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Operations Research, Systems Engineering and Industrial Engineering
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- Human systems integration (3)
- Linear programming (3)
- Machine learning (3)
- #afcec (2)
- Approximate dynamic programming (2)
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- Combat modeling (2)
- CubeSat (2)
- Digital engineering (2)
- Markov decision processes (2)
- Military Entrance Processing Stations (2)
- Natural language processing (2)
- Neural networks (2)
- Optimization (2)
- Random forest (2)
- Reinforcement learning (2)
- Simulation (2)
- Social network analysis (2)
- SysML (2)
- Value hierarchy (2)
- Value-focused thinking (2)
- Accident investigations (Aviation) (1)
- Activated aluminum (1)
- Agent-based modeling and simulation (1)
- Aging Workforce (1)
- Air combat (1)
- Aircraft Availability (1)
- Airworthiness certification (1)
- Alertness (1)
- Analysis of variance (1)
- Anti-access area denial (1)
Articles 1 - 30 of 58
Full-Text Articles in Engineering
Optimal Scheduling Of Aircraft Test And Evaluation Fleets To Balance Availability For Testing And Training, Sarah E. Hoops
Optimal Scheduling Of Aircraft Test And Evaluation Fleets To Balance Availability For Testing And Training, Sarah E. Hoops
Theses and Dissertations
The 96th Test Wing at Eglin Air Force Base manually schedules a fleet of approximately 26 aircraft to conduct a range of missions over a one-to-two year planning period. This study automates the scheduling process, does so in a manner that optimizes multiple planning goals related to aircraft availability for training, and provides the 96th Test Wing with a software tool for the implementation that can be used by operational analysts within the command. We formulate the scheduling problem as a multiobjective, nonlinear, binary integer math program that seeks to maximize both the lowest percent of time any aircraft is …
Cooperative Wide Area Search Algorithm Analysis Using Sub-Region Techniques, Shawn Whitney
Cooperative Wide Area Search Algorithm Analysis Using Sub-Region Techniques, Shawn Whitney
Theses and Dissertations
Recent advances in small Unmmaned Aerial Vehicle (UAV) technology reinvigorates the need for additional research into Wide Area Search (WAS) algorithms for civilian and military applications. But due to the extremely large variability in UAV environments and design, Digital Engineering (DE) is utilized to reduce the time, cost, and energy required to advance this technology. DE also allows rapid design and evaluation of autonomous systems which utilize and support WAS algorithms. Modern WAS algorithms can be broadly classified into decision-based algorithms, statistical algorithms, and Artificial Intelligence (AI)/Machine Learning (ML) algorithms. This research continues on the work by Hatzinger and Gertsman …
Project Selection In Facility And Infrastructure Maintenance Organizations, Bayram M. Kurbanov
Project Selection In Facility And Infrastructure Maintenance Organizations, Bayram M. Kurbanov
Theses and Dissertations
The current Air Force Civil Engineer Center (AFCEC) built infrastructure Facility Sustainment Restoration and Modernization (FSRM) portfolio management methodology results in an unbalanced project portfolio. The consequence of this unbalance is that majority of the funding goes towards buildings on the flightline and Facility Support Services activities do not get adequate funding which leads to further deterioration of those facilities. This research investigates whether decision support framework based on Value-Focused Thinking (VFT) process yields better project selection outcomes for facility and infrastructure maintenance organizations. To accomplish that, the investigation focuses on understanding current AFCEC decision support methodology, building an alternative …
Operational And Cost Analysis Of A Leo Radar-Based Satellite Constellation, Kyle O. Norbert
Operational And Cost Analysis Of A Leo Radar-Based Satellite Constellation, Kyle O. Norbert
Theses and Dissertations
This thesis presents a methodology to assess the ability of a Low-Earth Orbit (LEO) satellite constellation to successfully accomplish the GMTI mission in a cost-effective fashion. A simulation model was developed to test the coverage performance of 512 unique constellation designs. Significant factors were revealed by developing regression models that revealed the most critical constellation trade-offs on measures of performance. A Value-Focused Thinking (VFT) approach was applied to assign weights to a broad range of measures of performance from which the Pareto distribution on a cost-capability plot revealed cost-effectiveness. A novel measure of performance was developed and analyzed that accounted …
Root-Cause Analysis Of Rsaf Maintenance-Related Flight Safety Mishaps, Heaf H. Alqahtani
Root-Cause Analysis Of Rsaf Maintenance-Related Flight Safety Mishaps, Heaf H. Alqahtani
Theses and Dissertations
Poor maintenance is a major factor in many aviation mishaps. This is due to the fact that some maintenance activities are carried out improperly or overlooked as a result of human error. It is important to acknowledge that maintenance mistakes are a visible sign of deeper organizational issues. Therefore, adequate solutions to maintenance issues must consider organizational influences. Despite efforts to reduce the accident rate within the Royal Saudi Air Force (RSAF), the RSAF suffers from an increasing trend in mishaps attributed to maintenance. Therefore, safety data was analyzed to examine trends. Additionally, the Human Factors Analysis and Classification System …
Retention Prediction And Policy Optimization For United States Air Force Personnel Management, Joseph C. Hoecherl
Retention Prediction And Policy Optimization For United States Air Force Personnel Management, Joseph C. Hoecherl
Theses and Dissertations
Effective personnel management policies in the United States Air Force (USAF) require methods to predict the number of personnel who will remain in the USAF as well as to replenish personnel with different skillsets over time as they depart. To improve retention predictions, we develop and test traditional random forest models and feedforward neural networks as well as partially autoregressive forms of both, outperforming the benchmark on a test dataset by 62.8% and 34.8% for the neural network and the partially autoregressive neural network, respectively. We formulate the workforce replenishment problem as a Markov decision process for active duty enlisted …
A Methodological Framework For Parametric Combat Analysis, Dustin L. Hayhurst Sr.
A Methodological Framework For Parametric Combat Analysis, Dustin L. Hayhurst Sr.
Theses and Dissertations
This work presents a taxonomic structure for understanding the tension between certain factors of stability for game-theoretic outcomes such as Nash optimality, Pareto optimality, and balance optimality and then applies such game-theoretic concepts to the advancement of strategic thought on spacepower. This work successfully adapts and applies combat modeling theory to the evaluation of cislunar space conflict. This work provides evidence that the reliability characteristics of small spacecraft share similarities to the reliability characteristics of large spacecraft. Using these novel foundational concepts, this dissertation develops and presents a parametric methodological framework capable of analyzing the efficacy of heterogeneous force compositions …
Value Focused Thinking Analysis Of C-Band Australia Radar Operations, Samuel Ray Grothman
Value Focused Thinking Analysis Of C-Band Australia Radar Operations, Samuel Ray Grothman
Theses and Dissertations
The radars used for Space Domain Awareness (SDA) are inherently all-weather, day/night sensors capable of around the clock operations. Despite this fact, some radars are operated for fewer than their maximum operating capabilities. The decision-making process for selecting the operating hours of a sensor has historically been based on only a few factors or just one. This research uses the techniques in Value Focused Thinking to develop an evaluation process to score possible alternatives and find the alternative with the most value for the decision maker. By investigating the value that is added by operating an SDA radar, it is …
Evaluating Performance Competencies In The Royal Saudi Air Force Engineering Directorate And Squadrons, Faisal A. Al Dawood
Evaluating Performance Competencies In The Royal Saudi Air Force Engineering Directorate And Squadrons, Faisal A. Al Dawood
Theses and Dissertations
The effectiveness of tasks performed by the directorate of aeronautical engineering and squadrons in RSAF directly impacts flight safety, which in turn influences the organization either positively or negatively. Therefore, improving engineers' competencies will improve the overall performance of the organization. The study refined and reconstructed a model, namely a T-shape competency model, to assess the engineers' competencies which revealed some management and competency-related deficiencies and concluded with managerial recommendations.
Reconciliation, Restoration And Reconstruction Of A Conflict Ridden Country, Muhammad S. Riaz
Reconciliation, Restoration And Reconstruction Of A Conflict Ridden Country, Muhammad S. Riaz
Theses and Dissertations
Conflict has sadly been a constant part of history. Winning a conflict and making a lasting peace are often not the same thing. While a peace treaty ends a conflict and often dictates terms from the winners’ perspective, it may not create a lasting peace. Short of unconditional surrender, modern conflict ends with a negotiated cessation of hostilities. Such accords may have some initial reconstruction agreements, but Reconciliation, Restoration and Reconstruction (RRR) is a long term process. This study maintains that to achieve a lasting peace: 1) The culture and beliefs of the conflict nation must be continuously considered and …
A Model-Based Approach To Cubesat Propulsion And Payload Analysis, Madeline H. Johnson
A Model-Based Approach To Cubesat Propulsion And Payload Analysis, Madeline H. Johnson
Theses and Dissertations
Currently, there are only limited ways to increase mission success of CubeSats in terms of component and mission compatibility. The Payload Analysis Tool (PAT), developed by Air Force Institute of Technology (AFIT) students, combines the power of multiple tools to analyze payload compatibility on a single CubeSat bus. The PAT simulates a CubeSat mission with a variety of payloads to better understand how the payloads interact with the bus in terms of power, data rate, and memory, but it lacks a propulsion system. This thesis research advances the PAT by including a propulsion system which allows for increased mission time …
Developing A Model-Based Approach To Forecast A Competitor's System, Christopher A. Del Vecchio
Developing A Model-Based Approach To Forecast A Competitor's System, Christopher A. Del Vecchio
Theses and Dissertations
The purpose of this research is to develop a model-based approach to intelligence forecasting of a competitor’s system. This analysis currently uses a document-based practice to capture all knowledge of the forecast and its development. A framework of antithesis processes, or Anti-Processes, were derived from the systems engineering technical processes. This was then combined with analytical tradecraft from the field of competitive technical intelligence to build a SysML reference model, which was then applied to a small case study to enhance and refine the model. The Anti-Process framework and SysML reference model provide a rigorous, model-based approach to intelligence forecasts …
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Theses and Dissertations
The United States Air Force is investing in artificial intelligence (AI) to speed analysis in efforts to modernize the use of autonomous unmanned combat aerial vehicles (AUCAVs) in strike coordination and reconnaissance (SCAR) missions. This research examines an AUCAVs ability to execute target strikes and provide reconnaissance in a SCAR mission. An orienteering problem is formulated as anMarkov decision process (MDP) model wherein a single AUCAV must optimize its target route to aid in eliminating time-sensitive targets and collect imagery of requested named areas of interest while evading surface-to-air missile (SAM) battery threats imposed as obstacles. The AUCAV adjusts its …
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Theses and Dissertations
Using convolutional neural networks (CNNs) for image classification for each frame in a video is a very common technique. Unfortunately, CNNs are very brittle and have a tendency to be over confident in their predictions. This can lead to what we will refer to as “flickering,” which is when the predictions between frames jump back and forth between classes. In this paper, new methods are proposed to combat these shortcomings. This paper utilizes a Bayesian CNN which allows for a distribution of outputs on each data point instead of just a point estimate. These distributions are then smoothed over multiple …
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Theses and Dissertations
We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …
Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis
Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis
Theses and Dissertations
In 2007, the Office of the Assistant Secretary of Defense for Sustainment pushed for the need to transition to a Condition Based Maintenance Plus (CBM ) initiative for weapon systems in the U.S. Department of Defense. The CBM initiative can help increase aircraft availability (AA) for the United States Air Force. There are many reasons where AA can be affected but one such issue is engine availability primarily due to oil issues. Within the CBM perspective, this study examines the risk of a jet engine failure due to an oil issue and attempts to predict an engines time until next …
Game Theory Framework To Evaluate Nuclear Deterrence, Michael A. Cevallos
Game Theory Framework To Evaluate Nuclear Deterrence, Michael A. Cevallos
Theses and Dissertations
This research game theory framework evaluates the resilience of nuclear deterrence options between two players. We use lexicographic prioritization to value four priorities of political, military, economic, and civilian casualties. The value order may be varied. We demonstrate our approach with six player choices of no nuclear strike, demonstration, counterforce, tactical military, economic, or countervalue strike. We use game theory to construct and analyze the resulting damage matrix. We conclude that credible deterrence requires having at least equivalent offensive damage capabilities.
Accelerating Transition To Production By Manufacturing Readiness Focus During Development, William K. Duncan
Accelerating Transition To Production By Manufacturing Readiness Focus During Development, William K. Duncan
Theses and Dissertations
The Department of Defense has adopted management tools, such as Manufacturing Readiness Levels (MRLs), which seek to address issues that have delayed the transition to production and delivery of deployment-ready systems. The MRL scale and assessment process institutes periodic reviews of products during the acquisition process. Specifically, MRLs provide a scale to measure, and importantly communicate, progress by evaluating and summarizing multiple aspects of product maturity. Unfortunately, issues are often identified during the periodic assessments which, if addressed earlier, would have further streamlined product delivery. The current research applies Model Based System Engineering tools to analyze and refine organizational structures …
Geometric Generation Through The Merging Of Sysml, And Engineering Sketch Pad, Alexander J. Miesle
Geometric Generation Through The Merging Of Sysml, And Engineering Sketch Pad, Alexander J. Miesle
Theses and Dissertations
The United Stated Department of Defense (DoD) and Air Force (USAF) have placed increased emphasis on the utilization of modern systems engineering (SE) practices within the current and future acquisitions lifecycle. This call is driven by the current rate at which near-peer adversaries such as Russia and China are increasing their defense system capabilities and catching up or surpassing the Unites States in certain operational regions. To aid in the transition to a Digital Engineering and Digital Twin dominated acquisitions process, this thesis presents a method with which SysML and geometric tools can be linked within both new and existing …
Identifying Characteristics For Success Of Robotic Process Automations, Charles M. Unkrich
Identifying Characteristics For Success Of Robotic Process Automations, Charles M. Unkrich
Theses and Dissertations
In the pursuit of digital transformation, the Air Force creates digital airmen. Digital airmen are robotic process automations designed to eliminate the repetitive high-volume low-cognitive tasks that absorb so much of our Airmen's time. The automation product results in more time to focus on tasks that machines cannot sufficiently perform data analytics and improving the Air Force's informed decision-making. This research investigates the assessment of potential automation cases to ensure that we choose viable tasks for automation and applies multivariate analysis to determine which factors indicate successful projects. The data is insufficient to provide significant insights.
Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming, Andrew E. Mogan
Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming, Andrew E. Mogan
Theses and Dissertations
This research formulates and solves the multiagent routing problem with dynamic target arrivals (MRP-DTA), a stochastic system wherein a team of autonomous unmanned aerial vehicles (AUAVs) executes a strike coordination and reconnaissance (SCAR) mission against a notional adversary. Dynamic target arrivals that occur during the mission present the team of AUAVs with a sequential decision-making process which we model via a Markov Decision Process (MDP). To combat the curse of dimensionality, we construct and implement a hybrid approximate dynamic programming (ADP) algorithmic framework that employs a parametric cost function approximation (CFA) which augments a direct lookahead (DLA) model via a …
System Phasing And Schedule Growth Analysis, Daniel A. Long
System Phasing And Schedule Growth Analysis, Daniel A. Long
Theses and Dissertations
Software development research, once a priority for the DoD, has received less focus in recent years. What research that has occurred has focused on size and cost prediction of software. Generally lacking in these studies is analysis on phase distributions and schedule. Putnam (1978) showed that there were measurable effects between early program management and final schedule growth, but these relationships have not been explored using the 2001-2021 DoD Software Resources Data Report (SRDR) database. Additionally, industry software development guidance provides rules of thumb for effort allocation, but a comparison of the rules to DoD software projects is nonexistent. This …
Analysis Of Generalized Artificial Intelligence Potential Through Reinforcement And Deep Reinforcement Learning Approaches, Jonathan Turner
Analysis Of Generalized Artificial Intelligence Potential Through Reinforcement And Deep Reinforcement Learning Approaches, Jonathan Turner
Theses and Dissertations
Artificial Intelligence is the next competitive domain; the first nation to develop human level artificial intelligence will have an impact similar to the development of the atomic bomb. To maintain the security of the United States and her people, the Department of Defense has funded research into the development of artificial intelligence and its applications. This research uses reinforcement learning and deep reinforcement learning methods as proxies for current and future artificial intelligence agents and to assess potential issues in development. Agent performance were compared across two games and one excursion: Cargo Loading, Tower of Hanoi, and Knapsack Problem, respectively. …
Life Cycle Analysis Of Hydrogen Fuel Derived From Aluminum Versus Diesel, Tyson S. Metlen
Life Cycle Analysis Of Hydrogen Fuel Derived From Aluminum Versus Diesel, Tyson S. Metlen
Theses and Dissertations
The Department of Defense needs energy sources beyond petroleum products to effectively combat area denial strategies employed by its adversaries. Petroleum fuels are expensive, they have deleterious environmental impacts, and most of the world’s oil reservoirs are in volatile countries. A proposed alternative energy carrier is reacting aluminum with water to produce hydrogen and using the hydrogen as a fuel source. Normally aluminum forms a protective oxide layer that prevents continuous reaction but if aluminum is mixed with a 3.5% by weight gallium-indium eutectic, the oxide layer cannot form, and the reaction is sustainable. This study conducts a life cycle …
Inverse Optimization: Inferring Unknown Instance Parameters From Observed Decisions, Keith Batista
Inverse Optimization: Inferring Unknown Instance Parameters From Observed Decisions, Keith Batista
Theses and Dissertations
The objective of this research is to develop procedures that estimate selected, unknown parameters over an adversary's investment portfolio across a set of new or existing technologies. To solve for the selected unknown parameters, it is assumed that the adversary is maximizing the portfolio optimization problem and investing along the efficient frontier. The first technique is when an unknown risk attitude exists but all other parameters were known (i.e. expected return, variance, covariance). An adaptive line search technique that iteratively solved the portfolio optimization problem until the adversary's risk parameter was found. The second problem that was solved was when …
Training Logic And Random Forest Models To Predict It Spending, Jacob P. Batt
Training Logic And Random Forest Models To Predict It Spending, Jacob P. Batt
Theses and Dissertations
The Air Force must modernize, but the distribution of funds for technology remains as tight as ever. To this end, the Air Force Audit Agency is looking to utilize machine learning techniques to enhance their capabilities. This research explores Logistic Regression and Random Forest modeling to streamline data collection and cost classification. The final Logistic Regression model identified 4 significant attributes out of the 36 given and was 85 accurate in predicting whether a purchase amount was over or under $10,000. To expand beyond binary classification, a six-category classification Random Forest model was developed. It identified 6 significant attributes and …
Narrative Analysis Of Open-Source Social Media Activity In The Indopacom Aor, Aaron K. Glenn
Narrative Analysis Of Open-Source Social Media Activity In The Indopacom Aor, Aaron K. Glenn
Theses and Dissertations
Emotion classification can be a powerful tool to derive narratives from social media data. Recurrent Neural Networks (RNN) can meet or exceed the performance of state-of-the-art traditional machine learning techniques using exclusively open-source data and models. Specifically, these results show that RNN variants can produce more than an 8% gain in accuracy in comparison to Logistic Regression and SVM techniques and a 15% gain over Random Forest when using FastText embeddings. This research found a statistical significance in the performance of a single layer Bi-directional Long Short-Term Memory (Bi-LSTM) model over a 2-layer stacked Bi-LSTM model. This research also found …
Qualitative Insights On The Military Entrance Processing Station (Meps) Of Excellence Program, Brian T. Johnson
Qualitative Insights On The Military Entrance Processing Station (Meps) Of Excellence Program, Brian T. Johnson
Theses and Dissertations
The Military Entrance Processing Station (MEPS) of Excellence Program (MOE) is a program to improve operations through recognition and motivation and to sustain excellence in MEPSs core services. Quantitative MOE program data was studied using a hybrid approach of descriptive statistics, statistical process control, and logistic regression to gain relevant insights with respect to the program objectives of improvement, excellence, motivation, and recognition. Future work should employ information such as climate surveys, worker performance reports, and the civilian awards program for further insights into the MOEs effectiveness as a motivator.
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke
Theses and Dissertations
Given the increased threat and proliferation of adversary military capabilities, this research seeks to develop reasonably accurate and computationally tractable models to optimally maneuver aircraft to intercept cruise missile attacks. The research leveraged mathematical programming to model the problem, informed by constraints representing a system of (temporal) difference equations. The research began by comparing six models having alternative representations of velocity and acceleration constraints while analyzing situations with stationary targets. The Multiple Aircraft, Multiple Stationary Target Engagement Problem with Box Constraint Bounds (MAMSTEP-BC) Model yielded superior overall performance and was further analyzed through alternative mathematical programming model enhancements to create …
Examining The Relationship Between An Aging Workforce And Logistics Performance Indicators, Daniel Parkhill
Examining The Relationship Between An Aging Workforce And Logistics Performance Indicators, Daniel Parkhill
Theses and Dissertations
In the United States, 10,000 baby boomers turn 65 every day. The subsequent generation born between 1965 and 1976 is significantly smaller, referred to as the baby bust. As a result, this causes a talent shortage as Baby Boomers retire, leaving a workforce gap which the subsequent generation is not large enough to fill. This issue also has been recognized as a potential problem in the logistics community of the United States Air Force. The purpose of this study is to examine the impact of workers age on key logistics performance indicators (LPIs) such as aircraft availability, product flow days, …