C-ShipGen: A Conditional Guided Diffusion Model for Parametric Ship Hull Design
International Marine Design Conference(2024)
摘要
Ship design is a complex design process that may take a team of naval
architects many years to complete. Improving the ship design process can lead
to significant cost savings, while still delivering high-quality designs to
customers. A new technology for ship hull design is diffusion models, a type of
generative artificial intelligence. Prior work with diffusion models for ship
hull design created high-quality ship hulls with reduced drag and larger
displaced volumes. However, the work could not generate hulls that meet
specific design constraints. This paper proposes a conditional diffusion model
that generates hull designs given specific constraints, such as the desired
principal dimensions of the hull. In addition, this diffusion model leverages
the gradients from a total resistance regression model to create low-resistance
designs. Five design test cases compared the diffusion model to a design
optimization algorithm to create hull designs with low resistance. In all five
test cases, the diffusion model was shown to create diverse designs with a
total resistance less than the optimized hull, having resistance reductions
over 25
This work can significantly reduce the design cycle time of ships by creating
high-quality hulls that meet user requirements with a data-driven approach.
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