Westinghouse Research Laboratories P i t t s b u r g h , PA 15235 ABSTRACT High current density homopolar machines which emp l o y c u r r e n t c o l l e c t o r s c o n t a i n i n g a l i q u i d metal, such as NaK, r e q u i r e c r i t i c a l support systems to guarantee long term machine operation. This r e p o r t d e s c r i b e s experimental results concerning materials compatibilit y , l i q u i d metal r e c i r c u l a t i o n and p u r i f i c a t i o n spstem, and the inert, protective cover gas systems necessary for machine operation. Experimental studies, as well as operation of a 3000 €IP,107,000 ampere, 20 volt, dc homopolar generator have demonstrated the n e c e s s i t y of such subsystems to continued machine operation.
Automation plays a key role in shipping industry and aims towards minimal operating staff. However, the effective automation relies on effective controlling at various levels starting from shipbuilding to navigation. The industry is currently focussing on autonomous shipping which actually requires precise controlling. Although many conventional methods are available for control and automation with regard to automation, Artificial Intelligence Schemes (AIS) are widely attracting the maritime sector because of their benefits. The AIS along with fuzzy logic systems are offering promising results. The emerging use of AIS in a variety of maritime applications can act as a reference wpoint for new researchers. This paper aims to conduct a valid AIS study and to examine the various machine learning approaches used in various maritime applications. It is possible to achieve complete automation in the shipping industry by implementing a related technique.
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