ThermoData Engine (TDE): Software Implementation of the Dynamic Data Evaluation Concept. 8. Properties of Material Streams and Solvent Design

Abstract

ThermoData Engine (TDE) is the first full-scale software implementation of the dynamic data evaluation concept, as reported in this journal. The present paper describes the first application of this concept to the evaluation of thermophysical properties for material streams involving any number of chemical components with assessment of uncertainties. The method involves construction of Redlich–Kister type equations for individual properties (excess volume, thermal conductivity, viscosity, surface tension, and excess enthalpy) and activity-coefficient models for phase equilibrium properties (vapor–liquid equilibrium). Multicomponent models are based on those for the pure-components and all binary subsystems evaluated on demand through the TDE software algorithms. Models are described in detail, and extensions to the class structure of the program are provided. Novel program features, such as ready identification of key measurements for subsystems that can reduce the combined uncertainty for a particular stream property, are described. In addition, new product-design features are described for selection of solvents for optimized crystal dissolution, separation of binary crystal mixtures, and solute extraction from a single-component solvent. Planned future developments are summarized.

Critical Evaluation of Thermodynamic Properties for Halobenzoic Acids Through Consistency Analyses for Results from Experiment and Computational Chemistry

“…In future work, this type of analysis will be extended to other compound types, with the goal of developing an algorithm that can be applied across numerous compounds to highlight inconsistencies in evaluated thermodynamic properties with limited user (human) intervention, as per the goals set for the NIST ThermoData Engine. [1][2][3][4][5][6][7][8] 12. Appendix x conformer is the computed mole fraction of the most stable conformer for 2-fluorobenzoic and 2-chlorobenzoic acids.…”

“…Values shown in normal type (2-, 3-, 4-fluorobenzoic acids, 2-, 3-, 4-chlorobenzoic acids, 4-bromobenzoic acid, and 2-iodobenzoic acid) were derived entirely with the experimental thermodynamic properties, critically evaluated as described in the text, and validated with results of computational chemistry through the homodesmic reaction given in Eq. (8).…”

“…The critical evaluation of thermodynamic properties involves a demonstration of consistency among properties for a given compound based on enforced thermodynamic identities and well-established correlations (cf. the series of articles describing the National Institute of Standards and Technology (NIST) ThermoData Engine [1][2][3][4][5][6][7][8] ). In addition, evaluation involves the assessment of trends in property values within families of related compounds, such as trends in properties for homologous series, such as normal alkanes, which have remained a topic of interest to the research community for decades (cf.…”

Calculation of critical points from Helmholtz-energy-explicit mixture models

“…For higher alkanes (for instance hexadecane), non-Type I phase behavior is seen for mixtures with carbon dioxide. [10] (solid: multi-fluid model, dashes: SRK as one-fluid model with k ij = 0, markers: experimental measurements from the TDE database [54,55,56]), with parameters taken from Table 2 Figure 8 shows the critical lines calculated with the multi-fluid model and the one-fluid SRK model with k ij = 0. For the higher alkanes, the predictions of the critical temperatures are excellent and the SRK model captures the shape of the critical line with high accuracy.…”

Data quality and assessment, validation methods and error propagation through the simulation software: Report from the Round-Table Discussion at the 10th World Congress of Chemical Engineering in Barcelona (October 1–5, 2017)

“…The uncertainty concept has not received the deserved attention of process engineers in the past. Several research studies evaluating the impact of uncertainties in property models on process design and plant operability were performed in the past with different outcomes [4,5] [6,7] and references 43-48 in [7]. In some cases, rough approximations of physical properties are good enough for process design, but sometimes extreme sensitivity of design to physical properties is observed.…”