A data-driven UUVs bionic design method toward emotional and energetic sustainability using AI-based morphological synthesis - Yang, Chaoxiang; Zhao, Xiyue; Ye, Junnan (Expert systems with applications, 2026)
Unmanned Underwater Vehicles (UUVs) have traditionally adopted an engineering-oriented design paradigm, prioritizing functional performance and energy efficiency while neglecting users’ emotional experiences with product morphology. This imbalance has hindered the achievement of both emotional and environmental sustainability. As UUVs expand into the consumer market, users now expect not only high technical performance but also emotionally engaging morphological features, which pose new challenges for product design. To address this issue, this paper proposed a bionic morphology design methodology that integrated emotional and energetic sustainability to achieve comprehensive product sustainability. First, a mapping between product semantics and biological features was constructed to infer bionic prototypes aligned with user emotional preferences. Then, key biological features were extracted through eye-tracking experiments, and preliminary design alternatives were generated using generative artificial intelligence (AI). These alternatives were subsequently evaluated using facial expression analysis (FEA) to quantify emotional responses for emotion-based selection. Finally, Computational Fluid Dynamics (CFD) simulations were employed to evaluate and optimize the energy efficiency of the selected alternatives. The results indicate that the selected alternative, while maintaining emotional alignment, achieved a significantly lower hydrodynamic drag coefficient than the other alternatives. This core quantitative finding verifies the method’s effectiveness in simultaneously addressing emotional and energetic dimensions. Overall, this research provided a systematic framework for sustainable UUVs morphology design. It also offered engineering readers theoretical insights and methodological guidance for multi-objective design of complex products.