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Quantifying The Impact Of Highly Corrosive Environments On Fsrm Budgets And Infrastructure Condition At Air Force Bases, Justin M. Weber
Quantifying The Impact Of Highly Corrosive Environments On Fsrm Budgets And Infrastructure Condition At Air Force Bases, Justin M. Weber
Theses and Dissertations
The Department of Defense (DoD) faces significant challenges in maintaining mission-critical infrastructure within highly corrosive environments, with annual costs exceeding $22.5 billion to combat corrosion. This thesis investigated the interplay between environmental severity, sustainment funding, and infrastructure performance. This research utilized Facility Sustainment, Restoration, and Modernization (FSRM) funding data, statistical analyses, and regression modeling, to evaluate how Environmental Severity Index (ESI) categories influence Base Condition Index (BCI) trends and the efficacy of the Facility Sustainment Model (FSM). The analysis revealed that installations in higher ESI categories required significantly greater investment per square foot to achieve comparable improvements in BCI. The …
Accuracy Of Time Phasing Missile And Munition Using The Continuous Distribution Function, Joseph Zobler
Accuracy Of Time Phasing Missile And Munition Using The Continuous Distribution Function, Joseph Zobler
Theses and Dissertations
Accurate cost and schedule estimates are crucial for maintaining the U.S. military’s technological and operational superiority, ensuring efficient resource allocation and timely development of advanced defense systems. This research examines S-curve models for time-phasing non-recurring Research, Development, Test, and Evaluation (RDT&E) expenditures in missile and munition acquisition programs. This research evaluates the commonly used 60/40 rule, which assumes 60% of expenditures occur by 50% of the schedule, for its accuracy using Cost Assessment Data Enterprise (CADE) and Earned Value Management Central Repository (EVM-CR) data from 21 missile and munition development programs.
Personal Decontamination Of Copper Oxide Powder As A Radiological Surrogate On Ambulatory Patients In Arctic Environments: Assessing Residual Airborne Risks After Air Shower Or Vacuum Decontamination Of A Manikin, Quinn G. Pelichoff
Theses and Dissertations
This study assessed air-based decontamination methods for treating patients exposed to dry radiological contamination while minimizing reaerosolization during disrobing, particularly in extreme cold environments. A full-size manikin, simulating an able-bodied Airman, was dressed in military-issue extreme cold weather gear and coated with 28 grams of Copper Oxide. The manikin underwent one of three treatments: HEPA vacuuming, a mobile personal air shower, or no treatment (control). After treatment, researchers removed the uniform and used optical particle counters to measure airborne dust concentrations that could pose risks during disrobing. Each method was tested ten times (30 trials total). Statistical analyses (ANOVA, Tukey’s …
Uranium Particle Classification Using Statistical Machine Learning And Deep Neural Networks For Nuclear Forensics, Lee C. Lambert
Uranium Particle Classification Using Statistical Machine Learning And Deep Neural Networks For Nuclear Forensics, Lee C. Lambert
Theses and Dissertations
The classification of uranium particles from scanning electron microscopy (SEM) imagery is critical to nuclear forensics, but has traditionally relied solely on skilled analysts whose classification accuracy and procedures may vary widely. Existing morphology lexicology [1] provides standardization guidelines to aid analysts but cannot fully address analyst variability. Using a dataset of 1,906 SEM images across 13 unevenly distributed particle classes and 73 magnification levels, final accuracy between statistical and deep learning methods were compared to find the best classification techniques. Ultimately, the deep learning model achieved an impressive 82% accuracy (80% balanced accuracy) on a withheld test set. This …
Hypergame Models For Cyber Defense In A Purple Team Setting, Thomas N. Whitney
Hypergame Models For Cyber Defense In A Purple Team Setting, Thomas N. Whitney
Theses and Dissertations
Hypergame theory and purple teaming are two fields that can support an increased cybersecurity posture. This research investigates a hypergame theory framework that incorporates fittingly into the purple team feedback loop. Additionally, this research integrates empirical data into the hypergames. The data and the hypergames are supported by the MITRE ATT&CK framework. This research also includes a review of available game theory and hypergame theory software, five different hypergame models, a comparison of the two hypergame formats, and an innovative analysis technique using a multi-stage hypergame to represent the cyber kill chain. One finding of this research is that a …
Development Of An Advanced 16-Channel High-Fidelity Multi-Frequency Software-Defined Rf Front-End For Advanced Satnav Signal Monitoring Applications, Melbourne T. Ketteridge
Development Of An Advanced 16-Channel High-Fidelity Multi-Frequency Software-Defined Rf Front-End For Advanced Satnav Signal Monitoring Applications, Melbourne T. Ketteridge
Theses and Dissertations
Multi-element antenna array technology provides significant performance advantages in satellite timing and navigation (satnav) receiver applications. It is the most effective anti-jamming method with the ability to place steep nulls in the direction of jammers. Until recently, satnav systems with 4 or more antenna elements were designated as weapons technology and restricted under ITAR regulations. This opens the door to commercial multi-element satnav receivers. Due to advancements in wireless broadband technology a receiver built entirely using commercial off-the-shelf (COTS) components is possible. This thesis presents an architecture for a high fidelity 16-channel RF front-end (RFFE) for research and development of …
Statistical Analysis Of Spreading Code Authentication (Sca) Performance Under Varying Signal Conditions And Marker Quantization Schemes, Joseph Quinones-Ocasio
Statistical Analysis Of Spreading Code Authentication (Sca) Performance Under Varying Signal Conditions And Marker Quantization Schemes, Joseph Quinones-Ocasio
Theses and Dissertations
This thesis analyzes Spreading Code Authentication (SCA) in the GPS L1C signal using the PyChips software-defined receiver (SDR)framework. Monte Carlo simulations evaluate authentication performance under varying signal conditions, assessing the impact of double-precision and quantized data on signal integrity. Results demonstrate that authentication remains achievable at low signal-to-noise ratio(SNR) conditions but introduces trade-offs in memory usage and authentication time. These findings provide insights into optimizing SCAfor resource-constrained environments, contributing to secure GPS operations in critical applications such as aviation, autonomous systems,and national defense.
Reinforcement Learning For Aeromedical Evacuation In Nonstationary Combat Environments, Micah J. Kartchner
Reinforcement Learning For Aeromedical Evacuation In Nonstationary Combat Environments, Micah J. Kartchner
Theses and Dissertations
This research formulates the medical evacuation (MEDEVAC) dispatching problem as a sequential decision process and investigates the application of reinforcement learning under nonstationary conditions. We model the dynamic arrival rate of MEDEVAC requests using a nonstationary Hawkes process and design a Double Deep Q-Network algorithm that incorporates belief states to anticipate future requests. Through computational experimentation, we analyze the impact of belief formulation on decision quality and system performance. Results indicate that policies incorporating belief states significantly outperform myopic dispatching policies, reducing urgent casualty wait times by up to 49.68% and increasing on-time evacuations by up to 21.91%.
Cognitive Warfare In The South China Sea: Analyzing Media Influence And Public Opinion In Taiwan, Wyatt F. Blatti
Cognitive Warfare In The South China Sea: Analyzing Media Influence And Public Opinion In Taiwan, Wyatt F. Blatti
Theses and Dissertations
In a time where conflict extends beyond traditional battlefields, cognitive warfare emerges as a powerful tool to influence perceptions and gain strategic advantages. This study investigates China’s cognitive warfare strategies against Taiwan through trend analysis, topic modeling, and sentiment analysis of news media articles from March 2013 to August 2024 to uncover evolving techniques and mitigation efforts. The findings highlight the potential for tracking cognitive campaigns overtime but will require more than news media alone and suggests future research to better understand indicators of cognitive warfare.
Evaluating Atmospheric Water Generation For The Indo-Pacific: Predictive Modeling, Energy Considerations, And Regional Viability, Jose I. De La Serna
Evaluating Atmospheric Water Generation For The Indo-Pacific: Predictive Modeling, Energy Considerations, And Regional Viability, Jose I. De La Serna
Theses and Dissertations
Atmospheric Water Generator (AWG) technology presents a promising solution for extracting and harvesting water from ambient air through condensation methods. This innovative approach offers a viable alternative for water production in regions with limited or unreliable water sources. AWGs operate most effectively in hot and humid environments, typically at temperatures of 80°F and relative humidity levels of 80%. As of 2020, the Department of Defense (DoD) has identified the Indo-Pacific region as a strategic focus for addressing future greatpower competition. Within the framework of Agile Combat Employment, this study evaluates the feasibility and performance of AWG technology at pre-determined locations …
Retrospective Cohort Study Of Pure Tone Audiometry Hearing Changes Associated With Ototoxic Metals And Solvents, Continuous Noise And Impulse Noise Exposures At Robins Air Force Base From 2001-2019, Ronald Diaz Cataldo Ramos
Retrospective Cohort Study Of Pure Tone Audiometry Hearing Changes Associated With Ototoxic Metals And Solvents, Continuous Noise And Impulse Noise Exposures At Robins Air Force Base From 2001-2019, Ronald Diaz Cataldo Ramos
Theses and Dissertations
Utilizing DOEHRS-IH and DOEHRS-HC, a retrospective epidemiological study was performed on Robins AFB personnel to investigate relative risks of hearing loss associated with exposures to continuous noise, impulse noise, and ototoxic metals and solvents. An analysis of variance identified age, frequency octave, era and exposure type as influencers of hearing threshold shifts. Risk ratios showed higher risk of hearing loss for exposures to continuous noise + impulse noise + ototoxic metals as well as continuous noise + impulse noise at low frequencies (500Hz and 1,000Hz), and lesser risk for exposures to continuous noise + impulse noise and continuous noise + …
Discovering Design Requirements For Next Generation Arctic Tension Fabric Shelters, Mark W. Mcveigh
Discovering Design Requirements For Next Generation Arctic Tension Fabric Shelters, Mark W. Mcveigh
Theses and Dissertations
Military operations to remote Arctic regions require large-span temporary shelters to house tactical aircraft and provide heated maintained spaces. However, the current System-50 Large Area Maintenance Shelters used by the United States Air Force and Department of Defense are inadequate for Arctic deployments. These shelters lack durability against extreme subzero temperatures, heavy snow accumulation, and high wind speeds. They also fail to address critical Arctic-specific design challenges including permafrost protection, foundation disruption caused by frost heaves, and efficient heating as a result of their inadequate thermal resistance properties. This research analyzed 20 years of climatological data from 8,399 weather observation …
Atmospheric Water Generation: Bacterial And Inorganic Chemical Quality, Garrett E. Stanley
Atmospheric Water Generation: Bacterial And Inorganic Chemical Quality, Garrett E. Stanley
Theses and Dissertations
This study investigated the quality of untreated water collected from a vapor compression-based atmospheric water generator (AWG) operated outdoors in Dayton, Ohio. The concentrations of bacterial and chemical constituents were determined. The concentration of culturable bacteria was between 200 and 2300 CFU/mL, significantly higher than the reference levels described in recreational and drinking water quality guidance. Three discrete bacteria phenotypes were visually identified; two were yellow in color, rod-shaped and gram-negative while the third was milky white, circular, and gram-positive. Chemical analysis on 15 randomly selected samples revealed the presence of Barium (average = 0.16 mg/L), Magnesium (0.08 = mg/L), …
Understanding The Acceptance Of Digital Tools Within An Air Force Environment Using The Utaut2 Model, Britton J. Edwards
Understanding The Acceptance Of Digital Tools Within An Air Force Environment Using The Utaut2 Model, Britton J. Edwards
Theses and Dissertations
This research paper explores factors influencing digital tool adoption in a military context, using a modified UTAUT2 model with the inclusion of Military Status as a moderating factor. The study examines the moderating effects of Military Status on Social Influence towards Behavioral Intention and Behavioral Intention on Use Behavior. Data was collected through a Likert-scale survey from respondents across multiple Department of the Air Force (DAF) organizations. Findings revealed Social Influence had the potential to positively influence Behavioral Intention to use digital tools, but military experience did not significantly moderate this relationship. However, past experience with the legacy tool and …
Jamming-Tolerant Low-Rate Wireless Personal Area Network For Detection Sensor Networks, Michael A. Eddy
Jamming-Tolerant Low-Rate Wireless Personal Area Network For Detection Sensor Networks, Michael A. Eddy
Theses and Dissertations
This research evaluates the impact of electronic warfare, particularly jamming, on an audio-based drone detection wireless sensor network (WSN) using Monte Carlo simulations. A six-node IEEE 802.15.4 network, with five edge nodes and a central sink, is tested against jamming probabilities ranging from 0-100% in 5% increments across 30 iterations per configuration. Results show that packet delivery ratio (PDR) degrades linearly at approximately 20% per jammed node, while detection performance often exceeds PDR. Even at 80% jamming, detection success rates remain above 57%, highlighting resilience despite network degradation. The study reveals that jamming effectiveness depends on node placement relative to …
Emergency Response Digital Twin: Integrating Augmented Reality And Live Position Data With Simulation-Aided Decision-Making In Real-Time, Joseph Fuentes
Emergency Response Digital Twin: Integrating Augmented Reality And Live Position Data With Simulation-Aided Decision-Making In Real-Time, Joseph Fuentes
Theses and Dissertations
With the growing use of simulation across industries, the digital twin remains an underexplored research area, particularly in emergency management and response. Its real-time updating capability is often overlooked due to the misconception that "digital twin" is merely a complex term for simulation. This paper highlights its distinctiveness through an evasion exercise involving two independent entities in a collocated environment. Using a highly integrated virtual environment (HIVE) and internet of things (IoT) devices, we link the physical system with an analytical simulation, demonstrating the impact of lag times in high-pressure scenarios. The computational model leverages agent-based modeling (ABM) and discrete-event …
Assessing The Feasibility Of Managed Aquifer Recharge For The United States Air Force, Daniel Hendrix
Assessing The Feasibility Of Managed Aquifer Recharge For The United States Air Force, Daniel Hendrix
Theses and Dissertations
Water stress is becoming an increasing global issue, with 4 billion people (50% of the world’s population) experiencing water stress at least one month per year. By 2050, 60% of the world’s population and $70 trillion USD in global gross domestic product will be affected. This research analyzes 78 CONUS USAF installations to determine location-specific water stress and feasible Managed Aquifer Recharge (MAR) solutions. Although thousands of MAR projects have been implemented globally, active-duty USAF installations have yet to contribute to solving this growing issue. Important factors such as required subsurface conditions, physical limitations, design, cost, and regulatory constraints are …
Air-Based Chemical Patient Decontamination Methodologies For Arctic Regions Using Methly Salicylate As A Chemical Agent Surrogate On A Litter-Bound Manikin, Marcus D. Shadd
Theses and Dissertations
This study evaluated a mobile air shower for patient decontamination without disrobing or rinsing, an alternative for Arctic conditions where water is scarce. A manikin in extreme cold weather gear was exposed to 10 µL of methyl salicylate (MeS), a sulfur mustard surrogate, and placed in a horizontal chamber on a military litter. Airborne MeS was measured using a ppbRAE 3000 detector to assess inhalation risk for the patient and decontamination team. Three methods were tested: an air-knife system, paper towels, and no decontamination, with 10 trials each (30 total). ANOVA analysis showed significant reductions in airborne MeS with air-knife …
Calibrating Airfield Pavement Asset Management For A Changing Global Climate: A Case Study At Fairchild Air Force Base, Emily L. Worthy
Calibrating Airfield Pavement Asset Management For A Changing Global Climate: A Case Study At Fairchild Air Force Base, Emily L. Worthy
Theses and Dissertations
Military airfields and civilian airports serve as foundational nodes in the global transportation network, enabling travel, economic growth, and the projection of national security. This study investigates the relationship between climate variables projected through climate change and pavement degradation, with a focus on Fairchild Air Force Base (AFB). Using principal component regression (PCR), the research integrates historical pavement condition index (PCI) data with climate variables, including snowfall, precipitation, freeze-thaw cycles, solar irradiance, and wind speed to develop a predictive model of pavement performance under future climate scenarios, Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. These models, for both Portland …
Model-Based Approach To Support Safety Driven Design And Satisfy Mil-Std-882e Requirements With Stpa Coordination: A Case History In Suas Defense Acquisition, Daniel A. Shea
Theses and Dissertations
Increasingly complex defense systems that are routinely overbudget and behind schedule are driving digital engineering initiatives in the defense acquisition industry. MBSE offers a solution to counter this issue but the lack of guidance on how to implement it has led to significant experimentation. One MBSE area of interest is system safety. This research demonstrates how to conduct model-based Systems Theoretic Process Analysis (STPA) to meet the unique system safety process requirements from MIL-STD882E. Based in systems theory, STPA extended for coordination enables a safety-driven design process of complex systems. This research investigated conducting STPA in the SysML-RAAML modeling language …
Early-Phase Cost Estimation For Department Of Defense Construction Projects Via Artificial Neural Networks: Implications And Policy Recommendations For Artificial Intelligence Integration, Kobe T. Thompson
Theses and Dissertations
The Department of Defense lost over 500 million dollars between 2016 and 2024, partially due to poor early cost estimates resulting in cost overruns. practice for cost estimation relied on parametric techniques that incorporate historical data, subject matter experts in cost estimating, and predictive software applications. The main motivation for this study was to assess the viability of artificial neural networks as a means of providing a more accurate cost estimate in the early design phases of a construction project. The dataset initially contained approximately 48,000 data points from a database of various Air Force projects, including maintenance, repair, minor …
Material Classification With Spectropolarimetric Lidar, Alexander J. Watson
Material Classification With Spectropolarimetric Lidar, Alexander J. Watson
Theses and Dissertations
A method for characterizing unknown targets using a hyperspectral polarimetric light detection and ranging (LiDAR) system is presented. Light reflected from manmade objects tends to be more polarized than light reflected from objects in the natural world. As such, polarization measurements can be used in remote sensing applications to differentiate artificial and natural objects. Previous works have attempted to characterize objects through passive polarimetric imagery. Methods developed by Cain and Lemaster and Cunningham facilitate reconstruction of the Stokes Vector from returning light. Martin used multispectral polarimetry to classify targets when the angle of incidence (AOI) is close to 0º. Here, …
A Reinforcement Learning Approach For Maneuvering And Firing Decisions In Sead Operations, Nathaniel Garcia
A Reinforcement Learning Approach For Maneuvering And Firing Decisions In Sead Operations, Nathaniel Garcia
Theses and Dissertations
The integration of automated processes in defense continues to expand, enhancing the lethality of military forces. Artificial intelligence accelerates decision-making cycles, removes the constraints of human-operated hardware, and improves coordination by enabling seamless integration across multiple systems. Suppression of Enemy Air Defenses (SEAD) missions are critical to the United States (U.S.) military, as they neutralize hostile air defense systems, ensuring air superiority and enabling safe and effective operations for aircraft in contested environments. Therefore, it is necessary to pair emerging autonomous capabilities with an important mission set in defense. This research investigates the Autonomous Unmanned Air-to-Ground Strike (AUAGS) problem, modeling …
Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner
Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner
Theses and Dissertations
The extraction of symbology and numerical data from the T-38 Heads-Up Display (HUD) enhances post-flight analysis and supports real-time decision-making. This research develops a deep learning pipeline using YOLO-based object detection and Optical Character Recognition (OCR) to analyze HUD video data. Model evaluations showed mAP0.5:0.95 ranging from 0.422 (YOLOv11m, hard test set) to 0.696 (YOLOv8m, medium test set), demonstrating robust symbology detection. Numeric detection performed well (mAP0.5:0.95 = 0.764), but OCR struggled with glare and resolution limitations, achieving a recognition accuracy of 17.35%. These results validate deep learning for HUD data extraction but highlight the need for improved robustness …
Evaluating The Performance Of Conformal Prediction Generated Uncertainty Sets In Robust Optimization, Zion C. Johnson
Evaluating The Performance Of Conformal Prediction Generated Uncertainty Sets In Robust Optimization, Zion C. Johnson
Theses and Dissertations
Uncertainty is a major challenge in optimization, especially in problems where unpredictable costs impact decision-making. Robust optimization addresses this by modeling uncertainty via uncertainty sets. These sets are then used such that solutions hold under worst-case scenarios, with success depending on the accuracy of the uncertainty sets. This research examines the use of conformal prediction to construct uncertainty sets for RO, an approach that has not been widely explored. We test split and full conformal prediction in a robust optimization minimum cost flow problem, and comparing them to interval-based and normal-based ellipsoidal uncertainty sets. Experiments run across different network structures …
Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph
Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph
Theses and Dissertations
Artificial intelligence (AI) grows ever-more important in warfighting. Emerging technologies allow for the use of AI to control aircraft and weapons systems. This research investigates the application of reinforcement learning (RL) through the Proximal Policy Optimization (PPO) algorithm to a two-versus-two (2v2) beyond-visual-range (BVR) air combat maneuvering problem (ACMP). Implemented in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM), the methodology frames the engagement as a Markov decision process, wherein an autonomous RL agent learns continuous control decisions—throttle, pitch, roll, and yaw—under a cooperative communication scheme. A multi-phase curriculum-learning approach facilitates the progressive acquisition of flight stability, weapon deployment, …
Machine Learning Techniques To Predict Solar Particle Events And Radiation Of Aircrew, Haley Traub
Machine Learning Techniques To Predict Solar Particle Events And Radiation Of Aircrew, Haley Traub
Theses and Dissertations
Solar Particle Events (SPEs) are high-energy phenomena from the Sun that pose risks to technology, human health, and Air Force operations. Accurate prediction of SPEs exceeding 100 MeV is crucial for mitigating these risks. This thesis explores using Bayesian statistical models to predict such events, integrating prior knowledge from solar physics with the ability to update predictions based on new data. The research uses a dataset spanning three solar cycles (21–23) and incorporates attributes like flare fluence, peak flux, latitude, longitude, and class. Four Bayesian models (PyMC, Bnlearn, and two Dredge models) were compared to machine learning models. The Bayesian …
Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson
Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson
Theses and Dissertations
This research utilizes reinforcement learning (RL) to train two blue agents each imbued with a directed energy weapon (DEW) in a 2v2 within visual range air combat maneuvering problem. A phased solution approach is employed to repeatedly tune and train several RL algorithm implementations: Proximal Policy Optimization (PPO) and Double Deep Q Network (DDQN). Phase I of training includes reward shaping for basic flight elements such as altitude, airspeed, and target proximity. Phase II of training builds off policies developed in Phase I, but rewards emphasize winning the aerial engagement by any means necessary. DDQN significantly outperforms PPO in Phase …
Mediating And Moderating Effects Of Job Satisfaction, Organizational Commitment, Perceptions Of External Markets, And Work-Life Balance On Employee Retention, Naya J. Gillespie
Mediating And Moderating Effects Of Job Satisfaction, Organizational Commitment, Perceptions Of External Markets, And Work-Life Balance On Employee Retention, Naya J. Gillespie
Theses and Dissertations
Employee retention remains a critical challenge for organizations across industries, particularly in environments with high turnover rates and competitive external job markets. This thesis examines the correlations between organizational commitment, job satisfaction, work-life balance, and perceptions of external job markets to uncover their collective and individual impacts on employee retention. Using quantitative research design, data was collected through an online survey of 240 participants across various hierarchical levels. Key findings indicate that organizational commitment and job satisfaction significantly influence retention, with job satisfaction also serving as a mediator between organizational commitment and turnover intentions. Work-life balance plays a direct role …
Cloud One Migration Duration And Its Drivers, Grayson T. Hall
Cloud One Migration Duration And Its Drivers, Grayson T. Hall
Theses and Dissertations
As modern warfare evolves with rapid technological advancements, cloud computing plays a critical role in managing the vast amounts of data required for real-time decision making, as well as enabling seamless organizational access to mission-critical programs and information from around the globe. Recognizing its importance, the Department of Defense (DoD) identified cloud computing as essential for maintaining the military’s technological edge. However, despite cloud computing’s strategic significance, the DoD faces challenges in successfully implementing department-wide cloud computing. In contrast, the Air Force’s cloud computing environment, Cloud One, is fully operational and has already integrated over 145 systems into its platform. …