Accurate Prediction of Preheat Temperature in Solar Flash Desalination Systems Using Kernel Ridge Regression
Accurate Prediction of Preheat Temperature in Solar Flash Desalination Systems Using Kernel Ridge Regression
复制标题
使用核岭回归准确预测太阳能闪蒸海水淡化系统的预热温度
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Mohammad Abutayeh
中科院分区：
文献类型：
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作者：
Maher Maalouf;D. Homouz;Mohammad Abutayeh
摘要热脱盐系统包括从大量海水中分离淡水的相变操作。太阳能海水淡化系统涉及部分蒸发海水，称为闪蒸，使用太阳能热，然后冷凝闪蒸蒸汽以产生淡水。冷凝蒸汽的潜热通常用于预热海水，从而提高脱盐系统的能量效率。评估太阳能海水淡化系统的可行性需要准确确定离开冷凝器进入蒸发器的海水预热温度。由于复杂的相变动力学和冷凝器中溶解在海水中的不可冷凝气体的存在，确定该温度是非常具有挑战性的。预热温度取决于几个因素，如海水流速、系统真空度和闪蒸蒸汽温度。本研究利用核岭回归（KRR）的方法来预测预热温度作为一个函数...
AbstractThermal desalination systems consist of phase-change operations to separate freshwater from bulk seawater. Solar desalination systems involve partial vaporization of seawater, known as flashing, using solar heat then condensation of flashed steam to produce fresh water. The latent heat of the condensing steam is usually utilized to preheat seawater, thus increasing the energy efficiency of the desalination systems. Evaluating the feasibility of a solar desalination system requires accurate determination of seawater preheat temperature exiting the condenser to enter the evaporator. Determining this temperature is very challenging due to the complicated phase-change dynamics and the existence of noncondensable gases in the condenser that were dissolved in seawater. The preheat temperature depends on several factors such as seawater flow rate, system vacuum, and flashed vapor temperature. This study utilizes the kernel ridge regression (KRR) method to predict the preheat temperature as a function of ...