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This report presents the structural reliability analysis of the hull girder ultimate strength for the ship shaped FPSO Triton. The ultimate strength of the hull girder was calculated using a component approach, where the behaviour of the hull is evaluated based on the behaviour of the single structural components. Three collapse conditions were investigated; failure initiated by plate compression, failure initiated by stiffener tension and failure initiated by stiffener compression. Only vertical bending moment has been considered and the hull girder loads are divided into stillwater and wave induced components. The two loading components have been considered independent and Ferry Borges - Castenheta load combination method has been applied to obtain load combination factors for the Full Load, Partial Load (50 % loaded) and Ballast condition. The distributions of the extreme values of the vertical wave bending moments (VWBM) were calculated, based on linear strip theory and a long-term formulation. The vertical mooring forces are small and they were considered to have an insignificant influence on the bending moment response. The reliability analysis was carried out using a SORM analysis. Annual reliability indices (ß) and probabilities of failures were calculated for hogging and sagging conditions. The calculated ß values were higher than the annual reliability indices proposed in DNV Classification Notes 30.6 for serious failures in redundant structures. This indicates that the design is safe and reliable for operation in this particular location.

Predictions of the environmental loading and induced motional and structural responses are among the most important aspects in the overall design process of offshore structures and ships. In this thesis, attention is focused on the wave loads and excited bodily motion responses of large offshore structures and special vessels. With the aim of improving the existing theoretical methods to provide techniques of theoretical effectiveness, computational efficiency, and engineering practicality in marine and offshore applications, the thesis concentrates upon describing fundamental and essential aspects in the physical phenomenon associated with wave-structure interactions and deriving new methods and techniques to analyse offshore structures and unconventional ships of practical interest. The total wave force arising from such a wave-structural interaction is assumed to be a simple superposition of the potential and the viscous flow force components. The linear potential forces are solved by the Green function integral equation whilst the viscous forces are estimated based on the Morison's damping formula. Forms of the Green function integral equation and the associated Green function are given systematically for various practical cases. The relevant two-dimensional versions are then derived by a transformation procedure. Techniques are developed to solve the integral equation numerically including the interior integral formulation and, in particular, to tackle the mathematical difficulties at irregular frequencies. In applying the integral equations to solve problems with various offshore structures and special vessels, some modified, improved or simplified methods are proposed. At first, simplified method is derived for predictions of the surge, sway and yaw motions of elongated bodies of full sectional geometry or structures with shallow draft. Then, a new shallow draft theory is described for both three- and two-dimensional cases with inclusion of the finite draft effect. Furthermore, a three-dimensional strip method is formulated where the end effects of the body are fully taken into account. Finally, an approximation to the horizontal mean drift forces of multi-column offshore structures are presented. Some new findings are also discussed including the multiple resonances occurring in the motions of multi-hulled marine structures due to the wave-body interaction, the mutual cancellation effect of the diffraction and the radiation forces arising from a full shaped slender body, and so on. Further to those verification studies for individual methods developed, more comprehensive example investigations are given related to two industrial applications. One is a derrick barge semi-submersible with zero forward speed; and the other, a SWATH ship with considerable speed. By correlation of all the proposed approaches with available analytical, numerical and experimental data, the thesis tries to demonstrate a principle that as long as principal physical aspects in the wave-structure interaction problem are properly treated, an appropriately modified or simplified method works, performs well and, sometimes, even better.

The design of advanced maritime vessels is a complex and wicked process. The complexity arises from numerous systems being developed through multiple interdependent design processes. Product complexity and design difficulty continue to increase as technology advances, but the design methods used in the maritime design community have not kept pace. Research in the design science domain has historically focused on improving design from a product-centric perspective rather than examining and informing the relationship between the product and the design process. There are significant knowledge gaps regarding the execution of the design process itself and where in the design process emergent failure is likely to occur. Over the previous several decades, military naval ship design has faced especially severe design process failures, including cost and timeline overruns, product failures, and, ultimately, programs being canceled. Navies have lost trillions of dollars and years of effort to these failures due to incomplete or missing information within the design process. The research presented in this thesis focuses on the design process rather than the product to address the impact of emergent design failures. Novel Influence Structure Diagrams (ISDs), created as part of this research, model the impact of delayed decision-making and decision-making with incomplete or missing information. The ISD is a directed network developed to model the design process of advanced systems. The network contains variable, decision, and utility nodes representing design process stages, with edges representing directional dependencies among those elements. Within the ISD, variable nodes represent the desired or learned knowledge of design elements, decision nodes represent the lock-in of choice associated with certain knowledge elements, and utility nodes represent the design quality based on the connected knowledge. To address design failure issues directly, the concept of Design Nuisance Parameters (DNPs), which are design elements that are assumed to be required for decision-making but are not fully known or understood in time for the decision, are introduced within the ISD structure. Design Nuisance Parameters play a critical role in understanding design process failures by examining the likelihood of DNPs causing emergent design failure using Monte Carlo simulations. The presented thesis demonstrates the development of the ISD and Design Nuisance Parameter framework, which, in conjunction with several novel entropy metrics, is used to analyze design process failures. This thesis presents a case study focused on the design of an uncrewed surface vehicle that demonstrates the success of the ISD framework, and its associated metrics, in identifying the impact of emergent design failure through delayed and incomplete information in decision-making. The case study walks through over 75 unique cases which involve cascading failure, emergent rework, design churn, and integration failure through real-world scenarios. The presented case study and underlying framework provide a launching point for future research and advancements in reducing the impact of emergent design failure in complex design programs, not limited to the maritime domain, worldwide.

This thesis describes an adaptable component level machinery system weight and size estimation tool used in the context of a ship distributed system architecture framework and ship synthesis model for naval ship concept design. The system architecture framework decomposes the system of systems into three intersecting architectures: physical, logical, and operational to describe the spatial and functional relationships of the system together with their temporal behavior characteristics. Following an Architecture Flow Optimization (AFO), or energy flow analysis based on this framework, vital components are sized based on their energy flow requirements for application in the ship synthesis model (SSM). Previously, components were sized manually or parametrically. This was not workable for assessing many designs in concept exploration and outdated parametric models based on historical data were not sufficiently applicable to new ship designs. The new methodology presented in this thesis uses the energy flow analysis, baseline component data, and physical limitations to individually calculate sizes and weights for each vital component in a ship power and energy system. The methodology allows for new technologies to be quickly and accurately implemented to assess their overall impact on the design. The optimized flow analysis combined with the component level data creates a higher fidelity design that can be analyzed to assess the impact of various systems and operational cases on the overall design. This thesis describes the SSM, discusses the AFO's contribution, and provides background on the component sizing methodology including the underlying theory, baseline data, energy conversion, and physical assumptions.

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.

One of the major problems facing ship design today is that engineers often focus most of their efforts on the What of the design as opposed to understanding the Why. The What is defined as the solution itself, while the Why is defined as the decisions that drive how the set of solutions change through time. Decision making through time, especially in the face of uncertainty, has consistently been difficult for engineers. This is due to both uncertainty and the interconnected nature of complex decision making problems. There are no standard definitions or metrics that quantify the impact of engineering design decisions. This dissertation aims to address that need. This research extends the ship-centric Markov decision process (SC-MDP) framework which involves applying Markov decision processes to ship design and decision making. The SC-MDP framework is useful for analyzing decision making in the maritime domain due to its inherent temporal structure and ability to handle uncertainty. However, the framework is limited in its ability to clearly show how uncertainty affects decisions, and its inability to quantify the changes and long term implications of decisions. Two methods unique to this research are developed and explored. First, applying Monte Carlo simulations to the SC-MDP framework is proposed to give insight into the impacts of uncertainty on the decisions and set of results. Second, a method to perform eigenvalue spectral analysis within the framework was developed to understand the behavior of the decisions themselves. Three metrics are developed in regards to eigenvalue analysis. To quantify changes in decisions, the damping ratio is proposed, defined as the ratio of the largest eigenvalue to the magnitude of the second largest. To understand the long term implications of a set of decisions the principal eigenvector is presented. For eliciting relationships and inter-dependencies of decisions, analyzing repeated dominant eigenvalues and the set of principal eigenvectors are used. Three maritime case studies are presented that demonstrate the utility of these methods and metrics involving designing for evolving Emission Control Area regulations, ship egress analysis and general arrangements design, and lifecycle planning for ballast water treatment regulations.

A novel set reduction decision support framework for large-scale, team-based design efforts is presented. The framework provides a design manager with valuable and easy-to-understand information that is used to make better informed reduction decisions within a set-based design (SBD) environment. SBD is a convergent design method that uses dominance and infeasibility to consider multiple design alternatives in parallel while accommodating separate groups of specialists within a concurrent engineering approach. Based on the limitations of current SBD research and the completion of extensive design experiments, three major set reduction considerations are identified: time-dependent design relationships, the impact of reduction decisions, and identifying robust reduction decisions. Design relationships change as the fidelity of analysis increases, variable set-ranges are reduced, or requirement changes are instituted. Due to these changing conditions, the impact of reduction decisions can be difficult to determine. Although SBD has proven resilient to changing circumstances, the reduction process can still be impact the design process to the point of potential failure. Identifying robust reduction decisions avoids situations where changes lead to a design failure. Each of the three considerations set forth is addressed by a specific component of the overall decision support framework used to analyze a specific function of interest. Design space mapping is used to determine relationships between variable and function spaces. The Longest Path Problem (LPP) formulated as a Markov Decision Process (MDP) is used as a structure for the reduction decision-making process and the identification of optimal decision paths. Through simulation, robust decision paths are identified. Since the developed LPP MDP formulation has never been used to analyze set reduction problems, multiple metrics and representations are developed using the MDP and simulation results. Based on a series of studies, the MDP LPP framework is able to better handle situations with changing conditions, as well as better accommodate constrained problems, compared to a method based solely on current in-state knowledge. As part of a ship design case study, the framework’s ability to handle multiple and more complicated functions is shown. Also, how the framework fits into a more realistic reduction scenario is presented.

A novel design evaluation framework is offered to improve early stage design decisions relating to environmental policy change and similar non-technical disturbances. The goal of this research is to overcome the traditional treatment of policy as a static, external constraint and to address in early stage design the potential disruptions to performance posed by regulatory policy change. While a designer’s primary purpose is not to affect policy, it is the responsibility of the designer to be cognizant of how policy can change, of how to assess the implications of a policy change, and of how to deliver performance despite change. This research addresses a present need for a rigorous means to keep strategic pace with policy evolution. Use of a Markov Decision Process (MDP) framework serves as a unifying foundation for incorporating temporal activities into early stage design considerations. The framework employs probabilistic methods via a state-based structure to holistically address policy uncertainty. Presented research enables exploration of the performance of a design solution through time in the face of environmental instabilities and identifies decisions necessary to negotiate path dependencies. The outcome of this research is an advanced framework for addressing life cycle management needs that arise due to policy change, as judged from a life cycle cost perspective. Original metrics for evaluating decision paths provide insight into how the timing, location, and confluence of disturbances impact design decisions. Development of the metrics is driven by a desire to communicate the design-specific characteristics of a strategic response to policy change. Quantifying the amount and type of uncertainty present, changeability afforded, and life cycle changes exercised offer points of comparison among individual design solutions. The knowledge gained from path-centric measurements enables an enhanced ability to characterize design lock-in. Principles and metrics borne out of the design evaluation framework are validated through two ship design examples related to ballast water treatment and carbon emissions.

The Concept and Requirements Exploration process used at Virginia Tech is based on a Multi-Objective Optimization approach that explores the design space to produce a Non-Dominated set of ship design solutions ranked objectively by Cost, Risk, and Effectiveness. Prior research and effort has also been made to leverage the validation and verification of the U.S. Navy's ship synthesis design tool, ASSET, into the Virginia Tech Ship Synthesis Model. This thesis applies Design Structure Matrix theory to analyze and optimize the ASSET synthesis process by reducing or removing the feedback dependencies that require the iterative convergence process. This optimized ASSET synthesis process is used as the basis to develop a new Simplified Ship Synthesis Model (SSSM) using Commercial Off-The-Shelf (COTS) software, ASSET Response Surface Models (RSMs) and simplified parametric equations to build the individual synthesis modules. The current method of calculating an Overall Measure of Effectiveness (OMOE) used at Virginia Tech is based on expert opinion and pairwise comparison. This thesis researches methods for building a Design Reference Mission (DRM) composed of multiple operational situations (OpSits) required by the ship's mission. The DRM is defined using a Model Based Systems Engineering (MBSE) approach and an overall Ship Design System Architecture to define and understand the relationships between various aspects of the ship design. The system architecture includes the DRM and enables the development of Operational Effectiveness Models (OEMs) as an alternative to an expert opinion-based OMOE. The system architecture also provides the means for redefining and optimizing the entire ship design process by capturing the entire process and all related data into a single repository. This thesis concludes with a preliminary assessment of the utility of these various system engineering tools to the naval ship design process.

The goal of this research was to discern the effects of introducing uncertainty representation into a set-based design process with applications in ship design. The hypothesis was that introduction of design uncertainty would enhance the facilitation of set-based design practices. A presentation of three fuzzy logic agent based methods for facilitation of set-based ship design practices is offered. The first method utilized a type-1 fuzzy logic system to facilitate set-based design practices and possessed no uncertainty modeling. The next two methods included representation of design uncertainty in the set-based design space. Of these two methods, one utilized a novel approach that harnessed techniques of randomization to model an interval type-2 fuzzy logic system, the other method made use of general type-2 fuzzy logic methods that were well-known, but still relatively under-utilized in academics and industry when compared to type-1 fuzzy logic systems. Comparisons of the newly developed fuzzy logic systems with each other, and the type-1 agent based fuzzy logic system provided the basis for conclusions as to the effects of introducing uncertainty modeling into a set-based design process. The results of this experimental research have shown that the inclusion of uncertainty modeling in the set-based design process for the negotiation of design variables enhances the overall set-based design progression, especially when working with highly constrained designs. In the case of a highly constrained design, the type-1 fuzzy logic system was unable to promote set-convergence within the allotted experimental time without repeated design failures, while the use of uncertainty modeling allowed the interval type-2 modeling and general type-2 fuzzy logic systems to achieve feasible set-based design convergence. When performing a simplistic, loosely constrained design, all three fuzzy logic systems were capable of facilitating the principle practices of set-based design within the feasible solution space; specifically, the set-based practices of delaying design decisions and gradual reduction of the feasible solution space. This research has led to the enhancement of the set-based design process by providing capabilities to now represent uncertainty in the set-based design space though the use of either the newly developed interval type-2 or general type-2 fuzzy logic systems.

High speed planing craft play key roles in supporting several critical maritime activities, e.g., coastal surveillance, reconnaissance, life-saving operations, passenger and high value cargo transport. Despite their significant use, formal optimization frameworks have rarely been proposed to deal with their design challenges. In this thesis, an optimization framework for the preliminary design of high speed planing craft is presented. Several case studies of single- and multi-objective formulations of high speed planing craft design problem are solved using state-of-the-art optimization algorithms. The notion of scenario-based design optimization and innovization, i.e. a means to uncover design relations are also discussed. A modular, extensible design optimization framework that allows the analysis tools to be extended or replaced with the desired level of complexity or with the state-of-the-art analysis tools is proposed in this thesis. A validated 3D mathematical model of high speed planing craft hull form has been identified in this thesis. The use of global parametric transformation that preserves surface fairness and allows for the presence of curve discontinuities is incorporated. A suite of three state-of-the-art optimization algorithms, namely NSGA-II, IDEA and SA-EA is incorporated within the framework. The performances of the algorithms are compared using the case studies. Solutions to single-objective minimization of calm water resistance, resistance in a seaway and multi-objective formulations considering minimization of total resistance, vertical impact acceleration and steady turning diameter have been presented. The capability of the framework to capture design trade-offs is illustrated. The case studies are extended to provide for scenario-based design optimization in order to demonstrate the capability of the framework to solve optimization problems based on the ship's operational profile and operating conditions. A concept of innovization, which allows for the automatic discovery of design rules governing optimum hull forms, is introduced. The relationship gathered through the process of innovization is applied as a cheap pseudo-performance indicator within an optimization formulation, where the results compare favourably with the empirical estimate obtained from experimental data. Such extensions are new contributions to the ship design discipline, in which opens up the possibility of the development of optimum design rules for any particular ship class.

A new approach to generating, evaluating, and optimizing general arrangements of naval surface ships is presented. Beginning from a user editable database of spaces, the algorithms return an optimized arrangement. The user drives the design by quantitatively defining spaces’ goals and constraints for location, proximity, and shape. The arrangements task is undertaken in two parts: Allocation and Arrangement. Allocation is the assignment of a space to a region of a ship. The unit region used is dubbed a Zone-deck. The Zone-deck is the intersection of one deck and one watertight subdivision. The allocation solution evaluates Zone-deck area utilization and spaces’ relative and global position goals. Adjacency and separation distance between spaces is measured in increments of deck and subdivision. Global position is assessed by deck and subdivision. Each discrete distance and position has an editable default fuzzy preference value. Allocation is essentially a very large scale combinatorial bin packing problem. With the added complexity of relative location constraints, this also becomes a type of quadratic assignment problem. The independent variable vector is an ordered listing by space index number of each space’s assigned Zonedeck index number. A customized Genetic Algorithm optimizes the integer-coded chromosome. The second part arranges one Zone-deck at a time. Arrangement is done in two iterative steps: topology and geometry. Topology gives the relative longitudinal and transverse position of each space’s seed location. These locations are translated onto an orthogonal grid. In the second step, spaces are expanded to have size and shape filling the available area in the stochastic growth loop. Spaces are defined by up to three contiguous boxes allowing for L, T, C and Z shapes. The arrangement cost function evaluates each space’s required area satisfaction, aspect ratio, minimum overall dimension, minimum segment dimension, perimeter, connectivity to access, and proximity constraints to other spaces. Editable piecewise linear fuzzy utility functions translate each criteria measure to a fuzzy utility. The best of a modest number of geometry solutions returns joiner bulkhead locations and a cost function value to a Genetic Algorithm optimization of the topology chromosome.

A methodology is presented for optimizing commonality decisions in multiple classes of ships with consideration of mission effectiveness, construction costs, and the savings that will result from the use of commonality. Currently the automobile and consumer product industries apply commonality methodologies in developing families of products that use a common platform. From the use of common components, a manufacturer can realize significant savings in a given line of products. If properly applied, the shipbuilding industry could also see significant cost savings from the use of commonality. An approach to the optimal use of commonality has been developed for the design of different classes of ships using a platform of common components. Unlike previous methodologies, this optimization process takes into explicit consideration the savings associated with the use of commonality. A ship synthesis model was adapted to create ship designs from independent design variables in order to predict the mission performance and calculate construction costs for each design. This was linked with a fleet commonality savings model reflecting savings from bulk purchases of equipment and the shipbuilding learning curve. The commonality items considered were the cruise engines, ship service generators, weapons, superstructure, and midship hull blocks. A multicriterion evolutionary algorithm is utilized to efficiently search the design space for feasible designs of multiple classes of ships. The criteria studied are the mission performance of ship class A/average cost, performance of class B/average cost, and net fleet savings through commonality. Through the use of dominance sorting and genetic operators, offspring solutions are developed in order maximize multiple design objectives from one generation to the next. The resulting solutions form a discrete Pareto front that allows the designer to choose a suitable set of designs to best meet the mission needs of multiple ship classes. The design methodology is demonstrated and tested through a problem modeled on the U.S. Coast Guard Deepwater High and Medium Endurance Fleet missions to enable interpretation of results. Results demonstrate that the methodology presented will prove to be a valuable tool in making good commonality decisions.

Ship design, like many engineering problems, involves both objective knowledge such as mathematical models and subjective knowledge such as expert opinion or design requirements. Fuzzy set theory is a method of systems analysis that bridges the gap between traditional methods of analysis and the real world relationships between variables that are ambiguous. This dissertation focuses on a set-based design approach to the cross-functional design team (Integrated Product Team) activity in early ship design. A hybrid agent analogy with human agents aided by intermediate computer agents is utilized. A new implementation of a fuzzy system has been developed to enable these designers to communicate their preferences over a range of parameter values. The system involves a new input sequence compared to classical fuzzy systems and improves scalability through the use of meta rules. The new hybrid agent fuzzy system is unique in that the inputs are the membership functions mui(x) which are changed by the human agents to express their individual preferences for a particular design parameter as a design progresses. The fuzzification, linguistic fuzzy rule bank, fuzzy inference, and defuzzification components are typical. The input membership functions and the output variable span the set-based range currently under consideration from the parameter's lower limit to its upper limit. The output is, however, a crisp value function of the design variable indicating the joint preference of the team of human design agents over the current set of that variable. A new fuzzy logic software agent to enable hybrid agent design team communication and negotiation has been developed in JAVA(TM). A series of pair comparison design experiments in which non-collocated student design teams designed a small feeder containership using the new agent software or a chat window environment have been completed. The goal of the pair comparison experiments was to eliminate experimental biases and give an accurate evaluation of the fuzzy logic approach. The results and analysis of the experiments have demonstrated that the fuzzy logic software agent does enable set-based design thus increasing the probability of achieving a global optimum when compared to conventional team-based design systems.