The topology of planing hulls entails some of the most innovative specifications found in
modern advanced marine vehicles. Planing hull designs can vary depending on their …

The rapid growth of deep learning research, including within the field of computational
mechanics, has resulted in an extensive and diverse body of literature. To help researchers …

The construction material quantity (CMQ) is widely concerned in the structural design of
reinforced concrete buildings and is often included among the objective functions of …

In this work, we propose a set of physics-informed geometric operators (GOs) to enrich the
geometric data provided for training surrogate/discriminative models, dimension reduction …

Abstract Machine learned generative design is an extension of the generative design
process, addressing its inherent limitations, particularly those of interoperability. The …

Ship design is a years-long process that requires balancing complex design trade-offs to
create a ship that is efficient and effective. Finding new ways to improve the ship design …

Our work presents a novel approach to shape optimization, with the twofold objective to
improve the efficiency of global optimization algorithms while promoting the generation of …

In this work, supervised Machine Learning (ML) techniques were employed to solve the
forward and inverse problems of airfoil and hydrofoil design. The forward problem pertains …

The maritime industry is transporting about 90% of world commerce, contributing to the
global greenhouse gas emissions that cause climate change. Increasing pressure on the …

Parametric models have been widely used in pertinent literature for reconstructing,
modifying and representing a wide range of airfoil and/or hydrofoil profile geometries …