Hydrodynamic analysis for the Undaria pinnatifida (Wakame)

Abstract

With the depletion of traditional energy sources, development of renewable energy is turning into a necessity. Besides wind energy and solar energy, another alternative renewable energy is biomass. Seaweed is seen as one of the most promising marine plants that can produce the biomass needed to partly satisfy of our future energy requirements. Seaweed cultivation is deemed as sustainable and environmentally friendly because it does not need fresh water, fertilizer and agricultural land. Furthermore, it converts greenhouse gases into oxygen and uptakes inorganic nitrogen and phosphorus from the seawater to avoid eutrophication.

Stichting Noordzeeboerderij and MARIN (Maritime Research Institute The Netherlands) are working together to develop floating seaweed cultivation platforms for offshore. For this project, the loadings on the cultivation platform is interested. To accomplish this, this thesis will study the hydrodynamic characteristics of the seaweed, as they are the main contributors to the loading on the cultivation platform. Then the loading on the single blade of the seaweed is required to be predicted. In this research, two most common and highly economic value seaweed species are chosen, Undaria pinnatifida (Wakame) and Laminaria saccharina.

This thesis describes an experiment that was conducted in the TU Delft Environmental Fluid and Mechanics laboratory. In this experiment, a current flume was used to investigate the hydrodynamic coefficients for the chosen types of seaweed. Before this, the physical and mechanical features such as density, geometrical and the flexural rigidity for the algae of interest were tested in MARIN workshop. Based on these feature parameters, an accurately designed surrogate (has the same or similar magnitude of parameters with the prototype) was constructed in order to imitate fresh algae for the flume experiments. During the experiment, the behavior of L.saccharina was found to be characterised by complex three-dimensional movement that is heavily influenced by the chaos pattern of the surrounding flow. Because the motions of Wakame are more
planar so that easier to be simulated, Wakame was chosen to be the species to be studied in detail.

Two numerical models, were written in MATLAB language, were computed for two movement phases in order to predict the loading and movement of an individual Wakame plant in a current. The first model is suitable for low velocities (0 to 0.57m/s) and simulates a swinging motion of the seaweed in the current. During this process, hydrodynamic force, hydrostatic force, friction and gravity are taken into account. The steady-state position that is predicted by the model in steady fluid is well matched with the results that were measured in the experiment in the same situation.

The second model is used for large velocities (0.57m/s to 2.5m/s) when the structure is designed to have a horizontal position as its initial position and equilibrium position. A stable motion was simulated when the velocity varies from 0.57m/s to 0.81m/s. Furthermore, when the velocity exceeds 0.81m/s, the structure experiences a flutter instability and larger loading. In this procedure, a nonconservative inviscid force that is applied on the structure tip and its influence is discussed in detail. Based on the second model, the ultimate of the total moment of the individual Undaria pinnatifida thallus is predicted for five typical growing phases (with different length, density and stiffness) for accomplish the purpose of this thesis.

These two numerical models could be further used on other engineering time-domain simulation software as a package to simulate and predict the movement of Undaria pinnatifida (Wakame) and the loads that work on it. It could be also used for other seaweed species with similar morphology by inputting stiffness, size parameters and the number of sections that separate the whole seaweed blade in the model. In this way, the motions and loads of other, similar species could also be predicted by the models.