Topic outline

  • Aquaculture production

    Aquaculture production has significantly increased.

    Globally, it recently exceeded the production by fishing boats and fisheries.

    Our laboratory aims to improve the efficiency of aquaculture production by conducting simulation research.

    • Flow field simulation of aquaculture tank

      Complete aquaculture has the highest mortality rate in seedling production (from hatching to the larval stage), which has been a bottleneck for mass production.

      It is known that fish  at the larval stage are easily affected by the flow in the aquarium due to their low swimming ability and are prone to sinking death (a phenomenon in which they are damaged and die when hitting the bottom of the aquarium).

      To prevent sinking death, the flow field in the aquarium must be set to avoid a sudden downward flow.

      Our laboratory is working on visualizing the flow in the culture tank using fluid simulation (CFD analysis) and visualization experiment (PIV experiment), with the aim of improving the breeding environment in the tank.


      エアレーションによる流場

      Figure 1. The flow field in an aquarium generated by aeration.


      PIV

      Figure 2. Visualization experiment targeting the flow field generated by aeration.


      • Feeding simulation

        The cost of feed in aquaculture production is high, but efficient feeding  is expected to reduce the cost.

        Currently, we are working on simulating the feeding behavior of fish and their growth by coupling the fish school behavior model (Boid model, see separate section) and the growth model.

        Here, the differences in growth between the following two types (A: wide-range feeding, B: narrow-range feeding) are compared by simulation.


        Figure 3. Feeding range in the simulation 


          

         

        Video 1. Simulation of feeding condition A

         

         

        Video 1. Simulation of feeding condition B


        The final growth results are shown below. Feeding over a wide range (feeding condition A) resulted in less variation.

        We plan to use this simulation to identify the most profitable feeding method in the future.


        Figure 4. Breeding results after 90 days