The urgency to mitigate greenhouse gas emissions from maritime vessels has intensified due to the increasingly stringent directives set forth by the International Maritime Organization (IMO). These directives specifically address energy efficiency enhancements and emissions reduction within the shipping industry. In this context, hydrogen is the much sought after fuel for all the global economies and its applications, for transportation and propulsion in particular, is crucial for cutting down carbon emissions. Nevertheless, the realization of hydrogen-powered vessels is confronted by substantial technical hurdles that necessitate thorough examination. This study undertakes a comprehensive analysis encompassing diverse facets, including distinct variations of hydrogen fuel cells, hydrogen internal combustion engines, safety protocols associated with energy storage, as well as the array of policies and commercialization endeavors undertaken globally for the advancement of hydrogen-propelled ships. By amalgamating insights from these multifaceted dimensions, this paper adeptly encapsulates the myriad challenges intrinsic to the evolution of hydrogen-fueled maritime vessels, while concurrently casting a forward-looking gaze on their prospective trajectory.

Micro-holes were fabricated using micro-EDM on the surface of WC/TiC/Co carbide, CaF2 solid lubricants were filled into these micro-holes to form self-lubricating tool (MST). Dry cutting tests on AISI 1045 hardened steel were carried out with the MST tools and conventional tools (CT). The cutting temperature were measured and compared. The results indicated that the cutting temperatures with the MST cutting tools were reduced compared with the CT tools, and the cutting speeds were found to have a profound effect on the cutting temperatures variations of the MST tool. Two mechanisms of cutting temperature decrease are found, the first one is due to the formation of a discontinuous CaF2 lubricating film on the tool rake interface, which may decrease the average shear stress; the other one can be inferred from the microholes on the rake face, which contribute to the reduction of contact length at the tool-chip interface

Aiming at wide variations in loads and moment of inertia of the machine tool position servo system, the position loop controller is designed based on RBF neural network control and predictive control. The mathematical model of AC PMSM is established. The predictive model is designed based on controlled autoregressive integral moving average model, obtained the predictive vector and the reference trajectory. The RBF neural network structure is established, tuning PID algorithm is designed. A new control strategy which combined with predictive control and RBF neural network PID control is obtained. Compared with the torque fluctuation, anti-interference ability and tracking properties of the traditional PID control, predictive control ensures that the system tracking performance and RBF neural network control can adjust PID parameters on-line, which guarantees the robustness in the external disturbance and parameter perturbation. The simulation results demonstrate that the RBF neural network predictive controller can guarantee the static and dynamic performance of the system.