Multi-fidelity hydrodynamic analysis of an autonomous surface vehicle at surveying speed in deep water subject to variable payload

Autonomous surface vehicles (ASV) allow the investigation of coastal areas, ports, and harbors as well as harsh and dangerous environments such as the arctic regions. In the past decade, several studies addressed the shape optimization, control and stability, and seakeeping of ASVs. Nevertheless, the hydrodynamic analysis of ASV performance subject to variable operational parameters lacks a thorough investigation. In this context, this paper presents a multi-fidelity (MF) hydrodynamic analysis of a catamaran ASV, namely the shallow water autonomous multipurpose platform (SWAMP), at surveying speed in calm water and subject to variable payload and location of the center of mass, accounting for the variety of equipment that the vehicle can carry. The analysis is conducted in deep water, which is the condition mostly encountered by the ASV during surveys of coastal and harbor areas. The objective of the analysis is the investigation of the effects of the payload and its arrangement on the variations of the resistance, the vehicle attitude, and the wave generated in the region between the catamaran hulls. These are assessed using an unsteady Reynolds-averaged Navier-Stokes equation (URANSE) code and a linear potential flow (PF) solver. The latter also includes variable grid refinement and coupling between hydrodynamic loads and rigid body equations of motion. Furthermore, the limitation of a PF analysis in the current context is investigated. Finally, a multi-fidelity Gaussian process (MF-GP) model is obtained combining high- (URANSE) and low-fidelity (PF) solutions following an additive correction approach of the latter. The MF-GP model is iteratively refined using an active learning approach based on the maximum prediction uncertainty and the computational cost of the numerical simulations. Numerical results show that the MF-GP is effective in producing response surfaces of the SWAMP performance with a limited computational cost. It is highlighted how the SWAMP performance is significantly affected not only by the payload, but also by the location of the center of mass. The latter can be therefore properly calibrated to minimize the resistance and allow for longer-range operations.