Computationally aware and physically plausible hull form optimization incorporating the IMO intact stability code

Abstract

Optimizing the hull form is crucial for enhancing vessel performance, requiring a careful exploration of design variations once an initial concept is chosen. To address this, a well-defined parameterization and search space must be established, followed by a numerical optimization process. This phase involves balancing three key requirements: improving performance indicators like resistance (and consequently emissions), ensuring physical plausibility (e.g., designs that meet stability standards), and maintaining computational efficiency. While existing methods partially address these challenges using surrogate models to optimize performance, conducting a-posteriori checks for physical plausibility, and reducing the search space a-priori, they fall short of fully integrating these aspects. In this work, we introduce a two-fold approach to address these challenges. First, we integrate a key physical plausibility criterion directly into the optimization loop: the International Maritime Organization (IMO) Intact Stability Code. For the first time, we use a surrogate model to include this constraint within the numerical optimization process. This enables the generation of designs that inherently meet stability requirements. Second, we reduce the computational demands by applying data-driven methods to limit the search space in a problem-specific manner. This targeted reduction reduces the computational load without compromising the overall optimization performance. We test our proposal by optimizing the KCS hull form. Our results demonstrate two main achievements. First, we find that current optimization pipelines fail to meet the IMO stability guidelines, whereas our method achieves compliance by design. Second, our approach reduces the computational burden by 30 % without sacrificing performance, representing a significant leap forward in practical hull design optimization.