Comparing the effectiveness of various turbulent models in simulating the flow behind a tidal turbine

http://jmes.humg.edu.vn/en/archives?article=965
  • Affiliations:

    Khoa Dầu khí, Trường Đại học Mỏ - Địa chất, Việt Nam

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  • Received: 15th-Dec-2018
  • Revised: 26th-Jan-2019
  • Accepted: 28th-Feb-2019
  • Online: 28th-Feb-2019
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Abstract:

Nowadays, the climate changing intensified due to the over-use of fossil fuels such as coal and petroleum and petroleum-based products has become a major concern which urges human beings to find out alternative resources of energy to adapt for their needs with less impacts on the environment. Among those, exploiting and using the energy extracted from tidal currents are of particular interest. However, to get the best out of tidal energy, it requires several studies to construct and develope appropriate equipments and facilities to optimize the convertion of these sources of energy into other energies. Along with other research methods, numerical simulation proves to be an appropriate option. Furthermore, saving time and computer resources during computational calculations is crucial and deciding, thus, the authors aim to develop a realiable and reasonable model to solve the problem. In this article, we present a numerical method to investigate the flow behind a tidal turbine with a comparision between typical turbulence models such as k-ε Standard, k-ε Realizable, k-Ω SST and Reynolds Stress Model (RSM) and the commercial code ANSYS FLUENT. Results indicate that the k-ε Standard is quite a simple model capable of instroducing satisfying results in the aspect of simulating velocity and turbulence intensity at the downstream of a tidal turbine from a distance greater than 5D (diameter of the turbine). This is especially important to simulating multiple turbines allocated in a region of interest

How to Cite
Nguyen, T.Van 2019. Comparing the effectiveness of various turbulent models in simulating the flow behind a tidal turbine (in Vietnamese). Journal of Mining and Earth Sciences. 60, 1 (Feb, 2019).