2023/02/18 by Harsh Vardhan, Vardhan, Harsh, János Sztipanovits +1
Engineering · Environmental Science · #Artificial Intelligence (cs.AI) #Computational Engineering #FOS: Computer and information sciences #Finance #Maritime Navigation and Safety #Maritime Transport Emissions and Efficiency #Ship Hydrodynamics and Maneuverability #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.2302.09441
openalex publication_date 2023/02/18 · openalex created_date 2023/02/22 · openalex updated_date 2026/07/28
In Autonomous Underwater Vehicles (AUVs) design, hull resistance is an important factor in determining the power requirements and range of vehicle and consequently affect battery size, weight, and volume requirement of the design. In this paper, we leverage on AI-based optimization algorithm along with Computational Fluid Dynamics (CFD) simulation to study the optimal hull design that minimizing the resistance. By running the CFD-based optimization at different operating velocities and turbulence intensity, we want to study/search the possibility of a universal design that will provide least resistance/near-optimal design across all operating conditions (operating velocity) and environmental conditions (turbulence intensity). Early result demonstrated that the optimal design found at low velocity and low turbulence condition performs very poor at high velocity and high turbulence conditions. However, a design that is optimal at high velocity and high turbulence conditions performs near-optimal across many considered velocity and turbulence conditions.