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Challenges That Inhibit SBIR Commercialization: The Small Businesses’ Perspective
Get PDFEvery year the United States invests $3.2B in the Small Business Innovation Research (SBIR) Program. The program seeks to promote innovation among the nation’s small businesses. This research considers challenges faced by small businesses working with the DoD, which accounts for half of the annual SBIR investment. We surveyed participating businesses with open-ended questions to understand their perspectives. Our data consists of 286 responses from firms that have held Air Force SBIR contracts. Using Qualitative Content Analysis, we identified five categories of challenges: SolverSeeker Disconnect, Funding, Engagement, Processes, and Seeker Education. Furthermore, the results of a statistical analysis indicated that small businesses experienced in commercialization were more likely to emphasize the challenges of engaging stakeholders and identifying customers. The small business perspective reveals underexplored challenges. With this new insight, we can inform SBIR policies to improve the program’s effectiveness
Cloud One Migration Schedule Drivers and Schedule Growth
Get PDFCloud One, chartered in 2017 under the guidance of Air Force Life Cycle Management Center (AFLCMC) leadership, continues to serve as the USAF’s leading cloud services and hosting platform by providing secure computing environments, application migration assistance, and data management. Prior research has yielded qualitative insights regarding Cloud One’s personnel requirements, application of technical performance, requirements fulfillment, security risks, and various other cost metrics, but schedule improvement recommendations based on the quantitative analysis of migration schedule data has yet to be provided. This research identifies trends within migration sprint schedules and completed schedule data for Cloud One’s completed application migrations. Goals include identifying schedule deviation and schedule duration trends while attempting to account for said trends using application specific attributes. Additionally, the research attempts to construct a schedule estimating relationship (SER) capable of predicting total migration duration to reveal schedule drivers responsible for schedule variation and improve future schedule planning. Overall, the findings support that schedule deviations exist between planned and actual schedule data for one or more migration processes, the schedule deviations within processes can explain the total schedule deviation for the entirety of the migration timeline, and that application specific attributes are unlikely to influence the total duration of the migration. Finally, the research was unable to construct a reliable model using stepwise regression approach given various data limitations
Advanced Oxidation of Tert-Butanol with Ultraviolet Light Emitting Diodes and Hydrogen Peroxide
Get PDFTert-butanol (TBA), a versatile chemical widely used in industrial processes, poses exposure risks through inhalation, ingestion, and skin contact. Environmental contamination, often from industrial activities, emphasizes the importance of robust waste management and monitoring to protect water supplies from potential TBA migration and ensure drinking water safety. This study employed hydrogen peroxide (H2O2): TBA molar ratios of 100, 200, 400, and 500:1 in a Continuous Flow Stirred-Tank Reactor (CSTR) with UV-LED as the TBA degradation mechanism in an Advanced Oxidation Process (AOP). The UV-LEDs and H2O2 were synergistically employed to generate hydroxyl radicals in an advanced oxidation process. Gas chromatography–mass spectrometry (GCMS) was employed for concentration analysis, providing insight into mass ratios, while Density Functional Theory (DFT) was utilized to identify potential reaction byproducts and elucidate TBA degradation pathways. The findings highlight the efficacy of UV-LED and H2O2 synergy in degrading TBA, yet the studied molar ratios exhibit limited impact, achieving a 40% reduction in concentration. The DFT analysis predicted that acetone and 2-methylpropene were likely degradation products during the advanced oxidation process. Diversifying the investigation into various oxidation pathways for TBA is important to gain a comprehensive understanding of its degradation mechanisms. This exploration can contribute valuable insights for optimizing treatment processes and addressing potential challenges associated with TBA removal. To the best of the author\u27s knowledge, this study represents the inaugural application of a blend of experimental observations and DFT to examine the TBA removal process in an AOP
Level 2 Work Breakdown Structure Cost Growth Analysis
Get PDFThis thesis analyzes first and second level WBS elements of 59 historical USAF Acquisition Category I RDT&E programs for accuracy and influence on the overall program cost growth. For the accuracy analysis portion, the mean, 15th, and 85th percentiles of common practice estimates at completion are compared with the same percentiles for distributions generated using the data. The results reveal a trend of substantial underestimation of risks associated with cost overruns. For the influence portion, this thesis analyzes the effect that cost growth trends of different second level WBS elements have on cost growth of the overall program through regression analysis. This analysis focuses on the ST&E WBS element, identified as commonly neglected by decision makers yet significantly influential on program cost growth in research by Rosado (2011). This analysis provides a more comprehensive data set, a focus on USAF RDT&E programs, and analysis of other second level WBS elements. The results establish ST&E as the only WBS element analyzed that significantly predicts program cost growth and is highly influenced by improved cost and risk planning
Development of a Metric to Quantify Facility Hardening
Get PDFThis research investigates the intricate aspect of infrastructure resilience, focusing on the distinction between hardening and resilience. Hardening, often used interchangeably, with enhancing resilience, involves strategies to strengthen facilities, networks, or systems against various threats. Despite its recognized importance in mitigating physical disruptions and enhancing facility functionality amid different threats, a significant vagueness persists in quantitatively defining hardening. This thesis addresses this gap by developing a quantifiable metric for facility hardening, separate from general resilience measures. The study begins by exploring the historical context of facility hardening, linked to catastrophic events and the need for resilient infrastructure. It explores various definitions and applications of hardening, highlighting its critical role in infrastructure management. The research identifies significant gaps in existing literature, particularly the lack of a standardized, quantifiable metric for hardening. Addressing this, the thesis proposes a novel hardening metric to precisely assess hardening interventions, offering a unique tool for evaluating, comparing, and enhancing infrastructure robustness against threats. This work contributes to the field of infrastructure resilience by providing a measure for hardening, using existing and available facility characteristic data that is shown to be a significant predictor of failure during an extreme event
Estimating Stimulated Raman Scattering Noise in CWDM O-Band Channels Induced by Two Classical DWDM Sources in a Quantum Network Fiber Segment
Get PDFThe purpose of this research is to estimate the stimulated Raman scattering noise induced in CWDM O-band channels by two DWDM classical sources in a terrestrial quantum optical network containing classical and quantum optical signal coexistence in the same fiber segment. A use case is defined and analyzed which extracts a single fiber segment from a notional Bell state measurement found in a notional terrestrial quantum network. A stimulated Raman scattering noise model is employed in a Python simulation to estimate and rank-order the five O-band channels with the least amount of relative induced stimulated Raman scattering noise when given two classical DWDM classical communications sources. The results of the research provide initial decision support for selecting CWDM O-band channels for quantum communications in a classical-quantum coexistence network when using the White Rabbit protocol using two classical DWDM classical communications sources
Performance Analysis of Intel Total Memory Encryption - Multi-Key
Get PDFSecure cloud computing is an evolution in data management and security. As cloud-based services, ranging from storage solutions accessible from mobile devices to complex applications, become integral to daily operations, securing data throughout the life cycle of its use is essential. In response, hardware companies are advancing encryption and security technologies to protect data in use to thwart unauthorized access while mitigating the performance impacts of security and encryption features. This thesis addresses TME-MK performance when enabled and disabled on a server using all host threads and with three virtualized environments assigned separate unique threads each. The primary aim is to quantify performance characteristics of TME-MK on specific parts of computer architecture
Enhancing Port Efficiency and Lead Time Reduction through Predictive Analysis: A Case Study of Container Management at Khalifa bin Salman Port
Get PDFKhalifa bin Salman Port (KBSP), a key pillar in Bahrain\u27s maritime infrastructure, is the focal point of this study, highlighting the significant role of predictive analytics in optimizing port operations. This thesis analyzes container throughput data from 2017 to 2022, provided by Bahrain\u27s Ministry of Transportation database. This data forms the basis for forecasting the 2023 throughput. The study thoroughly compares these predictions with the actual 2023 data, assessing the predictive model\u27s accuracy. The findings underscore the importance of predictive analytics in strategic decision-making for port management, focusing on enhancing operational efficiency and reducing lead times. This research offers a comprehensive guide for port congestion at Khalifa bin Salman Port
Simulating Human-Autonomous Aircraft Teams in an Anti-Access Area Denial (A2AD) Environment
Get PDFThe role of autonomy has evolved recently, demanding tighter integration between human and autonomous systems, particularly in highly contested A2AD environments. Near-peer adversaries have modernized their integrated air defense systems (IADS), diminishing the current advantages of the United States Air Force. To regain air dominance, efforts like the Collaborative Combat Aircraft (CCA) program are underway, aiming to deploy unmanned autonomous alongside manned next-generation fighter aircraft. This research assesses various operational concepts, focusing on autonomous tactics post-manned fighter loss, strike timing of independent teams, and weapon configuration observability. Using the Advanced Framework for Simulation, Integration and Modeling (AFSIM), an agent-based model was developed to simulate friendly human-autonomous teams engaging enemy IADS assets in A2AD tasks. Statistical analysis via full factorial design of experiments evaluates the effects of different factors associated with the friendly teams, providing insights into lethality and survivability metrics
A Reinforcement Learning Self-Play Approach for Informing Wargaming Analysis & Development
Get PDFThe integration of RL into wargames to learn strategic and operational insights is of interest to the United States Air Force. This thesis explores the application of a RL SARSA(λ) algorithm to the wargame Stratagem MIST. The primary objective is to select air and ground combat policies for the Blue Agent to effectively counter various opponent strategies across different terrains. This testing enables a comprehensive evaluation of the Blue Agent’s adaptability and performance under varying combat conditions. The use of basis functions, linear value function approximations, and specific air and ground strategies simplifies the state and action spaces of the MDP, enabling computational tractability. A Latin hypercube design is employed to explore hyperparameter configurations, aiming to maximize total rewards in various combat scenarios. Key findings reveal the efficacy of SARSA(λ) in the Stratagem MIST environment, highlighting the promising role of RL algorithms and self-play in wargaming. Limitations due to computational resources point to the need for enhanced capabilities for more extensive simulations