Multi‐criteria optimization for parameterization of SAFT‐type equations of state for water

Abstract

Finding appropriate parameter sets for a given equation of state (EoS) to describe different properties of a certain substance is an optimization problem with conflicting objectives. Such problem is commonly addressed by single-criteria optimization in which the different objectives are lumped into a single goal function. We show how multi-criteria optimization (MCO) can be beneficially used for parameterizing equations of state. The Pareto set, which comprises a set of optimal solutions of the MCO problem, is determined. As an example, the perturbed-chain statistical associating fluid theory (PC-SAFT) EoS is used and applied to the description of the thermodynamic properties of water, focusing on saturated liquid density and vapor pressure. Different options to describe the molecular nature of water by the PC-SAFT EoS are studied and for all variants, the Pareto sets are determined, enabling a comprehensive assessment. When compared to literature models, Pareto optimization yields improved models

Optimal Design of Laboratory and Pilot‐Plant Experiments Using Multiobjective Optimization

“…An adaptive method , based on a hybrid algorithm is employed here to calculate a minimal number of Pareto‐optimal solutions to linearly approximate the complete Pareto frontier within a predefined tolerance. The methodology has previously been employed within product and process design and optimization , , , and parameter estimation of molecular simulation and thermodynamic models .…”

Digitalization in Thermodynamics

“…A number of recent studies demonstrate the applicability and advantages of MCO for the development of thermodynamic models. They cover the most important types of thermodynamic models, namely equations of state , models of the excess Gibbs energy of mixtures ( G E ‐models) , and molecular models (force fields) . The knowledge of the Pareto front gives a comprehensive overview of what can be achieved with a given model regarding the description of the considered data sets.…”

“…The optimization problem studied in Fig. is the development of PC(P)‐SAFT models for water, details are reported in . The conflicting objectives are the average deviation between model and experiments in the vapor pressure and the saturated liquid density, respectively.…”

Optimal Design of Laboratory and Pilot-plant Experiments using Multiobjective Optimization

“…An adaptive method [25], [28] based on a hybrid algorithm is employed here to calculate a minimal number of Pareto-optimal solutions to linearly approximate the complete Pareto frontier within a predefined tolerance. The methodology has previously been employed within product and process design and optimization [25], [26], [29]- [31], and parameter estimation of molecular simulation [32]- [34] and thermodynamic models [35].…”