Surrogate modeling of phase equilibrium calculations using adaptive sampling

Surrogate Modeling for Liquid–Liquid Equilibria Using a Parameterization of the Binodal Curve

“…Applications for surrogate modeling include, but are not limited to, cases where the original function is expensive to evaluate, e.g., computational fluid dynamics simulations, or where a functional form may not be available, e.g., experimental results. This section gives a summary of recent efforts [4,10] on using data-driven surrogate models for phase equilibrium calculations, particularly for LLE, to improve computational performance while preserving high model accuracy. For the sake of readability, some details of each approach are omitted here and we refer to the original publications for comprehensive descriptions.…”

“…In the model comprising Equations (7)-(10), f i is replaced by a surrogatef i ≈ f i . Kriging interpolation is used for the surrogatesf i in [4,10]. The inputs of the surrogate are N c − 1 mole fractions of the feed mixture and the temperature.…”

“…. , x in N c −1 , T) as in [4]. Since the scalar classifier g in [4] is as difficult to calculate as the equilibrium model, it is approximated by another surrogate modelĝ ≈ g, in this case a support vector machine.…”

“…A larger input dimension increases the size of the surrogate and necessitates more sample data. A difficult input domain may require modeling with an additional surrogate [4]. In addition, output multiplicities have to be treated with special methods [5].…”

“…The additional cost for sample generation is reduced by employing efficient sampling methods. Adaptive sampling approaches that employ exploration and exploitation strategies are preferred over one-shot methods in recent literature (see [3,4] for references).…”