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Assessment of RANS Models for Milli-Channel Turbulent Flow in Drip Irrigation Emitter

文献类型： 外文期刊

作者： Feng, Qi 1 ; Li, Qingzheng 1 ; Li, Yaojun 1 ; Qiu, Xuefeng 3 ; Wang, Jiandong 3 ; Huang, Xingfa 1 ;

作者机构： 1.China Agr Univ, State Key Lab Efficient Utilizat Agr Water Resourc, Beijing 100083, Peoples R China

2.China Agr Univ, Coll Water Resources & Civil Engn, Beijing 100083, Peoples R China

3.Chinese Acad Agr Sci, Inst Environm & Sustainable Dev Agr, Beijing 100081, Peoples R China

4.Chinese Acad Agr Sci, Western Agr Res Ctr, Changji 831100, Peoples R China

关键词： emitter; drip irrigation; computational fluid dynamics; RANS model; near-wall treatment

期刊名称：AGRONOMY-BASEL （ 影响因子：3.4； 五年影响因子：3.8 ）

ISSN：

年卷期： 2025 年 15 卷 1 期

页码：

收录情况： SCI

摘要： Accurate numerical simulation of turbulent flow within the milli-channels of drip irrigation emitters has long been a significant challenge. This paper presents a comprehensive Reynolds-Averaged Navier-Stokes (RANS) modeling-based analysis of the flow dynamics within the labyrinth milli-channel of a tooth-shaped emitter, with partial experimental validation. The objective was to assess the performances of four RANS turbulence models: RNG k-epsilon (RNG), Realizable k-epsilon (RKE), SST k-omega (SST), and baseline k-omega (BSL), alongside three near-wall treatments: scalable wall function (SWF), enhanced wall treatment (EWT), and y+-insensitive wall treatment (YIWT) for emitter flow analysis. The results showed that the RNG and RKE, coupled with EWT, are preferred options for predicting the flow rate-pressure loss relationship of the emitter, with relative errors of 2.08% and 1.02% in the discharge exponent and 5.66% and 7.58% in the flow rate coefficient, respectively. Although both RNG and RKE using SWF are viable for hydraulic performance prediction under high-flow rate conditions, the deviation of predicted flow rate reaches up to 25.46% under low-flow rate conditions. The SST and BSL models, which employ IYPT, captured induced vortices at channel corners; however, they underestimated emitter flow rates. Furthermore, computations using SWF failed to capture the asymptotic characteristics of flow parameters in the near-wall region, resulting in an overestimation of turbulent kinetic energy and turbulence intensity. Additionally, the magnitude of wall shear stress in the channel corners fell below the threshold required for self-cleaning, underscoring the necessity for optimizing channel structures to enhance the anti-clogging performance of the emitter.

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