Optimization Approach for a Catamaran Hull Using CAESES and STAR-CCM+

Abstract

Simulation-driven design is one of the most important methods for ship optimization. With the development of computer-aided design technology, research on hull shape optimization through computer simulation has gradually been applied to design more energy-efficient and environmentally friendly ships. In the preliminary design stage, it is very important to optimize the hydrodynamic characteristics of the hull form. As computers speed up and memory grows, researchers are experimenting more with Computer Aided Design (CAD) and simulation (CFD) methods. Due to the complex geometry shape of a ship's hull, it is difficult to use numerical methods to describe it. Therefore, researchers often choose to modify the hull form by making changes to a basic design. Lackenby (1950) developed a method to modify a hull by controlling the position of the center of buoyancy and shifting the section curves. Since then, the Lackenby method has been widely used in hull modification. In recent years, there have mainly been two popular ways of modifying a bulbous bow geometry: parametric modeling and the Free-Form Deformation (FFD) method. Chrismianto and Kim (2014) used a Cubic Bezier curve and curve-plan intersection methods to generate a parametric bulbous bow. Luo and Lan (2017) used a B-Spline curve and NURBS curve to generate a parametric bulbous bow in the CAD-CFD integration platform CAESES. Plug-in software called Grasshopper was used to generate a parametric bulbous bow from a few vertexes and NURBS curves. The wave-making resistance of a ship hull depends largely on the bow part (the area between the stem and mid-ship). It is efficient to optimize the bow part of a ship to reduce the wave-making resistance. The bulbous bow and the hull between the bulbous bow and mid-ship are two main parameters to optimize. Different governing equations are used in a CFD solver to predict a ship hull's hydrodynamic performance. One of the most popular methods is the Reynolds averaged Navier-Stokes (RANS) method. Zhang et al. (2018) used the RANS method to calculate the total resistance in an optimization framework (Park et al., 2019; Kim et al., 2019). Usually, hundreds of simulations are carried out in an optimization process, and the hydrodynamic performance prediction can be quite a time consuming. Researchers have tried different ways to reduce the computing time. Han et al. (2012) selected a non-linear potential flow using the Rankine panel method to predict trim and sink

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