Research On Thermal Performance Simulation And Optimal Design Of Countercurrent Closed Cooling Tower

The closed cooling tower has many advantages such as high cooling efficiency,energy saving and water saving,compact structure,etc.It is widely used in many fields.Unlike the common open cooling tower,the internal structure of the closed cooling tower adds a set of heat exchange tubes.The heat and mass exchange between the inside and outside of the heat exchange tube ensures that the water quality is not polluted.In addition,the spray water is attached to the outer wall of the pipe to cooperate with the air flow to take away heat,which greatly improves the cooling efficiency.The recycling of the spray water also achieves the purpose of energy saving and water saving.First of all,this paper starts from the heat transfer and mass transfer process of the counter-current closed cooling tower,introduces the differential equations between air,circulating spray water and cooling water,and solves the numerical solution of the theoretical model and the parameters in the distribution inside the heat exchanger.Secondly,the experimental study of the counter-flow closed cooling tower was carried out,the heat transfer and mass transfer coefficients in the theoretical model were revised,and the water spray density,inlet water temperature,and dry bulb temperature under different air-water ratios were analyzed.And the influence of wet bulb temperature on outlet water temperature and coefficient of performance.On this basis,this paper optimizes the structure of the closed cooling tower,taking the experimental tower as the research object,and adopting the theoretical model modified by the experiment to optimize the structure.The results show that under nominal conditions,the heat transfer after structural optimization is increased by7.66%,the heat transfer area is reduced by 16.19%,the coefficient of performance is increased by 9.65%,the pressure drop on the air side is reduced by 9.97%,and the pressure drop on the inside of the tube is reduced by 30.64%.The outlet water temperature is reduced by 1.41%.Finally,this article combines the climate characteristics of Beijing,Changsha,and Guangzhou to establish the operating parameter optimization model of the closed cooling tower,and uses the combination of neural network and genetic algorithm to solve the operating parameter model.The results show that when the temperature difference between the dry and wet bulbs is 2℃,the heat exchange in Guangzhou increased by 1.75%,and the operating energy consumption was reduced by 3.02%;the heat exchange in Changsha increased by 2.69%,and the operating energy consumption was reduced by 1.51%;the heat exchange in Beijing increased by 6.14%,and the operating energy consumption was reduced by 0.76%.From the perspective of the summer operating cycle,the total heat exchange in Beijing has increased by 15.05%,and the total operating energy consumption has been reduced by 11.07%;the total heat exchange in Changsha has increased by 13.04%,and the total operating energy consumption has been reduced by 9.31%;Guangzhou The total heat exchange in the region has increased by 12.59%,and the total operating energy consumption has been reduced by 7.28%.In general,the heat exchange rate has been improved after optimization,while the operating energy consumption has decreased.