Aerospace Engineering Commons^™

Impact Of Quenching Intensity Conditions On Using A Finite Element Model To Investigate The Microstructure And Hardenability Of Low-Alloy Steel, J. S. Alabi, E. Heidari, M. F. Buchely, K. Chandrashekhara, S. N. Lekakh, R. J. O'Malley, V. Athavale, A. Kumar

Materials Science and Engineering Faculty Research & Creative Works

Quenching is one of the primary processes to improve mechanical properties in steels, particularly hardness. Quenching is well established for different geometries of individually treated steel components; while in-steam quenching of large diameter continuously cast steel bar has several specific features which are difficult and costly to experimentally optimize. the end-quench Jominy test has been used extensively to study the hardenability of different steel grades. Different numerical, analytical, and empirical models have been developed to simulate the Jominy process and to understand quenching of steels. However, it is not straight forward to translate experimental data from Jominy test on instream …

Autonomous Strike Uavs For Counterterrorism Missions: Challenges And Preliminary Solutions, Meshari Aljohani, Ravi Mukkamala, Stephan Olariu

Computer Science Faculty Publications

UAVs are becoming a crucial tool in modern warfare, primarily due to their cost-effectiveness, risk reduction, and ability to perform a wider range of activities. The use of autonomous UAVs to conduct strike missions against highly valuable targets is the focus of this research. Due to developments in ledger technology, smart contracts, and machine learning, such activities formerly carried out by professionals or remotely flown UAVs are now feasible. Our study provides the first in-depth analysis of challenges and potential solutions for successful implementation of an autonomous UAV mission.

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 …

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 …

Venus Balloon Localization: A Map-Aided Navigation Approach Supported By A Single-Satellite, Heath Scott Cottrill

Graduate Theses, Dissertations, and Problem Reports (ETD)

Although Venus and Earth began as twins, possessing comparable size, mass, and composition, past exploration missions have revealed that Venus is now hellishly hot, devoid of oceans, and enveloped in a carbon dioxide-filled atmosphere. To understand when and why this evolutionary divergence occurred, further exploration is required. Today, there is a growing interest in the use of aerial platforms to circumvent the harsh conditions at the surface, which limit the lifetime of landed instruments. In this concept, a single balloon, propelled by the ambient wind field, would operate in the atmosphere at an altitude between 50 and 70 km, where …

Machine Learning-Assisted Multiscale Simulation And Design Optimization Of Composite Jackets Under Low-Velocity Impacts, Masoud Mohammadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

This research presents the development of a data-driven machine learning-assisted approach to simulate and optimize the design of composite materials subjected to low-velocity impacts. It focuses on a specific type of hybrid composite comprised of fiberglass and Kevlar fabrics stitched with Kevlar threads. The study begins by creating a multiscale finite element simulation for the composite under a low-velocity impact, which operates across three scales: microscale, mesoscale, and macroscale. This simulation accepts various inputs, such as different layer configurations and orientations, and provides impact outputs including maximum load and energy absorption capacity and displacement at failure.

Python and MATLAB scripts …

On Uncertainty For Ill-Posed Robot Decision Problems, Jared Joseph Beard

Graduate Theses, Dissertations, and Problem Reports (ETD)

As robots adopt more real world responsibilities, they will be expected to solve more complicated problems. In some cases limited prior knowledge will result in unmodelled environmental conditions; in others, multiple users may have competing perspectives on how to frame a decision problem. Many existing frameworks, namely Markov decision processes (MDP) presuppose users have identified a specific problem with models sufficient to solve or learn a problem. If we wish to extend MDPs to novel problems or those heavily dependent on user feedback, autonomous decision makers must be able to identify limitations in how a given problem is framed and …

Embedded State Estimation For Optimization Of Cislunar Space Domain Awareness Constellation Design, Thomas Henry Clareson

Graduate Theses, Dissertations, and Problem Reports (ETD)

The traffic in cislunar space is expected to increase over the coming years, leading to a higher likelihood of conjunction events among active satellites, orbital debris, and non-cooperative satellites. This increase necessitates enhanced space domain awareness (SDA) capabilities that include state estimation for targets of interest. Both Earth surface-based and space-based observation platforms in geosynchronous orbit or below face challenges such as range, exclusion, and occlusion that hinder observation. Motivated by the need to place space-based observers in the cislunar space regime to overcome these challenges, this paper proposes a cislunar SDA constellation design and analysis framework that integrates state …

Enhancement Of The Performance And Emission Attributes For The Diesel Engine Using Diesel-Waste Cooking Oil Biodiesel And Graphene Oxide Nanofluid Blends Through Response Surface Methodology, Medhat Elkelawy, E A El Shenawy, Hagar Alm-Eldin Bastawissi, Mahmoud M. Shams

Mansoura Engineering Journal

This study examined how diesel fuel and waste-cooked oil (WCO) biodiesel blends added by various concentrations of graphene oxide (GO) nanoparticles can effect on the performance and emission characteristics of constant-speed, four-stroke, single-cylinder, water-cooled diesel engines. The GO nanoparticles concentrations are 50,100 and 150 ppm dispersed in different diesel-WCO biodiesel blends are pure diesel fuel (B0), 20% WCO biodiesel and 76% diesel fuel (B20), and 40% WCO biodiesel and 56% diesel fuel (B40). In addition 4% toluene in all blends which used as a surfactant. The diesel engine fueled with these blends and operated at various engine loads are 2, …

Mission-Driven Inverse-Design Of Conventional And Unconventional Airplane Configurations Using Machine Learning, Rohan Srinivas Sharma

Doctoral Dissertations

"A key challenge in airplane design has been the long-desired ability to quickly create an airplane design with specific performance properties. To tackle this problem, researchers have traditionally leveraged design space exploration methodologies to iteratively explore a design space via surrogate models. On the other hand, inverse design is a process wherein performance objectives are fixed while a suitable design for satisfying these requirements is calculated. In recent years, artificial neural networks (ANNs) have been explored as viable surrogate models because traditional surrogate models struggle with the large number of output to input mapping needed for inverse design problems. In …

Analysis Of Variations In Flow-Independent Liquid Jet-In-Crossflow Injections, Michael Scott

Honors Undergraduate Theses

Liquid fuel injection is a critical mechanism for the deliverance of liquid fuel in contemporary aircraft propulsion combustion systems due to its outsized influence in providing optimal combustion conditions and improving overall aircraft efficiency and performance. Despite this, these liquid jet in crossflow (LJIC) systems are highly variable due to conditions in the jet and the surrounding airflow, leading to variability in performance behavior and inconsistency in fuel mixing and combustion efficiency. This has prompted the introduction of solid pintile obstructions of novel designs to provide a more flow-independent fuel injection scheme and decrease variability of the jet properties against …

Kinetic Modeling And Simulations Of Plasma-Surface-Dust Interactions For Lunar Exploration, David Clifford Lund

Doctoral Dissertations

"Due to the recent relevance of NASA’s focus on lunar missions, a better understanding of the lunar plasma-surface-dust environment is vital for their success. The lunar surface, devoid of an atmosphere and a global magnetic field, is directly exposed to solar radiation and solar wind plasma. This exposure leads to the electrical charging of the lunar surface due to the bombardment of solar wind plasma and the emission/collection of photoelectrons. Therefore, this research developed accurate and efficient computational models of plasma-surface-dust interactions and extend a legacy simulation code, namely the Immersed-Finite-Element Particle-in-Cell (IFE-PIC), to a parallel version: Parallel Immersed-Finite-Element Particle-in-Cell …

Efficient Modeling And Simulation For The Aerothermal Analysis Of Particle-Laden Hypersonic Flows, Andrew Hinkle

Doctoral Dissertations

"Standard approaches for simulating hypersonic flows in particle-laden environments have key limitations in practice, such as high cost and numerical noise. In this work, efficient solution strategies for particle-laden hypersonic flows were developed using both Lagrangian and Eulerian models for the particle phase with the focus on investigating spacecraft surface erosion, as well as convective and radiative heat flux augmentation due to atmospheric particulate encountered during planetary entry.

First, an efficient integration strategy for Lagrangian methods, the Trajectory Control Volume (TCV) method, was developed for steady analysis of dilute particle phase problems on general geometries. The TCV method was shown …

Optimizing The Total Life Cycle Of Li-Ion Batteries: From Constant Gradient Charging To Aged Cell Performance Restoration, Kasim Adesegun Adewuyi

Doctoral Dissertations

As demand for Lithium-Ion Batteries (LIBs) have skyrocketed over the past decade, the need for better charging methodologies and recycling methods have become vitally important. At a fundamental level, this dissertation strives to fulfill the green promise of a future without fossil fuels. In order to promote a transition away from fossil fuels, LIBs for vehicles require ultrafast charging times equivalent to a normal vehicle (6 mins). However, this process leads to high volume expansion for next generation electrode materials which causes degradation. Without limiting this factor, the environmental impact shifts from oil rigs to Li mines and landfills. The …

Dynamics Of A 3-D Inlet/Isolator Measured With Fast Pressure-Sensitive Paint, Andrew N. Bustard, Mark E. Noftz, Mitsugu Hasegawa, Hirotaka Sakaue, Joseph S. Jewell, Nicholas J. Bisek, Thomas J. Juliano

Publications

Fast pressure-sensitive paint (PSP) was applied to an inlet/isolator designed using the Osculating Internal Waverider Inlet with Parallel Streamlines (OIWPS) method. The dorsal isolator surface pressure was measured using anodized-aluminum PSP through transparent cast acrylic that makes up the ventral portion of the isolator. Temperature-sensitive paint was utilized to correct for the PSP’s temperature sensitivity. The model was tested under Mach 5.7 flow at Re = 8.5 ×106 /m and 10.2 ×106 /m in the AFOSR–Notre Dame Large Mach-6 Quiet Tunnel (ANDLM6QT) under conventional noise conditions. Flow phenomena, such as shocks originating in the inlet and flow separation at the …

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 …

Fundamentals Of Sustainability, Eva Maleviti

Publications

Fundamentals of Sustainable Aviation is the frst textbook to survey the critical feld of sustainability within the aviation industry. Taking a systems thinking approach, it presents the foundational principles of sustainability and methodically applies them to diferent aviation sectors. Opening with the basics of sustainability, emphasising the Sustainable Development Goals, the book then considers the environmental, economic and social dimensions of aviation. The following chapters apply these insights to aviation design, supply chains, operations, maintenance and facilities. The fnal chapter examines the concept of resilience in sustainable aviation. Overall, the textbook shows how future sustainability can be achieved by making …

Depressurization Characteristics Of Steam-Based Reciprocating Vacuum Pump, Hongling Deng

Dissertations

This dissertation introduces a novel vacuum technology that leverages low-pressure saturated steam and cooling-controlled condensation, offering an efficient way to utilize low-grade thermal energy sources like waste heat, steam, or solar energy. At the heart of this technology is a unique duo-chamber vacuum pump system, featuring a reciprocating piston and a heat-conductive wall, designed to generate a vacuum through steam-condensation and cooling processes.

The core of this research lies in developing and validating mechanistic models for the steam-condensation depressurization process, a complex phenomenon involving phase change and transport mechanisms. Prior to this work, these mechanisms were not sufficiently modeled or …

The Interaction Of The Cotton Piece With The Piles Of The Scrabble Cotton Drum, Fazliddin Egamberdiev, Ilkhom Abbazov, Oybek Kholmuratov, Rashid Kaldybaev

Technical science and innovation

This article presents the results of an analytical study of the process of loosening and cleaning raw cotton from small debris by pileging working bodies of purifiers, on the basis of which directions for further research were chosen to optimize the parameters of the developed pile drum with spherical piles and rubber strips. Cotton entering production contains impurities. The processes of loosening and cleaning the fiber shreds are key in the initial stages of ginning, as they prepare the raw cotton for ginning and directly affect the reliability, productivity of these processes and the quality of the resulting fiber. Weed …

Adaptation Algorithm For Self-Tuning Of Parameters Of Models Of Multi-Stage Flotation Processes, Nilufar Sharifzhanova, Maksadhan Yakubov, Francesco Gregoretti

Technical science and innovation

Modern methods for solving problems of planning the execution of batches of tasks in multi-stage systems are characterized by the presence of restrictions on their dimensionality, the impossibility of guaranteed obtaining better results in comparison with fixed packages for different values of the input parameters of the problem. In the article, the author solved the problem of optimizing the composition of job packages running in multi-stage systems using the branch and bound method. Research has been carried out on various ways to form package execution orders tasks in multi-stage systems (heuristic rules for ordering packages tasks in the sequence of …

An Experimental Investigation Of The New Vibration Viscometer, Jamshidbek Ulugbek Ugli Shamuratov

Technical science and innovation

The characteristics of the new oscillating-plate viscometer have been investigated experimentally. The results obtained are as follows: the resonant frequency of plate oscillation decreases with increasing viscosity; the apparatus constant 𝐾 determined experimentally includes the end and slip effects; the dimensions of the plate should be determined by referring to empirical relations between 𝜌𝜇 and Λ(≡{(𝐸𝑎𝐸)−1}𝑛) for various dimensions of the plate; where 𝜌 is the density, 𝜇 is the viscosity; 𝐸𝑎 the resonant amplitude of plate in the air; E the amplitude of plate in a liquid, and 𝑛 a constant. If the distance between the plate and the …

Indicators Affecting Passenger Service Processes And Their Scientific Interpretation, Maxliyoxon Madaminova Maxamatjon Qizi, Saidazim Amanullayevich Ganihodjayev

Technical science and innovation

Many traffic flow parameters affect the performance of the road network at high voltage. These are low vehicle speeds, high vehicle distances relative to road capacity, and density per unit time (lane occupancy). In turn, a number of factors affect the decrease in traffic speed: the presence of slow-moving vehicles in the stream; pedestrians crossing the road irregularly; increase in traffic flow, etc. The issues of public transportation depend on many factors, each of which requires a separate approach and a complex solution. In large cities around the world, the quality indicators of public transport services, including the issues of …

Multi-Mode Regulation Of The Drying Process Of Industrial Gas, Isamidin Xakimovich Sidikov Pr, Nashvandova Gulruxsor Murot Qizi Phd

Technical science and innovation

Currently, much attention is paid to the issue of energy efficiency of gas processing enterprises. The continuous growth of world prices for energy resources requires constant improvement of the management system, providing the most optimal conditions for the flow of technological processes. A conceptual model of the heat-mass transfer process occurring in the absorber as an object of research has been developed, which characterizes the relationship of the variables involved in the drying process of natural gas, control, measurable and immeasurable, as well as controlled parameters have been selected, which are used to develop and study a mathematical model of …

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 …

Aerodynamic Dimpling For The Nose Cone Of A High-Power Competition Rocket, Graham Geoffrey Monroe

Mechanical Engineering ETDs

This thesis investigates nose cone dimpling for the reduction of the aerodynamic drag of a Level 3 High-Power amateur rocket. Two rocket launches were conducted. The first used a COTS nose cone with a smooth surface. A dimple distribution was created according to dimensions calculated by Sandia National Laboratories’ proprietary Right- Size Dimple Evaluator. A dimpled nose cone, designed with geometry matching the COTS component, was 3D printed. Axial acceleration and barometric pressure data, recorded by an onboard flight computer, were used to calculate and plot the drag coefficient as a function of the Reynolds number for the smooth and …

Modeling Of Frontal Polymerization Of Carbon Fiber And Dicyclopentadiene Woven Composites With Stochastic Material Uncertainty, Ahmadreza Mohammad Sharifi, Dong-Jun Kwon, S. Z. H. Shah, Juhyeong Lee

Mechanical and Aerospace Engineering Faculty Publications

A novel finite element modeling framework is proposed for simulating dicyclopentadiene (DCPD) frontal polymerization in carbon fiber (CF) woven composites. A mesoscale CF/DCPD representative volume element (RVE) model was developed with two triggering directions, resulting in out-of-plane and in-plane DCPD polymerization. The Arrhenius equation coupled with a modified Prout-Tompkins autocatalytic model was used to evaluate the dynamic DCPD polymerization process. The rate and degree of DCPD cure were calculated by the material property uncertainties of DCPD with and without random void inclusions (3% used as a reference in this work). The DCPD frontal polymerization in CF/DCPD composite was strongly influenced …

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 …

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 …

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. …