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常压下丙醛-水-甘油体系汽液平衡测定与关联

Measurement and correlation of vapor-liquid equilibria for propionaldehyde-water-glycerin system at atmospheric pressure
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摘要 采用单循环汽液平衡釜测定了常压条件下丙醛-水的二元以及丙醛-水-甘油三元汽液平衡数据。运用MATLAB中求解非线性最小二乘法问题的函数Lsqnonli,结合丙醛-水的二元汽液平衡实验据,迭代出了Margules、Vanlaar、Wilson和UNIQAC四个方程的二元模型参数。通过计算值和实验值的比较,Wilson方程的相对误差均小于5%,故选择Wilson方程为本体系的适合模型。将测定的丙醛-水-甘油三元汽液平衡数据与模型参数带入Wilson方程求得的三元汽液平衡数据相比较,相对误差均小于5%,由此验证了本文Wilson模型参数的可靠性。本文的测定结果和计算结果为丙醛-水-甘油体系的萃取精馏模拟选择了合适的模型,关联得到的Wilson模型参数,为萃取精馏过程的模拟计算打下基础,同时也为丙醛和水混合液的有效分离提供了一定基础数据。 The vapor-liquid equilibrium data on the binary mixtures of propionaldehyde - water system and the mixtures of propional- dehyde - water - glycerol system were determined by single stage vapor-liquid equilibrium cauldron at atmospheric pressure. Two binary model parameters of the equation of Margules, Vanlaar, Wilson, UNIQAC were obtained by the function of Lsqnonlin which solves nonlinear least squares problem in MATLAB as well as the vapor-liquid equilibrium data on the binary mixtures of propionaldehyde - water system. By comparing the calculated and experimental values, the relative error of the Wilson equation was less than 5% and hence the Wilson equation was chosen for the model-based system. Compared the vapor-liquid equilibrium data of propionaldehyde - wa- ter-glycerol system with the vapor-liquid equilibrium data obtained by importing the Wilson equation, the relative error is less than 5%. Consequently, the reliability of the model parameters of the Wilson equation in this article is verified. The outcome of the calculated and experiment provided appropriate model for the extractive distillation simulation. Besides, Wilson model parameters obtained by associa- tion laid the foundation for the simulation of the extractive distillation process and simultaneously provided some basic data for the ef- fective separation of the mixture of water and propionaldehyde.
作者 宋浩 顾正桂
出处 《计算机与应用化学》 CAS 2016年第8期929-932,共4页 Computers and Applied Chemistry
关键词 丙醛 汽液平衡 关联计算 propionaldehyde vapor-liquid equilibrium correlation computing
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