Phase behaviour stability analysis using global optimization
Nima Saber, PhD student in Chemical Engineering
Supervisor - Dr. John Shaw
Reliable phase behaviour prediction is of great importance in chemical and petroleum engineering applications. It is difficult to predict correct behaviours, particularly for multiphase cases, or near critical points where local and global Gibbs free energy minima are numerically similar. Commercial simulators as well as research tools are both prone to false convergence. Correct identification of the composition associated with the global minimum in the tangent plane distance function normally leads to successful phase behaviour predictions. However, convergence to correct solutions is not guaranteed. Phase equilibrium solutions should be subjected to a second stability test to validate them. Robust computational methods used for stability analysis are normally associated with significant computational loads. In this contribution, a global optimization computational method called DIRECT is used to solve challenging phase equilibrium examples drawn from the literature. This method converged to the global minimum in the tangent plane distance function for all examples evaluated using one to three orders of magnitude fewer function evaluations compared with other successful methods.
Reliable phase behaviour prediction is of great importance in chemical and petroleum engineering applications. It is difficult to predict correct behaviours, particularly for multiphase cases, or near critical points where local and global Gibbs free energy minima are numerically similar. Commercial simulators as well as research tools are both prone to false convergence. Correct identification of the composition associated with the global minimum in the tangent plane distance function normally leads to successful phase behaviour predictions. However, convergence to correct solutions is not guaranteed. Phase equilibrium solutions should be subjected to a second stability test to validate them. Robust computational methods used for stability analysis are normally associated with significant computational loads. In this contribution, a global optimization computational method called DIRECT is used to solve challenging phase equilibrium examples drawn from the literature. This method converged to the global minimum in the tangent plane distance function for all examples evaluated using one to three orders of magnitude fewer function evaluations compared with other successful methods. 
