Physics-Based Direct Multi-Scale Modeling and Simulation of the Hydrodynamics of Aquaculture Farm including Interactions with Fish Schools and Flexible Structures

· 02/2023 - 01/2024

Project number: 2023-R/RRFA-012

Lead PI: Dick Yue, MIT

The key objective is the development of physics-based multi-scale modeling and simulation of the hydrodynamics of aquaculture farm. The simulations include the modeling of fish-like swimming, fish-fish hydrodynamic interactions, and the dynamics of fish schooling. The hydrodynamics will also track relevant scalar transports of nutrients, effluents and biological organisms. The final project goals are detailed simulation capabilities, quantitative predictions and knowledge base that inform optimal coastal and offshore fish aquaculture site selection, design, and operations. The model/simulations will also provide large physics-based datasets that would support complementary machine learning and intelligent digital models.

A combined theoretical and numerical approach is employed to model the flow dynamics within a fish farm net cage including the interactions of the (deformable) cage with ambient waves and currents, the hydromechanics of fish swimming and schooling, and the transport of nutrients and effluents within the cage. These components are modeled theoretically and combined in a highly efficient multiple-scale coupled simulation of the complete problem. These large-scale direct physics-based simulations will be used to understand and assess the flow and fish behavior and health inside net cage, leading to optimized fish farm site selection and design and operations.

While a much research and development has been devoted to the modeling of sea loads and global motions of marine aquaculture structures in waves and current, there exists almost no direct investigation of the hydrodynamics and water quality within a net fish cage. Obtaining insights and modeling capability of detailed flow dynamics inside net cage, especially including fish swimming, fish-fish interactions and schooling, is a challenging task but is of critical importance to the improvement of fish farm placement, design and operations, leading to optimized fish health and production, while minimizing the environmental footprint and impact of fish farming.