Early-Stage System-Level Optimization of a Fast Planing Monohull

The advantages of early-stage design space exploration (DSE) are well-recognized in the fast ship design community. DSE can significantly influence both fundamental design and business decisions, and it can enhance the effectiveness of subsequent simulations that employ resource-intensive higher-order codes. This study examines the potential of resource-efficient reduced-order simulation via semi-empirical parametric prediction models to provide valuable early-stage DSE. A systematic comparison will be given to an existing comprehensive 11-meter planing craft R&D project (AutoPlan). The reference project included viscous CFD predictions, towing tank tests, and full-scale sea trials. Hull form shape variants are developed using the parametric CAD features of the CAESES® shape optimization platform and will be coupled with the NavCad® hydrodynamic and propulsion system simulation tool rather than CFD for performance simulation. The goal is to follow the same design path as the previous R&D project for side-by-side comparisons of outcomes and resource expenditures, while also setting the stage for follow-on consideration for the evaluation and selection of drive systems. INTRODUCTION The design of high-speed craft is increasingly shaped by digital modeling tools that aim to accelerate development cycles while maintaining or improving vessel performance. Early-stage Design Space Exploration (DSE) plays a crucial role in this process, enabling informed decisions regarding hull form, propulsion, and operational efficiency before committing to more detailed and computationally expensive simulations. While high-fidelity models such as RANS-based Computational Fluid Dynamics (CFD) provide reliable performance predictions, their significant computational demands can be prohibitive, especially for smaller design offices or during the initial stages of product definition. This study investigates whether reduced-order simulation tools can offer sufficient fidelity to support early-stage DSE, thereby reducing time and resource requirements without compromising the quality of design decisions. We systematically evaluate this by benchmarking a reduced-order approach against a comprehensive design, test, and validation campaign from the AutoPlan project. The reference project involved an 11-meter planing monohull, optimized for a cruising speed of 27.5 knots and a displacement of 9.5 tons, featuring propellers in tunnels along conventional shaft lines. Its development incorporated hull form shape optimization with CAESES utilizing several free-form geometric hull shape parameters and coupled with RANS-based CFD for performance simulations (which were validated against towing tank experiments).