As unmanned vehicle capabilities have matured, the design and development of autonomous collaborative Systems-of-Systems (SoS) has gained increased attention. This has been motivated by the indication that significant improvements in overall effectiveness may be possible by employing many systems in cooperation with one another. However, as the potential combinations of vehicles, subsystems, and operational concepts becomes increasingly large, a systematic approach is needed for designing and analyzing alternatives. Furthermore, the discrete nature of the problem can cause variations in effectiveness that are counter-intuitive, such as a point of diminishing returns as the number of systems grows. Systems-of-systems are hierarchical in nature, consisting of top-level mission requirements that are decomposed into system- and subsystem-level performance measures. The overarching research objectives of this dissertation are to show that the analysis of alternatives should be performed at varying levels of the SoS hierarchy and to provide novel means for performing those analyses. In particular, it has been postulated that a formulation built on an energy-based approach to multi-level analysis of SoS components will enable more accurate and transparent subsystem and system trade-offs. Various steps of the design process are established and argued for or against, and significant focus is placed on the analysis of alternatives. The foundation of the new method is laid on structured SoS engineering principles. The full substance comes together by incorporating unique aspects developed within this dissertation. A new virtual experimentation approach is presented for creating sensor performance representations that are functions of vehicle operations. The sonar equation is used as a baseline sensor model for comparison against the new virtual experimentation method. Dozens of forward-looking and side-scan sonar experiments are designed, and data is provided to show the extent to which typical sensor modeling over-predicts performance without vehicle operations considered. In addition, comparisons are made between possible representations of vehicle performance. An underwater vehicle sizing and synthesis process is developed to enable comparisons between system-level component modeling approaches. The experiments attest to significant gaps in accuracy when performing sensor and operational trade-offs without energy-based modeling of the collaborative vehicles. Finally, a heuristic path-planning algorithm is formulated, and mixed-integer linear programming is used to choose between alternative SoS designs. The developed method is demonstrated through a representative example problem: a group of unmanned underwater vehicles (UUVs) operating in a collaborative fashion to search for underwater objects. The example scenario provides an application for illustrating the phenomenon discussed in regards to the analysis of alternatives of collaborative SoS. The significance of providing more or less analytic detail is traced and the effect on mission requirements is quantified. Counter-intuitive results are highlighted, such as the observation that the increased energy required for systems to effectively collaborate can often out-weigh the benefits gained in overall mission effectiveness.

A supercavitating vehicle, a next-generation underwater vehicle capable of changing the paradigm of modern marine warfare, exploits supercavitation as a means to reduce drag and achieve extremely high submerged speeds. In supercavitating flows, a low-density gaseous cavity entirely envelops the vehicle and as a result the vehicle is in contact with liquid water only at its nose and partially over the afterbody. Hence, the vehicle experiences a substantially reduced skin drag and can achieve much higher speed than conventional vehicles. The development of a controllable and maneuvering supercavitating vehicle has been confronted with various challenging problems such as the potential instability of the vehicle, the unsteady nature of cavity dynamics, the complex and non-linear nature of the interaction between vehicle and cavity. Furthermore, major questions still need to be resolved regarding the basic configuration of the vehicle itself, including its control surfaces, the control system, and the cavity dynamics. In order to answer these fundamental questions, together with many similar ones, this dissertation develops an integrated simulation-based design tool to optimize the vehicle configuration subjected to operational design requirements, while predicting the complex coupled behavior of the vehicle for each design configuration. Particularly, this research attempts to include maneuvering flight as well as various operating trim conditions directly in the vehicle configurational optimization. This integrated approach provides significant improvement in performance in the preliminary design phase and indicates that trade-offs between various performance indexes are required due to their conflicting requirements. This dissertation also investigates trim conditions and dynamic characteristics of supercavitating vehicles through a full 6 DOF model. The influence of operating conditions, and cavity models and their memory effects on trim is analyzed and discussed. Unique characteristics are identified, e.g. the cavity memory effects introduce a favorable stabilizing effect by providing restoring fins and planing forces. Furthermore, this research investigates the flight envelope of a supercavitating vehicle, which is significantly different from that of a conventional vehicle due to different hydrodynamic coefficients as well as unique operational conditions.