NUMERICAL AND COMPUTATIONAL ASPECTS OF COSMO-BASED ACTIVITY COEFFICIENT MODELS

In the present work, some numerical and computational aspects of COSMO-based activity coefficient models were explored. The residual contribution in such models rely on the so called self-consistency equation. This equation does not have a closed-form solution and is usually solved by the successive substitution method. The performance of a classical Newton-Raphson method was tested in solving the self-consistency equation. The results obtained by the Newton implementation and by successive substitution agreed within the convergence tolerance. The CPU times for solving the model using both methods also were compared. Contradicting the usual experience, it was observed that the Newton method becomes slower than successive substitution when the number of components (or number of COSMO segments) in the mixture increases. An analysis of the number of floating point operations required showed the same. Newton's method will be faster only for small systems.