Estimation of Seaweed Twist Based on Diffusion Kernels in Physical Simulation
Jun Ogawa*, Masahito Yamamoto*, and Masashi Furukawa**
*Graduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, Hokkaido 060-0814, Japan
**Department of System and Informatics, Hokkaido Information University, 59-2 Nishi Nopporo, Ebetsu, Hokkaido 069-8585, Japan
In the optimization of seaweed cultivation now being extensively researched, a problem arises in avoiding twisting seaweed. Twisting is a complex phenomenon and difficult to formulate. Producing the optimal water flow, requires calculating the risk of twisting occurring. In this paper, we propose a method to calculate and estimate the twist state based on the results of physical simulation. We devise a seaweed model using multiple rigid bodies that mutually and physically interfere. One result of physical interference, is that the model has two internal state variables – contact time and the number of contact points between individual pieces of seaweed. We introduce an evaluation function to quantify twisting using these state variables in each time step, and propose a way to calculate twist risk based on the von Neumann and Laplacian diffusion kernels, in a dynamic network.
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