Data-Driven probabilistic simulation of vessel operations to support the blue economy

• A data-driven probabilistic simulation model of vessel operations is proposed. • The model integrates stochastic environmental and operational parameters. • Probabilistic characterizations of key vessel operational metrics are produced. • The model is applied to five strategic regions in the U.S. Blue Economy. • Applications to offshore energy O&M and electrification planning are examined. Vessel operations are central to several Blue Economy industries, from offshore and marine energy to fisheries and aquaculture, ensuring efficient and safe transport of crew, equipment, and materials between ocean-based assets and land-based ports. Careful logistical planning of these vessels relies on accurate, data-driven simulation models of vessel operations which can rigorously account for the stochastic environmental parameters (i.e., met-ocean conditions) and operational parameters (e.g., route, activities, vessel speed and propulsion system). Along this line, we propose a data-driven simulation framework which integrates environmental and operational information to produce probabilistic characterizations of key vessel operational metrics, including serviceability, fuel consumption, emissions, and costs. Five case studies, focused on strategic regions in the United States (U.S.) Blue Economy, demonstrate the framework’s effectiveness in modeling vessel operations across diverse environments and operational conditions. While broadly applicable, we demonstrate the simulation framework’s value in two specific contexts: serviceability assessment to inform operations and maintenance (O&M) for offshore energy assets, and fleet electrification planning.