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Experimental and Numerical Modelling of Air Entrainment in Eco-hydraulics

Experimental and Numerical Modelling of Air Entrainment in Eco-hydraulics
生态液压中空气夹带的实验和数值模拟
批准号:
RGPIN-2018-03994
负责人:
Balachandar, Ramaswami
金额:
$3.79万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
翻译
在生态水力学中,自由表面流动中的卷吸空气现象是普遍存在的。夹带的空气影响溶解氧水平,在水处理中非常有用,以支持微生物进行水净化,并在河流和溪流中维持健康的水生生物。然而,鱼类通道中过多的空气夹带会导致气泡病,并对鱼类迁徙造成不利影响。在波浪破碎过程中,海洋中也会发生充气。据称,海浪能是最大的可再生能源,到2050年可能贡献全球电力需求的10%。从破波过程中提取能量的方法还有待探索。这些例子突出了研究空气-水流动的实际意义。自曝气是一个不受控制的过程,空气-水流动的动力学是复杂的。研究人员在很大程度上是通过实验研究空气-水流动,并在有限程度上使用数值工具。虽然这些研究揭示了流动的复杂性,但对其内部的湍流机制还没有完全了解。这是由于通常使用的单相流仪表的局限性,需要对其进行改进或改进才能用于空气-水流动。气液两相流动计算研究中的致命弱点是空气卷吸模型。为了取得成功,需要更好地理解管理流程的物理过程。随着仪器的改进和计算设施的增强,现在有可能开始一项研究计划,以开发实用的工具来预测河流中气体的过饱和,防止鱼类死亡和减少城市下水道系统中的气味。*提出了一种新的实验和数值研究计划,以预测/控制自由表面流动中的湍流和空气卷吸。我们将专注于代表人们在实际情况中遇到的大多数复杂性的流场。我们选择了3个流场:水跃、鱼道和破浪。这些流动具有共同的特征:高湍流度,自由表面破碎,空气卷吸,然后是气泡产生的湍流。将使用气泡图像测速仪进行实验研究,并辅之以互补的数值模拟。*主要目标包括:(I)通过使用最先进的仪器进行实验研究,提高我们对充气流动的理解;(Ii)开发适用于空气-水流动的基于计算流体力学的模型。将在流场中分析导致曝气、气泡相互作用和破碎的物理过程。这项研究将有助于改进落水井、鱼道、溢洪道和城市液压系统的设计。新工具将有助于减少未来对昂贵的物理模型测试的依赖。在5年周期内,将培训14名HQP(4名博士、5名硕士、5名理学学士)。
英文摘要
Air entrainment in free-surface flows is ubiquitous in eco-hydraulics. The entrained air influences the dissolved oxygen level and is very useful in water treatment to sustain microorganisms for water purification and in rivers and streams for sustaining a healthy aquatic life. However, excessive air entrainment in fish passages can result in gas-bubble disease and adversely affect fish migration. Aeration also occurs in oceans during the wave breaking process. Wave energy is said to be the largest source of renewable energy and could contribute 10% of the global electricity demand by 2050. Methods to extract the energy from the wave breaking process needs to be explored. These examples highlight the practical relevance of studying air-water flows.*** ***Self-aeration is an uncontrolled process and the dynamics of air-water flows is complex. Researchers have largely studied air-water flows experimentally and to a limited extent using numerical tools. While the studies have brought forth the complexity in the flows, the internal turbulence mechanism is not fully understood. This is due to the limitations in the commonly used single-phase flow instruments, which need to be improved or modified for use in air-water flows. The Achilles heel in the computational study of air-water flows is the air-entrainment model. To achieve success, an improved understanding of the physical processes that govern the flow is required. With the availability of improved instrumentation and enhanced computational facilities, it is now possible to begin a research program to develop practical tools that are required to predict the supersaturation of gases in rivers, to prevent fish-kill and to reduce odour in urban sewer systems.******A novel experimental and numerical research program is proposed to predict/control turbulence and air entrainment in free-surface flows. We will focus on flow fields that represent most of the complexities that one encounters in practical situations. We have chosen 3 flow fields: Hydraulic Jumps, Fish Passages and Breaking Waves. These flows have common features: high turbulence, free-surface breakup, air entrainment followed by bubble generated turbulence. Experimental studies using Bubble Image Velocimetry supported by complementary numerical modeling will be used.******The major goals include: (i) Improve our understanding of aerated flows by conducting experimental studies using state-of-the-art instrumentation and (ii) Develop computational fluid dynamics based models suitable for air-water flows. The physical processes that are responsible for aeration, air bubble interactions and breakup will be analyzed in the flow fields. The study will aid to improve the design of drop shafts, fish passages, spillways and urban hydraulic systems. The new tools will help to reduce future reliance on expensive physical model testing. Over the 5-year cycle, 14 HQP (4 PhD, 5 MSc, 5 BSc) will be trained.
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