SUMMARYThis paper concerns development and demonstration of a computational uid dynamics (CFD)-based multi-objective optimization method for ship design. Three main components of the method, i.e. computer-aided design (CAD), CFD, and optimizer modules are functionally independent and replaceable. The CAD used in the present study is NAPA system, which is one of the leading CAD systems in ship design. The CFD method is FLOWPACK version 2004d, a Reynolds-averaged Navier-Stokes (RaNS) solver developed by the present authors. The CFD method is implemented into a self-propulsion simulator, where the RaNS solver is coupled with a propeller-performance program. In addition, a maneuvering simulation model is developed and applied to predict ship maneuverability performance. Two nonlinear optimization algorithms are used in the present study, i.e. the successive quadratic programming and the multi-objective genetic algorithm, while the former is mainly used to verify the results from the latter. For demonstration of the present method, a multi-objective optimization problem is formulated where ship propulsion and maneuverability performances are considered. That is, the aim is to simultaneously minimize opposite hydrodynamic performances in design tradeo . In the following, an overview of the present method is given, and results are presented and discussed for tanker stern optimization problem including detailed veriÿcation work on the present numerical schemes.
The Reynolds-averaged Navier–Stokes (RANS)-based computational fluid dynamics (CFD) calculation using a two-equation turbulence model, such as the k–omega shear-stress transport (SST) model, is a mainstream method with sufficient accuracy for the estimation of integral hydrodynamic forces and moment at both the model-scale and full scale. This paper confirmed that the Reynolds stress model (RSM) has sufficient estimation accuracy of viscous resistance and wake distribution at the hull design stage. Herein, the ability of RSMs to estimate the viscous resistance and wake distribution of a JBC ship is evaluated. Specifically, the verification and validation (V&V) method is employed to indicate the numerical and model uncertainties of each turbulence model used to estimate the viscous resistance. The RSMs showed higher numerical uncertainty than the k–omega SST. However, the uncertainty of the experimental measurements is generally smaller than the numerical uncertainty. Moreover, the linear pressure–strain (LPS) and the linear pressure–strain two-layer (LPST) models show less comparison error of the viscous resistance than the k–omega SST. Furthermore, the LPST and k–omega SST models are applied to twenty ships with various full and fine hull forms to calculate the viscous resistance and compare it with the experimental results. The viscous resistance of the LPST model showed a small difference when employed in experimental fluid dynamics (EFD) and CFD calculations. Using the LPST model, the viscous resistance can be estimated with high accuracy in our setting. For industrial use, this study could provide an important insight into the designing of various types of vessels.
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