<p> Future Situation and Impact Awareness: FuSIA is a mission-centric framework using uncertain observables to determine the current and future impact for critical missions in an application such as protecting a computer network or protecting critical entities in a military environment. FuSIA serves to provide an implement of a domain-agnostic, yet domain-configurable, framework for higher level data fusion processes such as situation, impact, and threat assessment. </p><p> FuSIA ingests groupings of observables called attack tracks to estimate the current state of the assets in the given environment using state estimation. The state estimates can be combined across various in different ways to account for uncertainty through the use of the common mass function, which can be converted into a mission impact score. These assessments can then be processed by a mission tree that calculates the estimated impact of the critical missions, which is modeled by a mission tree. The mission tree uses a modification to the Yager Order-Weighted Aggregators to propagate not only the impact, but also uncertainty into the higher-level missions. The effectiveness of the mission impact calculations was also analyzed to determine how sensitive it was to different levels of uncertainty pertaining to different observables. </p><p> In addition to calculating current mission impact, FuSIA also generates a list of possible futures indicating events that could come to fruition in the near future. This list is pruned down to a human-manageable level through a process that involves assessing the likelihood of the futures using capability and opportunity metrics. </p><p> Finally, FuSIA solves a mixed-integer linear optimization problem for individual nodes on the mission tree while providing a heuristic algorithm to determine an optimal set of enforcers, actions that can be taken to improve a mission, to deploy so as the improve the overall state of the mission.</p>

An approach to the problem of approximating a continuous probability distribution with a series in orthogonal polynomials is presented. The approach is first motivated with a discussion of theoretical distributions which are inherently difficult to evaluate. Additionally, a practical application which involves such a distribution is developed. The three families of orthogonal polynomials that pertain to the methodology--the Hermite, Laguerre, and Jacobi--are then introduced. Important properties and characterizations of these polynomials are given to lay the mathematical framework for the orthogonal polynomial series representation of the probability density function of a continuous random variable. This representation leads to a similar series for the cumulative distribution function, which is of more practical use for computing probabilities associated with the random variable. It is demonstrated that the representations require only the moments and the domain of the random variable to be known. Relationships of the Hermite, Laguerre, and Jacobi series approximations to the normal, gamma, and beta probability distributions, respectively, are also formally established. Examples and applications of the series are given with appropriate analyses to validate the accuracy of the approximation.

This thesis investigates the feasibility of applying a knowledge-based approach to the problem of estimating the future success of a major defense acquisition. This thesis will model the US Government Accountability Office (US GAO) knowledge based methodology for evaluating programs. This methodology relies on three sets of knowledge, namely, technology, design, and production. In particular, the technology dimension is measured by Technology Readiness Level (TRL), as defined by NASA. In addition, the methodology relies on assessing the design readiness of a program by examining the status of the release of engineering drawings. Finally, the US GAO methodology assesses the production readiness of a program by examining the status of Statistical Process Quality Control (SPQC) procedures. This thesis also presents to the ROKAF decision maker an independent, knowledge-based estimation of the ROKAF T-50 program by applying the US GAO methodology to the T-50 program.

The FAst THeater Model (FATHM) is a joint theater-level attrition model that combines a Lanchester ground combat model with a linear program, hereafter the Air model, that determines the optimal allocation of air strikes against ground forces. FATHM models time phased ground battles between two forces BLUE and RED, and calls the Air model based on the outcomes of the most recent ground battle, assuming BLUE air supremacy. This thesis develops an enhanced Air model that endows RED with the ability to actively prepare for BLUE air attacks by deploying dummy targets and anti-aircraft artillery as two augmenting defense plans with the goal to more realistically reduce BLUE effectiveness in killing RED targets and simultaneously increase attrition to attacking BLUE aircraft. This Air model is a mixed integer program (MIP), a defender-attacker model, with RED as the defender and BLUE as the attacker. The MIP is a cost- and resource-interdicted model, combining interdiction-induced costs with restrictions on resources for some constraints. This new defender-attacker model provides an optimal defense plan by RED in anticipation of optimized BLUE air attacks without changing FATHMâ s basic concept or structure. We demonstrate defensive actions by RED that can significantly reduce the BLUE attackerâ s effectiveness.

The rapidly changing and asymmetric threat environment that we are facing today has called into question the effectiveness of the traditional approach of hierarchical command and control (C2) structures. Edge organizations have been proposed as a more suitable alternative in the current information age. Beside task-related factors, the characteristics and behavior of the people in an edge organization play an important role in determining the performance of the organization. In this thesis, we look at how the various characteristics of agents influence the efficiency of an edge organization in an intelligence gathering task, using an agent-based simulation model developed in Java. We also look at the attributes of an agent that performs well in an organization, and whether a reward system that encourages individual success in an edge organization is detrimental to the organizationâ s performance. Comparison between edge organizations with similar mean group attributes but different variability in agent characteristics, and comparison between an edge organization and a hierarchical organization are also performed.

This research analyzes the critical logistical requirements of a U.S. Marine Distributed Operations Platoon with the goal of developing a sustainable support plan. The development of Distributed Operations (DO) is one of the Marine Corps' major transformational efforts. The concept is designed to make infantry units more lethal by leveraging training and technology to allow more dispersed and intelligence driven operations. Since a DO platoon will operate far from secure lines of communication and support bases, logistically supporting it will be challenging. Through the use of simulation, statistical analysis, and logistical modeling, this thesis identifies critical factors and capabilities that are important to the sustainment of a DO platoon operating from a Marine Expeditionary Unit (MEU). The research concludes with a feasible support concept combined with the means to assess the effect that supporting a DO platoon has on other MEU missions. Results indicate that quick response time and dedicated support assets from the supporting agency, typically augmented by MEU helicopters, are critical to the success of a DO platoon. This limits the flexibility of the MEU aviation element to support other MEU missions. The biggest payoff in improving logistical effectiveness is given by reducing the response time.

Due to their high dependency on highway transportation, Republic of Korea's (ROK's) military and industry suffer from congestion, shortfall of means (convoys in the military case), high cost and increase in environmental damage. Our research develops an optimization model to guide TOK's military planning using multi-modal transportation. We apply our Military Logistics Transportation Model (MLTM) to a realistic scenario. MLTM provides guidance on the optimal frequency of transportation services and the optimal routes for the freight. By comparing the solution of MLTM with current practice for Wartime Transportation Planning (represented by a heuristic method), our MLTM can reduce the transportation cost up to 29%. This is enabled by the activitation of multi-modal transportation and service sharing by multiple demands. We also analyze scenarios in which either sea-port of debarkation (SPOD) where the supply originates has been shut down by enemy attacks. We find that losing Busan SPOD is more damaging than losing Kwangyang SPOD.

Approved for public release; distribution is unlimited / The Joint Distance Support and Response (JDSR) is an Advanced Concept Technology Demonstration (ACTD) initiative approved by the United States Joint Forces Command (JFCOM). The purpose of ACTD is to exploit mature and maturing technologies and rapidly transit new capability to address military problems, while JDSR aims to establish a common tele-maintenance environment to improve the efficiency of field military services to support war fighters. The operational concept of JDSR is to provide near real time maintenance solutions in an operational fighting environment to enhance situational awareness of platforms and weapon systems operational status for the joint task force commander. This common Joint Service tele-maintenance capability is achieved through the use of advanced commercial technologies integrated with the Services' ongoing development initiatives to provide four integrated functions: remote collaboration, information/knowledge sharing, remote weapon/platform diagnostics, and distant maintenance mentoring at the point of maintenance. The purpose of this thesis is to analyze the cost savings and the benefits of implementing the JDSR capability. This thesis will Develop a recommended standard for performing business case analyses of J/ACTDs, including defining the analytic structure required in a business case report. Conduct the JDSR ACTD business case analysis, including a baseline analysis and an extensive sensitivity analysis. / Outstanding Thesis

The primary purpose of this thesis is to provide analysis for future reliability studies. This thesis assesses the value of the Dynamic Sustainment simulation model as a logistics modeling tool and demonstrates data analysis techniques that can potentially be applied to model results. The secondary purpose is to explore the impact on the maintenance system of varying levels of platform reliability as part of an ongoing effort to provide the Office of the Secretary of Defense with credible analysis for future combat system reliability. The effects of a crew repair team having a high or low repair capability; having a fast or slow spare parts delivery speed; having high, medium, or low system reliability; and high or low numbers of mechanics was measured on maintenance man-hours required at the end of a 72-hour scenario. Twenty-four treatments with varying levels of each factor were designed and imposed on four combat arms brigades. The fourth brigade had 70 percent more vehicles than the other three. Significant effects of all factors except the number of mechanics were found with interaction between those factors. Spare parts delivery speed was ranked high in terms of significance followed by crew repair capability. Slow delivery speed reduced maintenance. Low reliability produced the most maintenance man-hours.

Traditionally in the Navy/Marine Corps, in an effort to be proactive and prevent failures, maintenance and inspections are performed at fixed intervals independent of aircraft status. The current preventive maintenance strategy services and replaces certain components on a predetermined schedule. Additionally, the current Navy/Marine Corps aircraft repair process is reactive. When failures occur, the logistics system - maintenance and supply - respond. The Joint Strike Fighter Autonomic Logistics System (ALS) is proposed to be better than the logistics system in place. Under the ALS maintenance is performed only as needed. The idea is to decrease the logistics infrastructure and simultaneously improve logistic performance, by performing maintenance only as needed. Additionally, parts are ordered 'autonomously' without human intervention. The logistics system prepares for an impending failure. In this thesis simulations are developed to compare the traditional repair system and the ALS. An analysis is conducted to show differences in performance in respect to aircraft availability, failures per mission, and maintenance-man-hour-per-flight-hour. The ALS maintenance model dominated traditional maintenance under the study assumptions.