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Modeling a weak turbulent flow in a narrow and wavy channel: case of micro-irrigation

Abstract : The baffle-fitted labyrinth channel is commonly used in micro-irrigation systems. The flow in this labyrinth channel has a rather low-Reynolds number. In addition, emitter clogging, which is the major drawback of the micro-irrigation technique, is significantly related to flow characteristics. In order to design an anti-clogging emitter with a good performance, the hydrodynamics must be understood and analyzed. As CFD modeling is nowadays the most efficient approach for improving emitter geometry, this paper presents assessment of several k― \\\backslashvarepsilon\\ \epsilon turbulence models for computation of micro-irrigation emitter hydrodynamics. The objective is to determine the simplest and most efficient model to improve emitter conception, in terms of both discharge/pressure loss and limitation of the areas where low velocity is likely to generate emitter clogging. Low-Reynolds number k― \\\backslashvarepsilon\\ \epsilon models are often assumed to be more suitable for the labyrinth-channel flow since these models have no wall functions, they can take into account low turbulence levels and they account for the effect of damped turbulence. The low-Reynolds number k― \\\backslashvarepsilon\\ \epsilon models used in the present study are compared to high-Reynolds number k― \\\backslashvarepsilon\\ \epsilon models. Very different trends are observed between low-Reynolds number k― \\\backslashvarepsilon\\ \epsilon models. Some models reproduce a turbulent behavior, while others reproduce a laminar behavior. The head loss analysis reveals that, contrary to classical smooth pipe flow, the contribution of turbulent dissipation cannot be neglected since its contribution is larger than wall friction ones. This feature explains why different models can induce quite different flow behavior.
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Jafar Al-Muhammad, Séverine Tomas, Fabien Anselmet. Modeling a weak turbulent flow in a narrow and wavy channel: case of micro-irrigation. Irrigation Science, 2016, 34 (5), pp.1--17. ⟨10.1007/s00271-016-0508-6⟩. ⟨hal-01318216⟩

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