Cognitive Digital Ocean: integration of quantum hybrid computing, digital twins and graph neural networks for bioresource and fleet management. Part 2

The paper presents the concept of the Cognitive Digital Ocean (CDO) – a multi level cyber physical system for managing the fishery complex, integrating quantum hybrid computing, physics informed neural networks (PINN), graph neural networks (GNN), a hierarchy of digital twins (from genome to global ocean), and fractal analysis of the spatial distribution of bioresources. Special attention is paid to the shipbuilding aspect: mathematical models of the ship power plant (SPP), controllable pitch propeller (CPP), propulsion complex, and hull hydrodynamics are presented. It is shown that solving the fundamental Millennium Problem – the Navier Stokes equations – on quantum computers opens up fundamental possibilities for hydrodynamic forecasting with a horizon of up to 30 days. The system is aimed at solving the strategic tasks of the Russian Federal Agency for Fisheries (Rosrybolovstvo) until 2030: increasing production by 25%, digital transformation, and technological sovereignty. The limitations of the applicability of quantum methods are considered and engineering workarounds are proposed.