Hydropower provides continuous and clean energy for human consumption but also brings a series of environmental concerns to local watersheds. Gas bubble disease or mass mortality in fish can be attributed to total dissolved gas (TDG) supersaturation, which occurs when water is released from dams. It is possible to create temporary refuges for fish suffering from supersaturated total dissolved gas (STDG) by strategically arranging aeration facilities along rivers or reservoirs and using the bubbles generated by aeration to increase the dissipation of STDG. The critical limitation to the widespread application of this approach in engineering is the insufficient understanding of the mass transfer mechanisms of STDG under aerated conditions and the transport characteristics of STDG in water flows. In this work, the mass transfer (MT) mechanisms of STDG under aerated conditions were systematically studied via experiments, image processing, and numerical simulation. An innovative three-dimensional numerical model was established to forecast the MT process of STDG under aerated conditions. The determination of STDG MT in the model incorporated a sophisticated approach that accounted for the dynamic changes in bubble sizes resulting from diverse mechanisms of bubble coalescence and breakup. To validate and calibrate the model, precise aeration experiments were executed at various aeration intensities to gather data on the bubble size distribution, total gas holdup, and STDG dissipation rates. Furthermore, a numerical model was used to quantitatively investigate the impact of the aerator installation depth on STDG dissipation performance. The results revealed that the relationship between the dissipation coefficients of STDG and the aerator installation depth followed a power function. This research can enhance the understanding of the MT characteristics of STDG under aeration conditions while also providing a useful tool for studying the design and optimization of facilities related to STDG engineering treatment via aeration measures.

中文翻译：

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一种模拟曝气条件下过饱和总溶解气体传质过程的数值模型


水力发电为人类提供持续的清洁能源，但也给当地流域带来了一系列环境问题。鱼类的气泡病或大量死亡可归因于总溶解气体 （TDG） 过饱和度，这是在水坝放水时发生的。通过战略性地沿河流或水库布置曝气设施，并利用曝气产生的气泡来增加 STDG 的消散，可以为患有过饱和总溶解气体 （STDG） 的鱼类创造临时避难所。这种方法在工程中广泛应用的关键限制是对曝气条件下 STDG 的传质机制以及 STDG 在水流中的传输特性的理解不足。在这项工作中，通过实验、图像处理和数值模拟系统研究了曝气条件下 STDG 的质量传递 （MT） 机制。建立了创新的三维数值模型来预测曝气条件下 STDG 的 MT 过程。模型中 STDG MT 的测定采用了一种复杂的方法，该方法解释了由气泡聚结和破裂的不同机制导致的气泡大小的动态变化。为了验证和校准模型，在各种曝气强度下进行了精确的曝气实验，以收集有关气泡尺寸分布、总气体滞留率和 STDG 耗散率的数据。此外，采用数值模型定量研究曝气器安装深度对 STDG 耗散性能的影响。 结果表明，STDG 的耗散系数与曝气器安装深度之间的关系服从幂函数。这项研究可以增强对曝气条件下 STDG 的 MT 特性的理解，同时也为研究通过曝气措施进行 STDG 工程处理相关设施的设计和优化提供有用的工具。