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Conceptual Aerothermal-Structural Design Space Exploration Using Adaptive Machine Learning
No full textExcerpt: This study presents an active machine learning approach for exploring the conceptual design space of hypersonic air vehicles. Hypersonic vehicles endure extreme thermal loads caused by aerodynamic heating, resulting in a strong coupling between structural performance and aerothermodynamics. Therefore, it is crucial to consider aerothermal-structural interactions from the early stage of conceptual design development
Flexible Supply Chain: Industrial Engineering Optimization Modeling of the Postal Service System
No full textNaimark-spatial families of equichordal tight fusion frames
No full textAn equichordal tight fusion frame (ECTFF) is a finite sequence of equi-dimensional subspaces of a Euclidean space that achieves equality in Conway, Hardin and Sloane\u27s simplex bound. Every ECTFF is a type of optimal Grassmannian code, being a way to arrange a given number of members of a Grassmannian so that the minimal chordal distance between any pair of them is as large as possible. Any nontrivial ECTFF has both a Naimark complement and spatial complement which themselves are ECTFFs. We show that taking iterated alternating Naimark and spatial complements of any ECTFF of at least five subspaces yields an infinite family of ECTFFs with pairwise distinct parameters. Generalizing a method by King, we then construct ECTFFs from difference families for finite abelian groups, and use our Naimark-spatial theory to gauge their novelty
Origami Application and Attitude Control Investigation of Space-Based Mirror System
Get PDFImaging and inspecting Resident Space Objects (RSO) have gained increasing importance in Space Situational Awareness (SSA) missions. These missions are driven by the necessity to perform satellite repairs, refueling, de-orbiting, and orbital debris reduction. However, the challenging lighting conditions in space often hinder these tasks. To overcome this challenge, a novel concept has been proposed—deploying mirrors from servicer satellites. These mirrors would harness solar energy to illuminate dimly-lit RSOs, enabling imaging, inspection, repair, and refueling operations. In this context, servicer satellites play a pivotal role in controlling the reflected light beam and precisely positioning themselves to illuminate RSOs effectively. Notably, these servicer satellites are envisioned as either 12U or 27U CubeSats, compact and versatile spacecraft. To make this concept feasible, extensive research is required to explore the application of origami techniques for folding mirrors into a compact state. Specifically, cubic or rectangular origami flashers are under consideration for CubeSat applications.
The outcomes of this research not only showcase the design, construction, and testing of an operational origami mirror membrane, but also delve into the intricacies of control design. Maintaining a specific attitude throughout a natural motion circumnavigation (NMC) orbit for SSA missions was a focal point of interest in this research. Leveraging optimal control methods for a deputy spacecraft to execute maneuvers within a 2-by-1 ellipse NMC orbit about a chief satellite. This positioning facilitates the application of the mirror and its associated control system. To achieve this, the research incorporates well-established Hill-Clohessy-Wiltshire (HCW) equations for accurately positioning a servicer satellite around an RSO in geosynchronous Earth orbit (GEO). The space-based mirror, is engineered to reflect solar energy at a precise angle. In essence, the research into the attitude controller aims to enable the illumination of an RSO from multiple angles using a servicer satellite, thus ensuring comprehensive coverage of all six sides of the RSO at distinct times. This innovation promises to significantly enhance the effectiveness of satellite mission operations
Enhanced Heuristic Algorithm for Optimal Cislunar Space Situational Awareness Architecture
No full textExcerpt: The goal of this study is to utilize heuristic optimization techniques, such as Genetic Algorithms, to examine near-optimal space-based sensor architectures within the cislunar environment for the space situational awareness (SSA) mission. Specifically, this study introduces an adapted heuristic algorithm for optimizing cislunar SSA architectures
Integrating Blockchain Technology into the Software Development Life Cycle to Satisfy the Software Bill of Materials Requirement for Government Software Systems
Get PDFThis thesis explores the integration of Blockchain Technology (BT) into the Software Development Life Cycle (SDLC) to satisfy the Software Bill of Materials (SBOM) requirement for government software systems. This study begins by synthesizing a standard SDLC definition from various government and industry references, which may provide the foundation for future efforts to standardize software development practices across the government software development community. This study proceeds to define working definitions for the software supply chain (SSC) and software supply chain management (SCM) before introducing and detailing the SBOM requirement as well as providing an overview of prior research regarding SBOMs and the applicability of BT to SCM. Subsequently, by employing Model-Based Systems Engineering (MBSE) techniques, this research leverages BT to propose a dynamic solution that updates SBOM data with each software version change as an integral component of the SDLC, thereby enhancing traceability and security. The findings suggest that this approach not only satisfies needs highlighted by prior BT research efforts, but also addresses concerns detailed in SBOM requirements documents regarding the static nature of SBOMs. This dynamic SBOM solution has the potential to significantly improve software supply chain management and security, offering a foundational framework to future research and analysis
A Staged Framework for LLM-powered Information Extraction in Government Contracts
Get PDFThe manual extraction of meaningful insights and conversion of content into structured forms to enhance document processing require substantial resources and are susceptible to errors. Despite numerous applications of various Natural Language Processing (NLP) models to streamline the manual process, challenges persist due to domain-specific data constraints and the deficiency of annotated data. This study attempts to address these challenges by leveraging a Large Language Model (LLM) to analyze government contracts. Through rigorous evaluation, we demonstrate the LLM’s effectiveness in information extraction and mitigating hallucinations, achieving a 87.86% accuracy in metadata extraction
Long-term Deterioration and Investment Modeling of Water Distribution Infrastructure
Get PDFThe United States Air Force (USAF) and municipal utilities rely on asset management processes to maximize utility of infrastructure assets while decreasing maintenance and repair costs. One of the core tenants of asset management is assessing the condition of the asset, which for water distribution pipes is challenging and costly to obtain. As a result, asset managers often rely upon pipe deterioration modeling using existing data, filling in the gaps when assessments are not available. This thesis uses USAF water distribution network data to develop a series of time-homogenous Markov chain probability models based on two sampling methods and four covariates: diameter, material, both material and diameter, and neither material nor diameter. An estimated Markov chain is obtained via a least square approach and solved via non-linear optimization, and is then used to project the condition of the portfolio. Investment levels are assessed for their impact on condition with pipe replacements costs from RSMeans. The results found that an annual investment of 0.25% of the total plant replacement value of all assets would improve the condition of the network, gradually replacing all pipes in the worst condition. This model can also inform asset management objectives while ensuring quality network performance
Root Cause Analysis for Troop Construction Schedule Delays and Cost Overruns
Get PDFTroop construction can be an effective tool when a project is simple enough to execute projects in a timely and cost effective manner. However, underlying variables plague these projects causing them to miss anticipated deadlines which in return could make them more costly. Significant variables that convey impact to cost and schedule are Equipment Operating Issues, Edits During Construction, Design Flaws, Lack of Communication, Poor User Coordination, Improper Documentation, Inaccurate Submittals, Low Quality Control, and Lack of Experience. Project engineers and project managers must provide effective continuity as well as improve their own competence and situational awareness to effectively mitigate or eliminate the impact these variables will have on a project. Troop construction is used primarily to train personnel when stateside, but to effectively train personnel, the leaders must be confident, knowledgeable, and improve their risk management strategies. Creating uniform practices between squadrons that are effective measures to appropriately communicate requirements and issues will improve overall project success. Troop construction units should improve current processes by using continual feedback from previous work and praising innovation to limit infractions. Units should also look to promoting professional credentialling for personnel to improve competence and reinforce the idea of over-communicating between stakeholders in projects to limit scope creep, construction edits, and programming issues. Ensuring equipment is operational prior to arrival and properly scheduling logistics lowers the likelihood of large schedule delays and cost overruns. Finally, a focus on developing members throughout the chain of command improves not only their competence but the confidence in work leading to better quality in projects as well as managing the risk with variables that directly affect schedule delays and cost overruns