The purpose of the study is to develop a set-based design framework which integrates high-fidelity physics-based simulation tools early in ship concept design, and to apply it to practical ship design problems. Any ship design methodology, either based on successive refinement of an initial concept (traditional design-spiral based), or innovative methodologies such as set-based [1~3], must address and harmonize a broad spectrum of mission requirements, as well as technical requirements [4~6] considering objectives of cost, risk, and overall mission effectiveness. All this, of course, while ensuring the technical consistency of the design as a whole. Brown et. al. have successfully developed a C&RE (concept and requirements exploration) framework  to optimize the concept design of monohull and trimaran naval ships . A great advantage of this C&RE framework is the mathematical reduction of broad design variable sets for convergence to a set of non-dominated (Pareto) designs using set-based methods and a multi-objective genetic algorithm. Discipline-specific explorations are performed independently, following the principles of set-based design. Feasible design space sets and individual discipline response surfaces developed in the discipline explorations are applied and integrated to identify overall feasible non-dominated designs. However, one of the common drawbacks of the current C&RE framework and similar concept design frameworks is that design synthesis and analysis are performed using low-fidelity models with limited accuracy, and the resulting designs and their assessment can be greatly different from designs created and analyzed using high-fidelity analysis . The contributions of the study are several to solve these issues: 1) high-fidelity physics simulations are integrated early in the design through a variable-fidelity response surface, 2) coupled sensitivities are calculated to determine the coupling strengths among the subsystems and for dimension reduction, 3) a Bayesian probability-based fidelity indicator predicts the required fidelity to analyze new design candidate points, and 4) adaptive sampling techniques of filtering and infilling samples are used to further increase the efficiency of the design framework. A brief schematic of the proposed design framework is shown in Fig. 1 with three objective functions with N design variables. In the full paper, variable-fidelity (VF) hydrodynamics analysis methods including linear inviscid panel method, Euler, and URANS solvers are used. CFD solution examples analyzed by the VF are shown in Fig. 2. A Bayesian fidelity indicator  and the adaptive sampling criteria  were developed in an author’s previous study  and will be directly utilized in the full paper. Major modifications to the C&RE frameworks will be made in a full paper which cover 1) the inclusion of the high-fidelity physics simulation per design iteration based on the probabilistic value of the dynamic fidelity indicator, 2) the variable-fidelity response surface, and 3) adaptive infill and filtering sampling criteria. Example application of the design method is chosen for the design of hullform and propular will be carried out which include their flow interactions.
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