蒸发结晶系统传热传质规律的研究

工业蒸发结晶是一个复杂的多相传热与传质过程，其传热传质规律直接决定着晶体的成核和生长，并最终决定产品的粒度分布。根据双步结晶理论，对蒸发结晶的成核和生长动力学进行分析，建立了成核和生长的理论模型。该模型准确描述了蒸发结晶的生长规律，对其中参数的求取和分析可以确定结晶的控制步骤。研究以氯碱工业中烧碱提纯单元NaCl蒸发结晶为例，通过对模型参数的求取，分析NaCl蒸发结晶过程的控制步骤。结果显示，在高温和低流速下，NaCl结晶受扩散过程控制。从而以扩散控制理论为基础，建立了NaCl蒸发结晶的传质传热模型。综合考虑了温度、流速、过饱和度、晶体粒度对结晶粒度分布的影响规律，建立了涵盖各个参数的数学模型。结合粒数衡算，进行了模型计算，得到结晶粒度与操作参数的关系。模型计算结果与实际结果吻合良好，表明该模型可以很好地表示蒸发结晶过程中各操作参数对结晶粒度分布的影响规律。

Study of Heat and Mass Transfer Patterns in Evaporative Crystallization Systems

Evaporative crystallization is a complicated multiphase mass and heat transfer process. Because of the fact that the crystal nucleation and growth is determined by mass and heat transfer, which influences the final crystal size distribution(CSD), the transfer pattern of the evaporation crystallization process was analyzed firstly and a transfer model was built. In the model, according to the two steps crystallization theory, the dynamics mechanism of crystal nucleation and growth was analyzed. On this basis, a model of crystal nucleation and growth has been set up, which can describe accurately the pattern of the crystallization. Through the calculation of some parameters of the model, the control step can be evident. NaCl evaporation crystallization in chlorine alkali industry, for example, is studied and applied for the model. The result showed that under the high temperature and low velocity of flow, NaCl crystallization is controlled by the course of diffusion. According to these, a function taking into account the operation parameters, such as temperature, velocity of flow, supersaturation and size of crystal, which can express accuracy the crystallization process, was built. By the calculation of mass balance, thermal balance and crystal population balance, the influence function of operation parameters on the CSD was established. The result of model calculation accords accurately with the experimentation data, which suggests that the mathematical model can simulate the relationship between the operation and crystal size. The model can be used to predict optimal operation parameters in industry.