Abstract
AbstractA new reduction method for mixture phase stability testing is proposed, consisting in Newton iterations with a particular set of independent variables and residual functions. The dimension of the problem does not depend on the number of components but on the number of components with nonzero binary interaction parameters in the equation of state. Numerical experiments show an improved convergence behavior, mainly for the domain located outside the stability test limit locus in the pressure–temperature plane, recommending the proposed method for any applications in which the problematic domain is crossed a very large number of times during simulations.
Highlights
Phase stability analysis is very important in process systems engineering and petroleum and gas reservoir, production and transport engineering
The cause of convergence problems in phase stability calculations in the single-phase state is the topology of the tangent plane distance (TPD) surface, as explained in refs. [6,7]
At the stability test limit locus (STLL), the TPD surface exhibits a saddle point, and for conditions outside the STLL in the pressure– temperature plane at a given composition, the iterates have to cross a domain of indefiniteness of the Hessian matrix, starting from one of the two-sided initial guesses [7]
Summary
Phase stability analysis is very important in process systems engineering and petroleum and gas reservoir, production and transport engineering. Phase stability testing assesses the state of a mixture at given specifications and is essential in the initialization of flash calculations, in checking the results of phase split calculations and in phase diagram construction It consists in an unconstrained minimization of the tangent plane distance (TPD) function [1]. At the STLL, the TPD surface exhibits a saddle point, and for conditions outside the STLL in the pressure– temperature plane at a given composition, the iterates have to cross a domain of indefiniteness of the Hessian matrix, starting from one of the two-sided initial guesses [7] This makes stability testing in the vicinity of the STLL really challenging, and any gradient-based algorithm will experience difficulties in this region [5,6,7,8]. The paper is structured as follows: first, a previous reduction method for stability testing is recalled, and the proposed method is introduced and tested for several examples before concluding
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