Global Gibbs Free Energy Minimization in Reactive Systems via Harmony Search

Abstract

Phase equilibrium calculations in systems subject to chemical reactions play a major role in the design of reactive separation schemes including chemical reaction engineering. Basically, these calculations involve the global minimization of Gibbs free energy constrained by the material balances and chemical equilibrium restrictions. However, Gibbs free energy function is non-convex, highly non-linear with many decision variables, and may have several local minimums including trivial and nonphysical solutions. In these conditions, conventional numerical methods are not suitable for solving reactive phase equilibrium problems. Recently, there has been a significant and increasing interest in the development of global strategies for reliably solving reactive phase equilibrium problems subject. Harmony search (HS) is a global stochastic optimization method, which has been conceptualized using the musical process of searching for a perfect state of harmony. Until now, HS has been successfully applied to solve various engineering and optimization problems. However, there are few studies concerning the application of this optimization method for chemical engineering calculations. To the best of our knowledge, the performance of HS for solving reactive phase equilibrium problems has not yet been reported. Therefore, this paper introduces the application of HS-based algorithms to the constrained global minimization of Gibbs free energy in reactive systems. Specifically, we have studied the performance of three variants of HS in reactive phase equilibrium calculations. Our results are useful to identify the capabilities and relative strengths of HS with respect to other stochastic optimization methods for the simultaneous calculation of physical and chemical equilibrium.

Ash Fusion Properties and Mineral Transformation Behavior of Gasified Semichar at High Temperature under Oxidizing Atmosphere

“…The software FactSage 6.1 was applied to predict the mineral transformation behavior of the semichar ash at high temperature. The package allows for thermodynamic equilibrium calculation based on Gibbs free energy minimization principle constrained by material balances and chemical equilibrium . The ash compositions were simplified and normalized to the SiO 2 –Al 2 O 3 –CaO-Fe 2 O 3 –MgO-TiO 2 –Na 2 O–K 2 O–SO 3 –P 2 O 5 multicomponent system.…”

“…The package allows for thermodynamic equilibrium calculation based on Gibbs free energy minimization principle constrained by material balances and chemical equilibrium. 30 The ash compositions were simplified and normalized to the SiO 1) was calculated by the phase diagram module to predict the liquidus temperature.…”

An Overview of the Application of Harmony Search for Chemical Engineering Optimization

“…Bonilla-Petriciolet et al [223] assessed the performance of GHS, IHS [78], and HS algorithms in the solution of phase equilibrium problems of reactive systems using the Gibbs free energy minimization approach. e constraints of this optimization problem were handled using a formulation that reduces the number of decision variables and numerical effort.…”

On the capabilities and limitations of harmony search for parameter estimation in vapor–liquid equilibrium modeling

“…In the context of applied thermodynamics, there are few studies concerning the application of this stochastic method [20][21][22] and, to the best of our knowledge, the performance of HS in non-linear parameter estimation for VLE modeling has not yet been reported. Thus, this study introduces the first application of HS for solving this challenging global optimization problem.…”

“…To date, HS has been successfully applied to solve global optimization problems in several engineering fields including few applications in chemical engineering [19]. With respect to the phase equilibrium modeling, previous studies suggest that this stochastic method is reliable for solving challenging global optimization problems [20][21][22]. In particular, the goal of this study is to gain insights on the numerical performance of HS for VLE data modeling.…”