  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.
