Network-Based Naval Ship Distributed System Design using Architecture Flow Optimization
dc.contributor.author | Parsons, Mark A. | en |
dc.contributor.committeechair | Brown, Alan J. | en |
dc.contributor.committeemember | Brizzolara, Stefano | en |
dc.contributor.committeemember | Choi, Seongim Sarah | en |
dc.contributor.department | Kevin T. Crofton Department of Aerospace and Ocean Engineering | en |
dc.date.accessioned | 2020-03-12T17:52:42Z | en |
dc.date.available | 2020-03-12T17:52:42Z | en |
dc.date.issued | 2019 | en |
dc.description.abstract | This thesis describes the application of a distributed system architecture framework and Architecture Flow Optimization (AFO) to naval ship Concept & Requirements Exploration (C&RE). It describes refinements to both C&RE and AFO, and naval surface combatant concept design case studies. The architectural framework decomposes naval ship distributed systems into the physical, logical, and operational architectures representing the spatial, functional, and temporal relationships of distributed systems respectively. This decomposition greatly simplifies the Mission, Power, and Energy System (MPES) design process for use in C&RE. AFO is a network-based linear programming optimization method used to design and analyze MPES at a sufficient level of detail to understand system energy flow, define MPES architecture and sizing, reduce system vulnerability and improve system reliability. AFO incorporates system topologies, energy coefficient component models, preliminary arrangements, and (nominal and damaged) steady state scenarios to minimize the energy flow cost required to satisfy all operational scenario demands and constraints. This thesis provides an overview of design tools developed to implement this process and methods, including objective attribute metrics for cost, effectiveness and risk, ship synthesis model, hullform exploration and MPES explorations using design of experiments (DOEs) and response surface models. | en |
dc.description.abstractgeneral | The design of modern warships presents many unique challenges not faced in the design of most commercial ships or past generations of warships. The objectives of warship design (e.g. effectiveness, design risk, and total lifecycle cost) cannot be summarized in a single quantitative metric as commonly done in commercial ship design (e.g. required freight rate: the minimum market price of a commodity to make a commercial ship design with a certain cargo capacity profitable). Furthermore, misison, power, and energy systems (MPES) of modern warships have become increasingly interdependent and complex, especially those of naval surface combatants (non-submarine warships designed to engage in direct combat with other ships). Determining quantitative metrics for these objectives is a difficult task to begin with. Determining accurate values for these metrics in early stage design (when designs have little detailed specifications and some technologies may even be still be in development) is another challenge altogether. This thesis describes simple and robust methods and processes to evaluate a warship’s arrangement and operational characteristics. Survivability characteristics, characteristics related to a warship’s ability to complete missions despite battle damage, are of particular interest in these methods. These methods incorporate physics and energy-based means of assessment rather than using historical parametric models that are insufficient in assessing new and revolutionary warship designs. | en |
dc.description.degree | M.S. | en |
dc.format.medium | ETD | en |
dc.identifier.uri | http://hdl.handle.net/10919/97319 | en |
dc.language.iso | en_US | en |
dc.publisher | Virginia Tech | en |
dc.rights | In Copyright | en |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
dc.subject | Ship Design | en |
dc.subject | Naval Ship | en |
dc.subject | Distributed System | en |
dc.subject | Vulnerability | en |
dc.subject | Survivability | en |
dc.title | Network-Based Naval Ship Distributed System Design using Architecture Flow Optimization | en |
dc.type | Thesis | en |
thesis.degree.discipline | Ocean Engineering | en |
thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
thesis.degree.level | masters | en |
thesis.degree.name | M.S. | en |