Suphat Watanasiri

Development of a new cubic equation of state for phase equilibrium calculations

Abstract A new cubic equation of state has been developed to allow a precise representation of pure component and mixture properties of interest in Process Engineering and has been implemented in the Process Simulator Aspen Plus. A major feature of this equation is that all parameters that are not available can be automatically estimated from pure component or group contribution data banks.

Representation of liquid-liquid equilibrium of mixed-solvent electrolyte systems using the extended electrolyte NRTL model

Abstract The three-contribution electrolyte NRTL model [1] with an additional term of Bronsted-Guggenheim type is applied to represent the liquid-liquid equilibrium (LLE) in mixed-solvent electrolyte systems. The Bronsted-Guggenheim term compensates for the inadequacies of the Debye-Huckel and Born equations when they are extended to mixed-solvent electrolyte systems. Attention is given to the definition of reference and standard states. The importance of the electrolyte solution chemistry is emphasized. The extended electrolyte NRTL model is compared with the Zerres-Prausnitz model [2] on correlation of LLE data for four ternary aqueous-organic solvent electrolyte systems.

Representation of nonideality in concentrated electrolyte solutions using the Electrolyte NRTL model with concentration-dependent parameters

Abstract The Electrolyte NRTL model proposed by Chen et al. [C.-C. Chen, H.I. Britt, J.F. Boston, L.B. Evans, AIChE Journal 28 (1982) 588–596.] and Chen and Evans [C.-C. Chen, L.B. Evans, AIChE Journal 32 (1986) 444–454.] has been modified to include concentration dependence of interaction parameters in order to enhance the capability of the model in representing the nonideality of concentrated electrolyte solutions. The concentration-dependent interaction parameter is based on the concept that the multi-body effect should be considered in determining the local composition when the electrolyte concentration is high. In this work, a linear concentration dependence is assumed and the activity-coefficient expressions for cations, anions and molecular species are derived from the excess Gibbs energy expression through the thermodynamic relationship. Therefore, the activity-coefficient expressions are consistent and satisfy the Gibbs–Duhem equation. The experimental mean-ionic-activity-coefficients of highly soluble aqueous electrolyte systems have been used to regress the concentration-dependent parameters. The calculated values and experimental data are in excellent agreement. The deviations are usually within experimental uncertainty and significantly smaller than those using the original model. The modified model is completely compatible with the original model because it reduces to the original model when the concentration-dependent term is zero.

Development of on-demand critically evaluated thermophysical properties data in process simulation*

Accurate thermophysical properties are essential to the development of high-quality process simulation models of chemical processes. Therefore, process-modeling software (simulator) must provide accurate, reliable, and easily accessible property data and models to enable efficient and robust process design. Property data and parameters for components of interest are generally available in the databases of the simulator. For components that are not in the databases, their property data must be supplied by the user. The number of components available in a typical simulator is about 1700. The number and types of components available in the simulator limit the scope and accuracy of process models that can be developed. In this paper, we review past practice in obtaining the necessary property data required in developing a process model and describe a new methodology that can be used to overcome the shortcomings of the current method. The new method is based on the dynamic data evaluation concept that combines the experimental data obtained from a comprehensive electronic database with structure-based property estimation system and data analysis and regression programs to generate critically evaluated property data. The concept and necessary software have been implemented in a process simulator, resulting in a new workflow that enables high-fidelity process models to be developed more easily and efficiently.

Modeling metallurgical processes using a chemical-engineering simulator

Abstract This paper describes the extensions of a Chemical-Engineering simulator to model extractive metallurgical processes. The extensions revealed many new challenges such as the needs for thermochemical properties of inorganic and organic species and the ability to model highly nonideal liquid and solid solutions over very wide temperature ranges. This paper describes the implementation of a new inorganic physical property data base and the modification of an existing Gibbs- free-energy minimization model used in modeling phase and chemical equilibria. Traditional Chemical Engineering activity coefficient models (Wilson and NRTL) are used to describe behavior of metallurgical solutions. Finally, an example application to a pyrometallurgical process is given.