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Study on the heat and mass transfer characteristics of spray separation tower at low temperature and normal pressure

机译:低温和常压喷雾分离塔的热传质特性研究

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摘要

A one-dimensional mathematical model for the drying process of calcium chloride solution in a co-current spray separation tower based on the four-stage drying model of single droplet is proposed. A corresponding pilot system is set up and the reliability of the model is validated by a series of experiments. The maximum relative errors of the mathematical model are within 10% and 15% while the average relative errors are 4.0% and 7.0% when predicting the outlet air temperature and humidity, respectively. The effects of inlet parameters on the heat and mass transfer characteristics of the spray separation tower at low temperature and normal pressure are evaluated as well. Simulation results show that air mass flow rate, inlet solution concentration and solution mass flow rate have greater effect on the thermal efficiency than other inlet parameters while the inlet solution concentration plays a pivotal role on the drying strength. The most significant factor on the volumetric heat transfer coefficient is the inlet solution concentration. Besides, the back propagation (BP) neural network model of the spray separation tower is also established on the basis of experimental data, and the comparison between the one-dimensional mathematical model and the BP neural network model is conducted in detail.
机译:提出了一种基于单液滴四阶段干燥模型的杂电喷射塔中氯化钙溶液干燥过程的一维数学模型。设置了相应的导频系统,并且通过一系列实验验证了模型的可靠性。数学模型的最大相对误差分别在预测出口空气温度和湿度时平均相对误差为4.0%和7.0%。进样口参数对低温和正常压力下喷射分离塔的热量和质量传递特性的影响。仿真结果表明,空气质量流速,入口溶液浓度和溶液质量流量对热效率的影响比其他入口参数更大,而入口溶液浓度在干燥强度上发挥着枢转作用。体积传热系数的最显着因素是入口溶液浓度。此外,还在实验数据的基础上建立了喷射分离塔的后传播(BP)神经网络模型,并详细地进行了一维数学模型与BP神经网络模型的比较。

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