Aerospace Engineering Commons^™

Production Box Cost Estimating Relationships For Dod Avionics, Carla J. Cisneros, Edward D. White, Brandon M. Lucas, Jonathan D. Ritschel, Robert D. Fass, Shawn M. Valentine

Faculty Publications

The authors use historical information obtained from the Cost Assessment Data Enterprise to estimate recurring production unit cost for DoD avionics via cost estimating relationships (CERs). The specific modeled responses include mean unit cost, median unit cost, and the 100th production unit cost (T100) utilizing learning curve theory. For T100, the authors adopt both a multiplicative and an additive error for CER comparison. Recommended CERs consist of the mean unit cost and the T100 utilizing a multiplicative error. Moreover, results reveal that weight has a significant effect on cost as well as a potential underaccounting of real price change or …

Suppression Of Dynamic Aeroelastic Response Of A Semispan Wing Using Traditional And Distributed Sensing, James Ramey

Mechanical & Aerospace Engineering Theses & Dissertations

Characterization and management of aeroelastic effects are a vital part of aircraft design. Mitigation of these effects often includes control systems to suppress the vibrations. Control systems are constantly being developed and improved, with one such avenue of development being new sensing systems that can increase the information fed into the controller. Fiber Optic Strain Sensing (FOSS) technology is one such system that utilizes Fiber Bragg Gratings (FBGs) on a fiber optic cable to sense the strain on structural elements. This system has promise as a high-density feedback device, and the maturation of the technology has allowed assessment of its …

Experimental And Computational Investigation Of Green Laser Propagation Through Turbulent Medium In A Water Tank, Richard Owusu Adansi

Open Access Theses & Dissertations

Turbulence medium poses significant challenges to the propagation of laser beams, impacting applications such as free-space optical communication, remote sensing, and laser weapons systems. Therefore, comprehending and mitigating turbulence effects are vital for enhancing the performance of these systems. Analysis of a strong turbulence impact on electromagnetic wave propagation requires extensive knowledge of the Earth's atmospheric and Oceanic phenomena and Maxwell's electromagnetic theory of light as a propagating wave of electric and magnetic fields. Optical systems' propagation often encounters Strong Turbulence, causing interference and diffraction. Nonetheless, light propagation through randomly fluctuating media has been an exciting and active area of …

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

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 …

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 K. Tullino, Andrew S. 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 …

Pkt-Sin: A Secure Communication Protocol For Space Information Networks With Periodic K-Time Anonymous Authentication, Yang Yang, Wenyi Xue, Jianfei Sun, Guomin Yang, Yingjiu Li, Hwee Hwa Pang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Space Information Network (SIN) enables universal Internet connectivity for any object, even in remote and extreme environments where deploying a cellular network is difficult. Access authentication is crucial for ensuring user access control in SIN and preventing unauthorized entities from gaining access to network services. However, due to the complex communication environment in SIN, including exposed links and higher signal delay, designing a secure and efficient authentication scheme presents a significant challenge. In this paper, we propose a secure communication protocol for SIN with periodic k-time anonymous authentication (named PkT-SIN) that allows satellite users to anonymously authenticate to ground stations …

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 …

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 …

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 …

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

LSU 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 …

Relations Between Printability And Rheology In A Ceramic Paste Extrusion Process, Nicholas Durand

Open Access Theses & Dissertations

Ceramic additive manufacturing (AM) uses the same fundamentals as material extrusion (MEX) that utilizes polymers or resins for printing applications. Ceramic AM uses the same process of slicing an STL file to determine a toolpath for the printer that will facilitate material deposition to manufacture full parts; ceramic AM also provides a low-cost advantage when compared to processes that require high powered lasers for melting metal powders or heated nozzles used for dispensing thermoplastics. Despite having the similar design freedom and ability for rapid prototyping that other printing methods benefit from with the addition of low cost, ceramic AM has …

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 …

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

LSU 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 …

Performance Effects Of Dissociated Hydrogen In Nuclear Thermal Propulsion Engines, Richard Adam Gorrell

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nuclear thermal propulsion (NTP) research considers hydrogen dissociation as negligible to design and analysis of propulsion engines. This study reintroduces chemically reacting flow to NTP engine analysis for investigation of the dissociation effect on engine performance. A first-principles approach observes the basic chemical mechanism and reaction within the high-speed, high-temperature NTP flow to baseline expected atomic hydrogen levels and validate equilibrium. A surface reaction study looks into hydrogen absorption through dissociation and its effect on the boundary layer, and bulk flow. For total performance, the resulting dissociated flow is analyzed through nozzle expansion and performance metrics calculated.

All historic reactor …

System Identification For Motion Control Of Unmanned Aerial Vehicles Platform, Raj Ramesh Agarwal

Theses and Dissertations

Comprehensive research on Unmanned Aerial Vehicles (UAV) system identification for motion control parameters is presented in this thesis, with a focus on the necessity of precise control and improved performance. Using Pseudorandom Binary Sequence (PRBS) and Normally Distributed Random Numbers, it presents a unique technique for excitation of UAV dynamic systems. It also shows how effective random signals are in time-domain identification for precise control in a range of flying circumstances. The piece of research includes a thorough analysis and implementation of various approaches and its further improvements, highlighting the benefits and drawbacks of each. These approaches include the free …

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 …

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. …

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 …

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 …

Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen

Faculty Publications

It has been recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth’s anomaly magnetic field immersed in overwhelming complex signals for magnetic navigation in a GPS-denied environment. The accuracy of the detected anomaly field corresponds to a positioning accuracy in the range of 10–40 m. To increase the accuracy and reduce the uncertainty of weak signal detection as well as to directly obtain the position information, we exploit the machine-learning model of random forests that combines the output of multiple decision trees to give optimal values of the physical …

Standardization Of Risk Classifications For Unmanned Space Vehicle Missions, Collin A. Gwaltney

Theses and Dissertations

This paper seeks to model risk classification levels (A-D) for 122 Space Vehicle programs. Models include multinomial logistic regression as well as random forest, a machine learning technique based on decision trees. We use independent variables (IVs) which are theoretically correlated to risk class for the regression and one random forest model. We then include all IVs and allow the random forest technique to use those which provide the most information on risk class before paring down the number of IVs to only 7. We show that the accuracy of predictions increases from 62% to 87% by using random forest …

Data And Intelligent Driven Space Science Experimental Research: New Exploration Under Ai4s Paradigm, Shengyang Li, Kang Liu, Yunfei Liu, Chufan Lai

Bulletin of Chinese Academy of Sciences (Chinese Version)

As artificial intelligence (AI) technology continues to advance, it is revolutionizing various scientific fields, giving rise to a new research paradigm known as AI for Science (AI4S). This study highlights the unique multidisciplinary advantages of AI in space science experiments conducted under microgravity conditions. It provides a comprehensive analysis of AI-driven approaches to multimodal space science experiment data pattern mining, domain knowledge extraction, interdisciplinary knowledge integration, and cognitive intelligence. The study reveals AI’s substantial potential to enhance intelligent scientific research, cognition, and discovery within the realm of space science experiments. The findings suggest that data-driven space science research, as a …

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 …

Development Of Advanced Instrumentation For High-Enthalpy Flow Characterization For The Onr-Uta Arc-Jet ”Leste” Facility, Ian Raybon

Mechanical and Aerospace Engineering Dissertations - Archive

Sustained hypersonic flight is an exceedingly challenging task comprised of a myriad of complex physical processes. At hypersonic speeds, which is defined by the presence of unique phenomena like high-temperature nonequilibrium flow, viscous and vorticity interactions, and thin shock layers, which are not seen in supersonic, transonic, or subsonic vehicles, the vehicle design is principally driven by the high levels of aerodynamic heating caused by the conversion of kinetic energy to internal energy. Gaining an understanding of how these physical processes interact with each other is required to develop a design methodology for this class of vehicles. Arc-jet wind tunnels …

Latent Space Dynamics Learning For Stiff Collisional-Radiative Models, Xuping Xie, Qi Tang, Xianzhu Tang

Mathematics & Statistics Faculty Publications

In this work, we propose a data-driven method to discover the latent space and learn the corresponding latent dynamics for a collisional-radiative (CR) model in radiative plasma simulations. The CR model, consisting of high-dimensional stiff ordinary differential equations, must be solved at each grid point in the configuration space, leading to significant computational costs in plasma simulations. Our method employs a physics-assisted autoencoder to extract a low-dimensional latent representation of the original CR system. A flow map neural network is then used to learn the latent dynamics. Once trained, the reduced surrogate model predicts the entire latent dynamics given only …