Marine Crane Modeling and Analysis for Onboard Support

Abstract

The marine crane system is a multi-disciplinary complex system involving such as kinematics, dynamics, hydraulics, operational control, etc. The working environment of marine cranes is unpredictable, and offshore operations are challenging due to the harsh weather conditions and rough sea conditions. These environmental loads introduce intense motions in six degrees of freedom, leading to a dynamic base for the marine cranes. This dissertation introduces a digital solution for the modeling and analysis of marine cranes for onboard support, aiming to provide valuable insights into the optimization and enhancement of marine operations through digital technology. The increasing complexity of computer tools has led to a corresponding complexity in model development and analysis, with simulations and applications in specific fields being constrained by the development of tools within those fields. Marine operating systems are characterized by intricate interactions between a wide range of physical and engineering domains. Co-simulation technology allows for the independent development and validation of different subsystems using the tools best suited for each domain, and their integration into a unified simulation environment. This effectively addresses the challenges of integrating diverse models, accommodating different modeling languages, and utilizing specialized extension libraries. The main objective of the research is to establish a holistic framework for marine crane simulation and onboard support development based on co-simulation technology. This dissertation highlights three cases following the research route. The FMI standard defines a shared format to support model exchange and co-simulation of dynamic models. It enables model development without being confined to specific domain tools. The SSP standard defines a standardized way to store and apply parameters to these components, providing a standardized format for the connection structure of a network of components (FMUs in particular). These two powerful and independent standards facilitate the construction of marine operating systems in a virtual co-simulation environment, allowing for seamless integration and efficient system development. Within the framework, users can substitute models and modify parameters for all the components, and also configure environmental loads or incorporate real data to observe system performance in various scenarios. Based on this, a path planning case using A star algorithms is implemented. The results provide the feasibility of conducting the application development of the marine operation onboard support based on the virtual marine operation system using the co-simulation approach. An increasing number of systems and processes on board a modern vessel are dependent on computers and networks for monitoring and control. Feedback loops from system measurements are included in the computations and affect the controllers. As these systems exploit the benefits of increased connectivity and various sensors, the complexity level is rising and new methods for design, testing and verification are required. A major advancement in digital twin development is the integration of data-driven and model-driven approaches. This integration allows for the creation of digital twins that combine data-driven models, which are based on empirical data with physics-based models. The co-simulation framework also supports this maritime industry’s progression towards more data-driven and automated processes, which is foundational in its ability to provide a robust platform for innovation and continuous improvement in marine operations. Thus another focus of this dissertation is to validate the virtual marine operation system as a digital twin, where the field experiments on the vessel R/V Gunnerus are carried out with data collected compared with its in the DT simulator. The demo case offers a valuable solution for operation evaluation in challenged conditions for demanding marine operations.