Pico scale undershot waterwheel for ultra-low-head: Analytical, experimental and CFD method

IF 4.2 Q2 ENERGY & FUELS
Dendy Adanta , Dewi Puspita Sari , Imam Syofii , Kaprawi Sahim , Erie Martides , Yadi Radiansah , Dalmasius Ganjar Subagio , Yusuf Suryo Utomo , Oo Abdul Rosyid , Ahmad Fudholi
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引用次数: 0

Abstract

In the 19th and early 20th century, the utilization and development of the undershot waterwheel (USWW) was massif. USWW represents a global warming and crisis electricity solution issue for the world. However, the best condition and design of USWW are still incomplete; previous research is based on assumptions. Hence, this work aims to theoretically estimate the power loss (head loss, leakage loss, and friction loss) occurring in USWW to predict the relation between the blade number and optimum operation. The investigation employs analytical and CFD methods, then validated with experimental data. Then, based on root mean square error (RMSE) analysis, the average RMSE of analytical results to experimental data was 9.02%, and of CFD data was 9.07%. Then, depict the blade number and optimum operation relation to USWW performance expressing using multiple quadratic polynomial regression. The empirical law identifies the 16-blades, and the working operation of 0.5 is USWW maximum performance in ultra-low-head.

Abstract Image

用于超低水头的皮米级下射水车:分析、实验和 CFD 方法
在 19 世纪和 20 世纪初,大量利用和发展了底座水车(USWW)。水车是解决全球变暖和电力危机的重要手段。然而,USWW 的最佳状态和设计仍不完整,以往的研究都是基于假设。因此,本研究旨在从理论上估算在 USWW 中发生的功率损失(水头损失、泄漏损失和摩擦损失),以预测叶片数量与最佳运行之间的关系。研究采用了分析和 CFD 方法,然后用实验数据进行验证。根据均方根误差(RMSE)分析,分析结果与实验数据的平均均方根误差为 9.02%,与 CFD 数据的平均均方根误差为 9.07%。然后,使用多元二次多项式回归描述了叶片数量和最佳运行与 USWW 性能的关系。经验法则确定了 16 片叶片和 0.5 的工作运行是 USWW 在超低水头下的最大性能。
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来源期刊
Renewable Energy Focus
Renewable Energy Focus Renewable Energy, Sustainability and the Environment
CiteScore
7.10
自引率
8.30%
发文量
0
审稿时长
48 days
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