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Coupling model and solving approach for performance evaluation of natural draft counter-flow wet cooling towers

机译:自然通风逆流湿式冷却塔性能评估的耦合模型和求解方法

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When searching for the optimum condenser cooling water flow in a thermal power plant with natural draft cooling towers, it is essential to evaluate the outlet water temperature of cooling towers when the cooling water flow and inlet water temperature change. However, the air outlet temperature and tower draft or inlet air velocity are strongly coupled for natural draft cooling towers. Traditional methods, such as trial and error method, graphic method and iterative methods are not simple and efficient enough to be used for plant practice. In this paper, we combine Merkel equation with draft equation, and develop the coupled description for performance evaluation of natural draft cooling towers. This model contains two inputs: the cooling water flow, the inlet cooling water temperature and two outputs: the outlet water temperature, the inlet air velocity, equivalent to tower draft. In this model, we furthermore put forward a soft-sensing algorithm to calculate the total drag coefficient instead of empirical correlations. Finally, we design an iterative approach to solve this coupling model, and illustrate three cases to prove that the coupling model and solving approach proposed in our paper are effective for cooling tower performance evaluation.
机译:在具有自然通风冷却塔的热电厂中寻找最佳冷凝器冷却水流量时,必须在冷却水流量和进水温度发生变化时评估冷却塔的出水温度。但是,自然通风的冷却塔的出风口温度和塔架吃水或进风速度密切相关。传统方法(例如反复试验法,图形法和迭代法)不够简单有效,无法用于工厂实践。在本文中,我们将默克尔方程与吃水方程结合起来,并开发了用于自然吃水冷却塔性能评估的耦合描述。该模型包含两个输入:冷却水流量,入口冷却水温度和两个输出:出口水温度,入口空气速度,相当于塔的吃水深度。在该模型中,我们还提出了一种软测量算法来计算总阻力系数,而不是经验相关性。最后,我们设计了一种迭代方法来求解该耦合模型,并举例说明了三种情况,以证明本文提出的耦合模型和求解方法对于冷却塔性能评估是有效的。

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