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The purpose of this thesis is to provide a methodological approach for conducting a Business Case Analysis (BCA) for the Advanced Technology Ordnance Surveillance (ATOS) Advanced Concept Technology Demonstration (ACTD). This study compares the cost savings over time of having an ATOS infrastructure in place at Navy Munitions Management locations compared to the base case of "as-is" inventory management. ATOS is a Radio Frequency Identification (RFID)-based automated system that provides a capability to collect environmental data in near real-time and supports munitions management tasks on stored munitions pallets. This type of data has never before being available and is critical for making more precise decisions about the shelf life and operational performance of individual munitions throughout their service life. ATOS is not meant to be a replacement for the status quo processes of Ordnance Management (OM). Instead, ATOS is meant to enhance many of the current processes and add additional capabilities and dimensions to OM. A Business Case Analysis for a notional site, using exemplar data sets indicates that with an initial investment of 1.3 million dollars, a Net Present Value (NPV) of 5.3 million dollars can be obtained over a 10-year period. The payback period is less than one year, and the Return on Investment is 214 %, or almost 11 % annual, compounded ROI.

The understanding of sympathetic detonation of energetic materials is important from the stand point of safety, shelf life, storage requirements and handling. The objective of this thesis is to introduce a methodology to assess performance and sensitivity levels of insensitive munitions to sympathetic detonations. AUTODYN code was utilized to validate the shock sensitivity results for Composition B explosives. Upon code validation, simulations were conducted to evaluate small scale sympathetic detonation via gap tests. Similarly, large scale simulations of sympathetic detonations, reflective of real life scenarios, were performed. The understanding of this analysis offers insights for the testing, design and storage orientation of future energetic materials.

In previous work conducted in the modeling and simulation of ships subjected to underwater explosions, there has been some debate over the influence that hull appendages have upon the dynamic response of a multi-degree-of-freedom structural model surround by a fluid mesh. This thesis investigates the effects on the dynamic response of a structural model resulting from the inclusion of hull appendages such as rudders, shafts and keel boards. Moreover, it examines the differences resulting from these appendages having been modeled as coupled or uncoupled structures with respect to the surrounding fluid in the finite element analysis. In this case, a Meko-like box model, based on the actual dimensions of a typical Meko-class ship, was investigated using the underwater shock modeling and simulation methodology developed at the Naval Postgraduate School's Shock and Vibration Computational Laboratory. Presented herein is a detailed study on the validity of including hull appendages, the proposed coupling scheme for these appendages, and the resulting effects on the vertical and athwartship velocity response motions.

Declining budgets and the reduction of workforce has caused many organizations to perform additional job assignments with fewer personnel. These organizations realized that in order to survive in a competitive market, scarce resources would provide the most value if used to work on mission-essential tasks, while allowing the performance of support functions by an outside source (called outsourcing). The Department of the Navy (DoN) is one organization that has chosen to outsource many business areas, but none bigger than the outsourcing of information technology (IT) to form the Navy Marine Corps Intranet (NMCI)â the largest IT outsourcing contract to date. While the DoN has faced many challenges since the onset of the NMCI contracting agreement, this thesis focuses on the challenges faced by the Navy Reserve with managing the Intranetâ 's user accounts. The research uses the principles of Business Process Redesign (BPR) and Knowledge Management (KM) to determine the current state (As-Is) and to recommend changes in the account management process. Specifically, the Knowledge-Value Added (KVA) methodology was used to determine the amount of knowledge quantitatively embedded in each sub-process for a relative comparison of the value that the sub-processes provide to the overall process.

This thesis is part of a project at the Naval Postgraduate School to assess the Computer Network Operations (CNO) threat of foreign countries. CNO consists of Computer Network Attack (CNA), Computer Network Exploitation (CNE), and Computer Network Defense (CND). Threats to the nation's critical infrastructures come from an adversary using CNA and CNE to degrade, deny or destroy access to the information systems they depend upon. Defensive capabilities are also addressed since exploitation, attack, and defense are inherently related. The result of a successful cyber-attack upon these critical infrastructures has the potential to cripple a country's communications and other vital services, economic well-being, and defensive capabilities. The goal of this thesis is to develop a methodology for assessing the CNO threat of Iran. The methodology is based on open sources that can supplement classified information acquired by the intelligence community.

In the frequency domain all materials can be described electrically by their complex permittivity and permeability. These constitutive parameters determine the response of the material to electromagnetic (EM) radiation. The precise knowledge of complex permittivity and permeability is required not only for scientific but also for industrial applications. Due to the uncertainties in manufacturing processes, often the only way to find a material's parameters is to measure them. The concept of metamaterials, exhibiting negative permittivity and permeability, is attracting a lot of attention. Such materials are also termed left-handed materials (LHMs). This thesis examines several methods to determine the effective permittivity and permeability of both normal materials and metamaterials. CST Microwave Studio is used to model the materials in both free space and rectangular waveguide environments to calculate the S-parameters (S11 and S21) from which the constitutive parameters can be extracted.

This senior thesis project explores and generalizes some fundamental machine learning algorithms from the Euclidean space to the statistical manifold, an abstract space in which each point is a probability distribution. In this thesis, we adapt the optimal separating hyperplane, the k-means clustering method, and the hierarchical clustering method for classifying and clustering probability distributions. In these modifications, we use the statistical distances as a measure of the dissimilarity between objects. We describe a situation where the clustering of probability distributions is needed and useful. We present many interesting and promising empirical clustering results, which demonstrate the statistical-distance-based clustering algorithms often outperform the same algorithms with the Euclidean distance in many complex scenarios. In particular, we apply our statistical-distance-based hierarchical and k-means clustering algorithms to the univariate normal distributions with k = 2 and k = 3 clusters, the bivariate normal distributions with diagonal covariance matrix and k = 3 clusters, and the discrete Poisson distributions with k = 3 clusters. Finally, we prove the k-means clustering algorithm applied on the discrete distributions with the Hellinger distance converges not only to the partial optimal solution but also to the local minimum.

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