Engineering Commons^™

Encouraging Voluntary Government Action Via A Solar-Friendly Designation Program To Promote Solar Energy In The United States, Xue Gao, Casey I. Canfield, Tian Tang, Hunter Hill, Morgan Higman, John Cornwell

Engineering Management and Systems Engineering Faculty Research & Creative Works

Sustainable development requires an accelerated transition toward renewable energy. In particular, substantially scaling up solar photovoltaics (PV) adoption is a crucial component of reducing the impacts of climate change and promoting sustainable development. However, it is challenging to convince local governments to take action. This study uses a combination of propensity score matching (PSM) and difference-in-differences (DID) models to assess the effectiveness of a voluntary environmental program (VEP) called SolSmart that targets local governments to engage in solar-friendly practices to promote the local solar PV market in the United States. Via specific designation requirements and technical assistance, SolSmart simplifies the …

Challenges Of The Industrial Revolution Era 1.0 To 5.0 : University Digital Library In Indoensia, Merlin Apriliyanti, Ilham M

Library Philosophy and Practice (e-journal)

This study explains the development of the world of libraries to establish a very close relationship with the world of information technology. For this reason, facilities and infrastructure are needed to facilitate data and information retrieval quickly and accurately. Facing the challenges of the Industrial Revolution 5.0 era by utilizing information technology, libraries must also adapt to the times. Because the library has an important role, among others, as a source of information and the development of knowledge. Used libraries are still conventional to be converted into digital libraries. In essence, this development represents the desire of library users for …

A Systems Approach For Solving Inter-Policy Gaps In Dynamic Spectrum Access-Based Wireless Rural Broadband Networks, Pawel Kryszkiewicz, Casey I. Canfield, Shamsnaz Virani Bhada, Alexander M. Wyglinski

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper, we articulate the challenge of multiple intersecting policies for the realization of rural broadband networks employing dynamic spectrum access (DSA). Broadband connectivity has been identified as a critical component of economic development, especially during the COVID-19 pandemic, and rural communities have been significantly (and negatively) affected by the lack of this important resource. Although technologies exist that can deliver broadband connectivity, such as 4G LTE and 5G cellular networks, the challenges associated with efficiently deploying this infrastructure within a rural environment are multi-dimensional in terms of the different dependent policy decisions that need to be considered. To …

Technical Inventory Management For College Of Liberal Arts, Sofya Shatalova

Industrial and Manufacturing Engineering

This project is sponsored by California Polytechnic State University’s Information Technology Services (ITS) department aimed to help with the transfer of inventory management from ITS to the College of Liberal Arts’ departments. Currently, there are no guidelines on how equipment is handled and little to no information about the flow of equipment. This creates difficulty for faculty and staff within those departments to check out, look up, or keep track of equipment. The sponsor needs for each department to be responsible for their own equipment and to familiarize themselves with the old database system the ITS used.

After understanding the …

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.

Evaluating The Military Medical Evacuation Dispatching And Delivery Problem Via Simulation And Self-Exciting Hawkes Process, Virbon B. Frial

Theses and Dissertations

The location, allocation, and utilization of military medical evacuation (MEDEVAC) resources significantly impact the quality and timeliness of medical care to injured troops. In 2009, Secretary of Defense Robert Gates introduced the Golden Hour mandate that entails the evacuation of critically-injured troops to military treatment facilities (MTFs) within an hour to prevent further complications. To develop high-quality policies that improve MEDEVAC system performance, several papers in the current literature assume that MTFs have both the capacity and capability of treating any patient, regardless of the type of injury. However, these assumptions are unrealistic when conducting high-intensity operations. While acknowledging MTF …

A Decision Analysis Framework To Consider Space Congestion In Orbit Selection, Anthony J. Correale

Theses and Dissertations

Low Earth Orbit (LEO) is becoming more congested, which increases the risk to space missions. Decision makers will need to consider this increase in congestion as an increased risk within their mission engineering process. This thesis proposes a methodology to create and implement a value structure that quantitatively scores a range of orbits based on congestion factors of each orbit and how well each orbit meets mission requirements. This thesis demonstrates this methodology on a set of circular LEO orbits defined by altitude and inclination, and scores this illustrative scenario based on notional mission measures and expected number of encounters …

A Proposed Mission Assurance Framework For University Cubesat Programs, Mitchell R. Thomas

Theses and Dissertations

The low cost, small form factor, and use of Commercial-Off-The-Shelf components make CubeSats an ideal platform for university use given their unique constraints. Since 2000, roughly 55% of CubeSats developed by universities fail to meet mission goals. Mission assurance, which is used to increase confidence in mission success, is based around traditional government programs, and does not provide an adequate road map for universities. Leaving them without specific guidance in tailoring mission assurance activities to operate within their constraints. This paper adapts these traditional practices to develop a baseline mission assurance framework for university CubeSat programs.

An Exploratory Analysis Of Time Series Econometric Data For Retention Forecasting Using Deep Learning, John C. O'Donnell

Theses and Dissertations

Officer retention in the Air Force has been researched many times in an attempt to better predict the personnel needs of the Air Force for the future. There has been previous work done in regards to specific AFSCs and how their retention compares to specific yet similar private sector jobs. This study considers different econometric time series statistics as a feature space and an average Air Force officer separation rate as the response variable for the multivariate time series analysis deep learning techniques. The econometric indicators used in this study are New Business Formations, New Durable Good Orders, and the …

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 …

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, …

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.

Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas

Theses and Dissertations

Previous research investigating lightning warning radii about the Cape Canaveral space launch facilities have focused on reducing these radii from either 5 nautical miles (NM) to 4 NM or from 6 NM to 5 NM depending on the structures being protected. Some of these findings have suggested the possibility of both a seasonal difference (warm versus cold) and lightning detection events (cloud-to-ground lightning (CG) or total lightning (TL)) impacting these radii and associated risk levels. Utilizing the 2017-2020 data provided by the 45th Weather Squadron at Patrick Space Force Base via the Mesoscale Eastern Range Lightning Information System (MERLIN), this …

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

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 …

The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold

Theses and Dissertations

Traditional control mechanisms restrict human input on the displays in 5th generation aircraft. This research explored methods for enhancing pilot interaction with large, information dense cockpit displays; specifically, the effects of visual feedback and control button configuration when augmenting cursor control with head tracking technology. Previous studies demonstrated that head tracking can be combined with traditional cursor control to decrease selection times but can increase pilot mental and physical workload. A human subject experiment was performed to evaluate two control button configurations and three visual feedback conditions. A Fitts Law analysis was performed to create predictive models of selection time …

A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia

Theses and Dissertations

The purpose of this research is to explore the utility and current state of touchless technologies. Five categories of technologies are identified as a result of collecting and reviewing literature: facial/biometric recognition, gesture recognition, touchless sensing, personal devices, and voice recognition. A thematic analysis was conducted to evaluate the advantages and disadvantages of the five categories. A reference analysis was also conducted to determine the similarities between articles in each category. Touchless sensing showed to have the most advantages and least similar references. Gesture recognition was the opposite. Comparing analyses shows more reliable technology types are more beneficial and diverse.

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.

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 …

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 …

Exploring The Value Of Training System Alternatives Through Methods Technologies, And Relevant Attributes, Brian R. Novitsky

Theses and Dissertations

Skilled maintainers are being lost at a higher rate than average of all enlisted career fields within the Air Force. Although incentive programs can provide some retention, attrition rates may continue to vary, placing the readiness of the warfighter in jeopardy. Additionally, the technologies used to train maintainers have evolved substantially, including augmented reality (AR) and virtual reality (VR) solutions, among others. These technologies have recently gained notoriety as novel ways to increase training effectiveness, providing avenues for maintainers to achieve greater skill levels at a faster rate than traditional platforms. Through semi-structured subject matter expert (SME) interviews, this qualitative …

Networked Cooperative Autonomous Munitions Digital Twin Modeling Utilizing Model Based Systems Engineering, Christopher R. Reed

Theses and Dissertations

An example of a high-complexity system is a swarm of Networked Cooperative Autonomous Munitions (NCAM) that prioritize wide area search and multiple view target confirmation. First, this research discusses methods toward building behavioral models within a Model-Based Systems Engineering (MBSE) tool. Then, this research presents the parallel modeling effort of NCAM in two environments: the MBSE model in Cameo Systems Modeler, and a physics-based model in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM). Each digital model in its environment provides distinct benefits to the stakeholders of the design process, so the models must present consistent and parallel information. …

Analyzing The Impact Of Blood Transfusion Kits And Triage Misclassification Errors For Military Medical Evacuation Dispatching Policies Via Approximate Dynamic Programming, Channel A. Rodriguez

Theses and Dissertations

Members of the armed forces greatly rely on having an effective and efficient medical evacuation (MEDEVAC) process for evacuating casualties from the battlefield to medical treatment facilities (MTF) during combat operations. This thesis examines the MEDEVAC dispatching problem and seeks to determine an optimal policy for dispatching a MEDEVAC unit, if any, when a 9-line MEDEVAC request arrives, taking into account triage classification errors and the possibility of having blood transfusion kits on board select MEDEVAC units. A discounted, infinite-horizon continuous-time Markov decision process (MDP) model is formulated to examine such problem and compare generated dispatching policies to the myopic …

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

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 …

Analysis Of Container Shipments For Ustranscom, John N. Campos Y Campos

Theses and Dissertations

USTRANSCOM (United States Transportation Command) sends containers to various overseas destinations, mainly commercial container shipping companies. Delivering the containers to the destinations on time is important to support the United States (US) Forces deployed in foreign countries. This study analyzes container shipment records for two years from 2019 to 2021 and prepares insights for USTRANSCOM. This study utilizes descriptive statistics, data visualization, and one-way analysis of variance (ANOVA). According to the records, almost half of the containers (41.25%) were delivered late for one day or longer. The container with the longest delay took 408 days. Major reasons for delays included …

Simulating Autonomous Cruise Missile Swarm Behaviors In An Anti-Access Area Denial (A2ad) Environment, Kyle W. Goggins

Theses and Dissertations

The increasingly sophisticated anti-access area denial (A2AD) threat imposed by the modern integrated air defense system (IADS), coupled with the decreasingly potent advantage provided by high-end stealth platforms, has prompted Air Force senior leaders to invest in radically changing the nature of air power for the year 2030 and beyond. A prominent element of this new vision is weapon swarming, which aims to address this challenge by overwhelming the IADS with huge numbers of low-cost, attritable aerial assets emboldened by autonomous capabilities. This research proposes a framework for classifying the different levels of autonomous capability along three independent dimensions—namely ability …

Screening Heuristics For The Evaluation Of Covert Network Node Insertion Scenarios, Andrew E. Pekarek

Theses and Dissertations

The majority of research on covert networks uses social network analysis (SNA) to determine critical members of the network to either kill or capture for the purpose of network destabilization. This thesis takes the opposite approach and evaluates potential scenarios for inserting an agent into a covert network for information gathering purposes or future disruption operations. Due to the substantial number of potential insertion scenarios in a large network, this research proposes three screening heuristics that leverage SNA measures to reduce the solution space before applying a simple search heuristic.

Air Force Specialty Code Assignment Optimization, Rebecca L. Reynolds

Theses and Dissertations

Each year, the Air Force Personnel Center determines which career field newly commissioned officers will serve under during their time in the Air Force. The career fields are assigned while considering five priorities, dictated by Headquarters Air Force, Manpower and Personnel: target number of cadets, education requirements, average cadet percentile, cadet source of commissioning, and cadet preference. A mixed-integer linear program with elasticized constraints is developed to generate cadet assignments according to these priorities. Each elasticized constraint carries an associated reward and penalty, which is used to dictate the importance of the constraint within the model. A subsequent analysis is …

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. …