@article{HE2026, 
author = {Xiaodong HE and Bingqi SI and Miaomiao LI and Yi HONG and Weicheng JIAO},
title = {Novel materials and intelligent design methodologies for naval vessels},
year = {2026},
journal = {Chinese Journal of Ship Research},
volume = {21},
number = {4},
pages = {138-155},
keywords = {composites, sandwich structures, metamaterials, functional-structural integration, artificial intelligence, intelligent design},
url = {https://www.sciopen.com/article/10.19693/j.issn.1673-3185.04966},
doi = {10.19693/j.issn.1673-3185.04966},
abstract = {Escalating maritime security demands higher comprehensive stealth, energy efficiency, structural reliability and multifunctional integration performance for naval vessels. Conventional design modes dependent on metal materials and empirical design suffer inherent drawbacks such as long R&D cycles and high costs. Against this backdrop, the collaborative innovation of new functional-structural integrated materials and intelligent design has become a core route to break through the performance bottlenecks of naval vessels. This paper systematically reviews the research progress of marine new materials and intelligent design technologies, and analyzes their synergistic relationship and engineering constraints. In terms of new materials, fiber-reinforced polymer composites (carbon, glass, aramid fiber composites) feature outstanding specific strength, corrosion resistance and designability, and are widely adopted in hulls, superstructures, propellers and pressure cabins. Composite sandwich structures (foam, balsa, honeycomb, foldcore, lattice core) further realize lightweight design and integrate sound absorption, heat insulation and anti-impact functions. As a new type of artificial material, acoustic metamaterials (phononic crystals, local resonance structures, Helmholtz resonators, acoustic cloaks) solve the low-frequency wideband sound absorption defects of traditional materials and provide new ideas for underwater acoustic stealth. Artificial intelligence technologies reconstruct the functional-structural integrated design system of ships. Artificial neural networks act as high-efficiency surrogate models to rapidly predict mechanical and acoustic properties of composite materials and metamaterials. Generative large models can create innovative topological structures to expand the design space beyond empirical limits. Intelligent optimization algorithms handle multi-objective and multi-constraint optimization tasks to balance lightweight, bearing and stealth performance. The closed-loop "generate–predict–optimize" design framework greatly shortens design cycles and maximizes material performance potential. This paper further summarizes the key engineering bottlenecks. For novel marine materials, the main challenges include large-scale forming stability, long-term marine aging degradation and recycling difficulties. For intelligent design methods, critical limitations lie in insufficient professional datasets, poor interpretability of black-box AI models and the disconnection between design optimization and manufacturing constraints. In the end, this paper prospects future research trends, including multifunctional composite integration, cross-scale multi-physics coupled design, interpretable intelligent design systems and full-lifecycle structural intelligent management. This review provides theoretical support and technical references for the development of high-performance, lightweight and intelligent naval vessels.}
}