Works of Scholarship

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    Modeling the Effects of a Cyber-Attack on the Tactical Edge
    (USMA, 2018) Mittal, Vikram; Lesinski, Eugene; Dabkowski, Matthew F.
    Combat modeling involves opposing forces following set processes coupled with uncertainty to determine the winner. These models are built around traditional weaponry and tactics; however, cyber-attacks do not follow the traditional rules. Moreover, due to the very nature of a cyber-attack, it is difficult to model their effects, especially as it relates to a tactical mission. This study provides a simplified method to model the impact of a cyber-attack on a dismounted Army squad. Different pathways for the attack are identified. This method then assumes that the cyber-attack was effective and looks at the change in soldier performance as a result of the attack. In particular, it looks at the degradation of a soldier’s ability to shoot, move, and communicate. This degradation can then be modelled in the Infantry Warrior Simulation (IWARS) to capture the changes in performance metrics to include survivability and lethality. Two case studies are presented. The first looks at the degradation of a soldier with a hacked Facebook account that received personal misinformation. The second looks at a jammed surveillance drone that provides the soldiers with the wrong information.
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    Modeling Supply Chain Disruptions During a Pandemic: A System Dynamics Approach
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2021) Oursler, Patrick; Middlebrooks, Arthur
    The COVID-19 Pandemic of 2020 uniquely impacted the janitorial supply industry with shocks in both demand and supply. Some products experienced massive increases in demand leading to shortages, while the closing of public spaces caused a decrease in demand of other products. The industry experienced delays in shipping and production because of factory closings. Changing public policies for hygiene standards in public buildings, schools, and government buildings has led to a sustained increase in demand for certain products. The janitorial supply chain is a dynamic system that continues to experience change as the pandemic and the public response to it evolves. This research uses a System Dynamics approach to model a small janitorial supply business’ inventory both before and during the pandemic using Vensim. The model focuses on the main categories of products the business sells (Paper Products, Chemicals, Aerosols, and Garbage Bags) and how their respective flows of supply and demand are affected. The business purchases some products directly from manufacturers and others from larger distributors. It sells primarily to the following categories of customers: government contracts, factories, businesses, and individual walk-in sales. Ultimately, this model explores practical policies the store could implement to make them more resilient to the extreme levels of uncertain supply and demand caused by the pandemic. Implementing inventory minimums for sales and safety stocks for orders improved the number of sales and increased revenue for the business during pandemic simulations. Safety stocks and inventory minimums prove to be useful policies for small businesses to consider to become more resilient and survivable to a pandemic.
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    Modeling Human Factors for the Soldier Systems Enterprise Architecture
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2017) Markey, Aaron; Katz, Andrew; Henderson, David; Jefferson, Dominique; Mittal, Vikram
    The Soldier System Enterprise Architecture (SSEA) is a collaborative effort to standardize systems engineering practices in the Army. The reference architecture for SSEA is tied into a Distributive Modeling Framework (DMF) that allows for the analysis of human systems integration, human performance optimization, and materiel development. This study sets out to enhance the existing modeling framework by adding dimensions of human capabilities into existing models. In particular, movement models were analyzed and improved to account for Soldier load and fitness levels. Additionally, shooting models were enhanced to account for Soldier weapon, firing position, skill level, and exhaustion level. These model updates allow for better analysis of Soldier performance during a standard movement to contact mission. The models updated with human factor inputs were compared to existing models and demonstrated a higher degree of fidelity.
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    Measuring the Return on Investment for AFRICOM’s African Enlisted Soldier Development Efforts II
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2021) Bender, Tyrese; McGinnis, Reilly; Skidmore, Tyler; Torres, Emily; Ungrady, Graham; Dabkowski, Matthew F.
    In October 2018, AFRICOM published its Africa Enlisted Development Strategy (AEDS) to codify its approach for facilitating the professional development of its African partners. During Academic Year (AY) 2020, a senior capstone design team from USMA partnered with AFRICOM to create a scale to subjectively assess how well African nations develop and empower their non-commissioned officers (NCOs). Known as the Enlisted Development Maturity Level (EDML) scale, it provided AFRICOM with an easy-to-implement tool to evaluate the high-level return on its investments; however, it did not measure investment, and it lacked granularity. To remedy this, in AY 2021 USMA extended the EDML effort to track investments and score African militaries on six core NCO competencies. Dubbed the AEDS Investment Tracker and the Enlisted Development Review, they provide AFRICOM with a way to monitor the return on its investments over time, enhancing the implementation of the AEDS.
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    (Modern War Institute, 2022) Smith, Maggie; Starck, Nick
    Three months ago, as Russia invaded Ukraine, the world watched as Twitter exploded with real-time data, reporting, and analysis of the unfolding conflict. It quickly became clear that the war presented analysts with an unprecedented amount of rich, open-source data on military movements, troop location, shelling damage, weapon types, and more. Ukraine has been quick to capitalize on Russia’s poor data protection and President Volodymyr Zelenskyy has become Ukraine’s most potent weapon because of his ability to use data and information and Russia’s inability to protect it.
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    On the Average Probability of Hitting a Satellite during a Laser Counterartillery Engagement
    (Journal of Directed Energy, 2014) Burk, Roger Chapman
    This paper investigates the probability that a high-energy laser fired at an incoming projectile will inadvertently hit (not necessarily damage) a background satellite. Typically called the counter-rocket, -artillery, and -mortar (C-RAM) mission, such an engagement can be defined by parameters describing projectile trajectory, laser characteristics, laser firing, and spacecraft orbit parameters, so that a probability of hit can be accurately calculated from the geometry of the situation. The model discussed here takes into account laser location, laser pointing and angular sweep, laser beam angular divergence, and orbit height, inclination, and ascending node. The model does not take into account atmospheric refraction or absorption, assumes that the laser beam propagates beyond the intended target into space, and does not address the probability of damage given a hit. Based on the single-engagement probability calculation, Monte Carlo sampling is then used to find a general probability of hit. For each replication, the threat launcher is placed at a random distance and azimuth, the impact point randomly placed within 1 km of the laser, and the engagement placed randomly in the trajectory. The spacecraft parameters are selected randomly from a comprehensive set of 1417 orbital elements for actual operational or formerly operational spacecraft. A simulation constructed to represent defense against mortars in a near-term counterinsurgency conflict gives a probability of hit of about 15.5 × 10-9 per engagement per satellite, or 15.5 nanohits, for satellites in sun-synchronous orbits. Another simulation was constructed to represent a hypothetical major combat operation with long-range rocket and artillery threats in addition to mortars. This simulation yields 27.5 nanohits for the same set of satellites. An extensive sensitivity analysis explores how these results vary as the parameters describing spacecraft, projectile, laser, and engagement are changed, giving results from 0 to 549 nanohits. Hits increased as the laser site moved north, as the distance to the threat launch point increased, as the engagement moved away from the midpoint of the projectile trajectory, as laser beam quality deteriorated, as engagement duration increased, and as satellite altitude increased. Over all cases, the statistical 95% confidence interval was ±3% to 10%. Accumulating the scenario results over a notional 3-year counterinsurgency conflict and 20 sun-synchronous spacecraft of interest results in a total of 0.0034 expected spacecraft hits during the conflict. Accumulating over a notional 2-week major combat operation and the same spacecraft results in 0.015 expected hits.
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    Integration of Robotics in Warfare
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2018) Price, Samantha; Mittal, Vikram
    Modern day combat has transformed with the integration of Unmanned Ground Vehicles (UGVs) in small unit operations. To show how UGVs have changed operations and positively impacted U.S. military missions, the Infantry Warrior Simulations (IWARS) is used to develop scenarios involving infantry squads and robots. A base model involving an infantry squad gives the initial data (number of kills, shots fired, mission time). Using the base model, the infantry squad then integrates a UGV that can act as a forward observer and even dispose of IEDs. Currently the U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC) is designing capabilities for a robotic mule to deploy a small IED robot to conduct reconnaissance. To model TARDEC’s mission, the IWARS model replicates a real-world scenario and determines the effects of modern-day tactics. An analysis between the two models shows the significance of using UGVs in combat and gives proper analysis into modern warfare.
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    Equipment Turn-In and Transfer Process Modeling
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2021) Morel, Rebecca; Mittal, Vikram
    In military bases across the country, there is excess equipment that costs money to store while it is going unused. When this excess grows large enough, there is an obvious need to turn it in or transfer it to a location where it will be used, but there is not currently a process in the military to handle large stocks like Fort Hood, Texas. This research examines the possibilities of what this turn-in process can look like and how to create a modernized and synchronized method that can be employed across the Army. Modeling this proposed process in ProModel should highlight issues with the current flow and recommend system improvements. Although the process has just been implemented at Fort Hood, there are several system improvements that have been identified by backlogs in the discrete-event simulation including reducing process times, allowing workers to perform tasks in parallel, and reducing time needed to order and install parts. These improvements will make the equipment turn-in process more manageable for Army-wide implementation and success.
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    Exploring the Causal Relationship between Factors Affecting US Army Recruitment
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2021) Ungrady, Graham; Dabkowski, Matthew F.
    Every year, United States Army Recruiting Command (USAREC) dedicates considerable resources to recruiting and accessing soldiers. As the largest branch of the United States Armed Forces, the Army must meet a high recruiting quota while competing in the free-labor market for quality recruits. Over the past two decades, the Army’s success in recruiting ebbed and flowed within the broader context of society and global events. While numerous studies have examined the statistical relationship between factors associated with recruitment, these studies are observational and definitively ascribing causality in retrospect is difficult. With this in mind, we apply fuzzy cognitive mapping (FCM), a graphical method of representing uncertainty in a dynamic system, to model and explore the complex causal relationships between factors. We conclude our paper with implications for USAREC’s efforts, as well as our model’s limitations and opportunities for future work.
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    Engineering Design for Policy: Generating Value-Focused Diversity and Inclusion Strategies at West Point
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2021) Bender, Tyrese; Middlebrooks, Arthur
    In 2015, the United States Military Academy (USMA) published a five-year Diversity and Inclusion Strategic Plan (DISP) to help achieve a key organizational objective: to prioritize diversity and inclusion throughout USMA. Between 2015 and 2020, the DISP contributed to significant progress in the institution’s diversification efforts, but it still left much to be desired in areas of equity and inclusion. To leverage the power of their increasingly diverse student-faculty population, USMA must establish strategic level, policy-driven directives that provide a greater level of organizational focus on equity and inclusion. This approach not only helps redress existing structures of inequity and exclusion within USMA, but also provides cadets with opportunities to develop into inclusive leaders of character who are more prepared and more inspired to lead a diverse Army organization. This research applies a rigorous engineering design method—the Systems Decision Process (SDP)—to identify instances of inequity and exclusion, design and evaluate policy alternatives, and present seven stakeholder driven policy recommendations that foster more inclusive and equitable conditions. These recommendations call for increased data collection and internal organizational assessments, heightened levels of subordinate empowerment, and an integration of diversity, equity, and inclusion into key areas of cadet academic and professional development to better enable their growth into leaders of character.
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    Design and Development of a Portable Auditory Situation Awareness Training (PASAT) System
    (IIE Annual Conference Proceedings, 2021) Thompson, Brandon S.; Casali, John G.; Lee, Kichol; Cave, Kara M.
    Auditory situation awareness (ASA) is essential for safety and survivability in military operations where many of the hazards are not immediately visible. Unfortunately, the Hearing Protection Devices (HPDs) required to operate in these environments can impede auditory localization performance. Promisingly, recent studies have exhibited the plasticity of the human auditory system by demonstrating that training can improve auditory localization ability while wearing HPDs, including military Tactical Communications and Protective Systems (TCAPS). As a result, the U.S. military identified the need for a portable system capable of imparting auditory localization acquisition skills at similar levels to those demonstrated in laboratory environments. The purpose of this investigation was to design and develop a Portable Auditory Situation Awareness Training (PASAT) system capable of reproducing acoustically accurate localization cues similar to a proven laboratory grade system. Extensive research of components and equipment helped ensure optimal performance and packaging of the PASAT system. Selection of these components included a formal decision algorithm developed for optimizing component selection decisions for human-equipment systems. The innovative PASAT system consists of an accordion-style, collapsible frame housing 32-loudspeaker capable of training 360-degrees of azimuth and 60-degrees of elevation operated by a user-controlled tablet computer. Two human factors experiments and a usability study demonstrated the effectiveness of the PASAT system to test and train localization and to detect differences in performance between hearing protection devices.
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    Applying Lean Six Sigma: Personnel Reliability Program
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2021) Krueger, Mason; Nichols, James; Olep, Greyson; Rosu, Andrei; Thompson, Brandon S.
    The Personnel Reliability Program (PRP) monitors over 400 employees who handle controlled chemical or biological agents for the U.S. Army Combat Capabilities Development Command Chemical Biological Center (CCDC-CBC). The program requires an annual recertification consisting of a medical evaluation, safety training requirements, both in-person and online, and security clearance updates. The annual recertification process begins when a program administrator notifies a PRP enrolled employee to complete their recertification. The process is complete when administrators document the employee’s completion of all recertification requirements. Initial surveys revealed over 20% of employees were dissatisfied with the annual recertification process and over 30% of employees were dissatisfied with the instructions provided to complete the recertification requirements. A Lean Six Sigma study was performed to improve the recertification process and increase employee satisfaction. A secondary goal for the study was to decrease the average cost, per employee, of completing the annual recertification process.
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    Analysis of the Impacts of Nett Warrior on Lethality, Survivability, Collateral Damage, and Detection Range
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2019) Mittal, Vikram; Gabrovic, Amelia
    Nett Warrior is a mission command system that supports the mission of dismounted combat leaders. It graphically displays a map detailing the location of leaders, friendly vehicles, and enemy activity on an Android Smartphone while allowing Soldiers to communicate using voice, data, and Position Location Information messages. Although Nett Warrior provides new capabilities, they may not have a large enough impact on lethality, survivability, collateral damage, and detection range to make it worth utilizing. This project simulates two scenarios tied to basic infantry tasks, with and without Nett Warrior capabilities, to compare the impacts to overall lethality, survivability, collateral damage, and detection range. The simulation tool utilized was Infantry Warrior Simulation (IWARS) which is a force on force simulation package that models individual and small unit operations. The study culminates by analyzing the outputs from the simulation to look at the efficacy of Nett Warrior on small unit operations.
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    Aligning Needs, Technologies, and Resources for Special Operations
    (USMA, 2019) Harrison, Kennedy; White, Josh; Rivera, Paul; Giovinco, Tyler; Jurado, Jaritzel; Mittal, Vikram
    USSOCOM equips its warfighters with cutting-edge technology to ensure they have a tactical edge over their adversaries. Special Forces encompasses a wide array of military operations; as such, they have numerous areas of interest (AoI) for technology investment. Companies submit proposals aligned with these AoIs following a Broad Agency Announcement (BAA). Currently, USSOCOM decides which projects get funded based on the perceived military value. However, this process is arbitrary and does not account for the state of technology. This paper analyzes the BAA from 2019 to identify critical technologies (CT) that will solve USSOCOM’s needs. These CTs are analyzed through Technology Readiness Level (TRL) to capture the state of the given technology. A trade space analysis tool plots the TRL against the importance of the technology, which can be leveraged to aid decision making in prioritization. This process provides numerous benefits over traditional approaches; additionally, there is an opportunity to automate this process.
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    An Adversarial Training Based Machine Learning Approach to Malware Classification under Adversarial Conditions
    (Proceedings of the 54th Hawaii International Conference on System Sciences, 2021) Devine, Sean; Bastian, Nathaniel D.
    The use of machine learning (ML) has become an established practice in the realm of malware classification and other areas within cybersecurity. Characteristic of the contemporary realm of intelligent malware classification is the threat of adversarial ML. Adversaries are looking to target the underlying data and/or models responsible for the functionality of malware classification to map its behavior or corrupt its functionality. The ends of such adversaries are bypassing the cybersecurity measures and increasing malware effectiveness. We develop an adversarial training based ML approach for malware classification under adversarial conditions that leverages a stacking ensemble method, which compares the performance of 10 base ML models when adversarially trained on three data sets of varying data perturbation schemes. This comparison ultimately reveals the best performing model per data set, which includes random forest, bagging and gradient boosting. Experimentation also includes stacking a mixture of ML models in both the first and second levels in the stack. A first level stack across all 10 ML models with a second level support vector machine is top performing. Overall, this work reveals that a malware classifier can be developed to account for potential forms of training data perturbation with minimal effect on performance.
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    Counter-AI Tool System Design for AI System Adversarial Testing and Evaluation
    (Proceedings of the Annual General Donald R. Keith Memorial Conference, 2022) Bastian, Nathaniel D.; Byington, Nathan; Davis, Carter; Meehan, Matthew; Vincent, Caroline; Woodward, David
    This work consists of the initial recommendations and conclusions found while soliciting functional requirements for the research, design and development of a Counter-AI Tool for conducting adversarial testing and evaluation of artificial intelligence (AI) systems. The report includes a literature review of relevant AI concepts and extensive research within the adversarial AI domain. An intensive stakeholder analysis, consisting of requirement elicitation from over twenty governmental and non-governmental organizations, assisted in determining what functional requirements should be included in the system design of a Counter-AI Tool. The subsequent system architecture diagram takes user input, tests for various types of adversarial AI attacks, and outputs the vulnerabilities of the AI model. Prior to the operationalization of this tool, iterative experimentation will be conducted by partner organizations, which is the next step in the development and deployment of this Counter-AI Tool.
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    The future of coal as a transportation fuel
    (Energy & Environment, 2021) Mittal, Vikram; Shah, Rajesh; Huq, Nabill
    Due to environmental concerns and cost issues, coal is currently being phased out from usage in electricity production. Regardless, there remains a massive stockpile of coal reserves along with a large industrial complex and a robust distribution/processing infrastructure. As such, coal should be considered for usage in other energy areas. Since coal is simply a solid hydrocarbon, it can be converted over for usage as a transportation fuel. The Fischer-Tropsch process that underlies this conversion is well established with some countries like South Africa currently using it at large scales. Unfortunately, this conversion process has a large carbon footprint, even when using carbon capture technology. However, the blending of coal-based fuels with biodiesel has been found to be more carbon neutral than standard diesel or biodiesel alone. Additionally, coal can be used as an alternate to methane for hydrogen production. Given carbon capture technologies and the existing coal infrastructure, these two uses of coal provide opportunities for a sustainable and economical use of coal as a transportation fuel.
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    The Network Profile Summary: exploring network science through the lens of student motivation
    (Journal of Complex Networks, 2017) Gera, Ralucca; Librertini, Jessica M.; Roginski, Jonathan W.; Zupancic, Anthony
    Productive learning environments strike a balance between student motivation and the necessary learning outcomes associated with a particular course. This article explores one way to achieve such a balance and discusses some of the subtle benefits that spring from that balance. We designed a network science course that achieves course objectives and at the same time allows students to develop, test, and monitor a network of their own choosing. Rather than use canned networks, we introduce a set of assignments called the Network Profile Summary in which students continually apply newly learned course concepts to their selected networks and are therefore able to realize the utility and place of these concepts. This course design fosters student motivation and encourages independent learning. Under this pedagogical paradigm, students began to see coursework, concepts and feedback as productive and globally meaningful rather than corrective and locally meaningful.
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    The Development of the Octane Number Tests and their Impact on Automotive Fuels and American Society
    (The International Journal for the History of Engineering & Technology, 2016) Mittal, Vikram
    Modern automobiles and fuels were shaped heavily by the development of the octane number tests. These tests were developed between 1929 and 1932 to quantify a fuel’s anti-knock performance in spark-ignition engines. Since knock imposes limits on the maximum engine compression ratio, which correlates to engine performance, the anti-knock property of a fuel is a crucial design constraint. Prior to the development of the octane number tests, engines were designed to run at very low compression ratios to avoid knock, significantly limiting their performance. The octane number tests created standards that allowed for better engine development and advancements in fuel technology. Engines could now be designed to handle a specific octane number of fuel allowing for increased performance. The demand for better performing engines resulted in an increase in the average fuel octane number from 50 to 75 during this period, with the Great Depression and World War II setting the stage for this advancement. These advancements in fuel technology played a crucial role in the survival of the American automobile industry during the Great Depression, the Allied success in World War II, in addition to creating the ‘American obsession’ with powerful automobiles. This paper provides an overview of knock, a historical summary on the development of the octane number tests, the corresponding advancements in fuel technology, and the implications of these advancements on American society.
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    Value Modeling and Trade-Off Analysis of the Tactical Assault Light Operator Suit
    (Industrial and Systems Engineering Review (ISER), 2017) Fairbrass, Elliot; Genders, Leonard; Perez-Ortega, Giovanni; Swisher, Clint; Mittal, Vikram
    The Tactical Assault Light Operator Suit (TALOS) is a powered, armored exoskeleton designed to enhance an operator’s survivability, lethality, and mobility. The suit is a SOCOM initiative using rapid acquisition practices with a functional prototype expected in 2018. Value modeling allows the TALOS design teams to rapidly perform design trade analysis while ensuring that the proposed system is in-line with the operator’s needs. A stochastic value model was built for the power subsystem through an analysis of the requirements to develop value hierarchies, swing-weight matrices, and value functions. An Excel based tool performed trade-off analysis to determine the best design solution. This tool accounts for uncertainty in raw data values to create distributions in the cost and value of each design alternative, which is critical for assessing risk. The model was expanded to other subsystems as well as the suit as a whole.