the first in-depth analysis of the challenges and preliminary solutions for the successful implementation of an autonomous UAV mission. Specifically, we …

Speculative Anisotropic Mesh Adaptation On Shared Memory For Cfd Applications, Christos Tsolakis, Nikos Chrisochoides

Computer Science Faculty Publications

Efficient and robust anisotropic mesh adaptation is crucial for Computational Fluid Dynamics (CFD) simulations. The CFD Vision 2030 Study highlights the pressing need for this technology, particularly for simulations targeting supercomputers. This work applies a fine-grained speculative approach to anisotropic mesh operations. Our implementation exhibits more than 90% parallel efficiency on a multi-core node. Additionally, we evaluate our method within an adaptive pipeline for a spectrum of publicly available test-cases that includes both analytically derived and error-based fields. For all test-cases, our results are in accordance with published results in the literature. Support for CAD-based data is introduced, and its …

Ai-Based Defect Detection In Aerospace Ultrasonic Signals, Rami Issac Lake

Graduate Research Theses & Dissertations

Ensuring the safety and integrity of materials and structures throughout the manufacturing cycle is a critical concern across various industries, including aerospace, automotive, oiland gas, and civil engineering. Non-Destructive Inspection (NDI) techniques allow for the examination of materials without causing damage or alteration, enabling the early detection of potential issues before materials are utilized in the field. The inspection of fuselage composites presents a particular challenge due to their complex structures, diverse materials, and differences in thickness, making defect detection a challenging yet crucial task. Moreover, defects of various types and causes can emerge across all depths of the material …

The Feasibility Of Motion Tracking Camera System For Magnetic Suspension Wind Tunnel Tests, Hisham M. Shehata, David Cox, Mark Schoenenberger, Colin Britcher, Eli Shellabarger, Timothy Schott, Brendan Mcgovern

Mechanical & Aerospace Engineering Faculty Publications

The Entry Systems Modeling (ESM) Program at NASA has actively participated in the re-development of the Magnetic Suspension Balance System (MSBS) at the six-inch subsonic wind tunnel at NASA Langley Research Center. This initiative aims to enhance the MSBS system's capabilities, enabling the testing of stingless entry vehicle models at supersonic speeds. To achieve this, control algorithms are required to ensure magnetic levitation control and stability for models during free-oscillation dynamic responses. Currently, the system relies on electromagnetic position sensors to provide real-time 3 degrees of freedom control of a rigid body. While this approach has proven successful for subsonic …

Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won

Faculty Publications

Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …

Numerical Study Of Owls' Leading-Edge Serrations, Asif Shahriar Nafi, Nikolaos Beratlis, Elias Balaras, Roi Gurka

Physics and Engineering Science

Owls' silent flight is commonly attributed to their special wing morphology combined with wingbeat kinematics. One of these special morphological features is known as the leading-edge serrations: rigid miniature hook-like patterns found at the primaries of the wings' leading-edge. It has been hypothesized that leading-edge serrations function as a passive flow control mechanism, impacting the aerodynamic performance. To elucidate the flow physics associated with owls' leading-edge serrations, we investigate the flow-field characteristic around a barn owl wing with serrated leading-edge geometry positioned at 20° angle of attack for a Reynolds number of 40 000. We use direct numerical simulations, where …

Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt

All Dissertations

Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …

Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad

Theses and Dissertations

Running computer vision algorithms requires complex devices with lots of computing power, these types of devices are not well suited for space deployment. The harsh radiation environment and limited power budgets have hindered the ability of running advanced computer vision algorithms in space. This problem makes running an on-orbit servicing detection algorithm very difficult. This work proposes using a low powered FPGA to accelerate the computer vision algorithms that enable satellite component feature extraction. This work uses AMD/Xilinx’s Zynq SoC and DPU IP to run model inference. Experiments in this work centered around improving model post processing by creating implementations …

Development Of User Interface And Testing Harness, Jacob Amezquita, William Albertini

College of Engineering Summer Undergraduate Research Program

No abstract provided.

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 …