关键词:

相稳定性, 相平衡, 全局优化, 粒子群, 约束

Abstract:

The tangent plane distance (TPD) method is the most popular method for phase analysis, which needs to find the global minimum value of TPD function. Because the Gibbs free energy function has multiple minima caused by the strong nonideality and the optimization problem always has a tiresome trivial solution, local optimization algorithm will not converge to global minimum in general, which leads to wrong judgment for phase stability. Linear constraint particle swarm optimization algorithm is a global optimization dealing with constraints of non-negative and affine real space. It generates initial particle population in a feasible space and utilizes the intrinsic linear operation, which makes the whole population always evolves in the feasible space. Considering the characteristics of tangent plane distance method, local acceleration and stopping criteria were devised, which increases the efficiency of algorithm. This method can be applied to any thermodynamic model, including activity coefficient model and EOS model, and this work extends phase analysis from liquid-liquid phase splitting to liquid-liquid-vapor phase splitting.

Key words:

相稳定性, 相平衡, 全局优化, 粒子群, 约束