Browsing by Author "Hurter, Ruan Martin"

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    Comparing the group-contribution SAFT-γ Mie equation of state with SAFT-VR Mie
    (Stellenbosch : Stellenbosch University, 2019-12) Hurter, Ruan Martin; Burger, A. J.; Cripwell, Jamie T.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
    ENGLISH ABSTRACT: Group-contribution methods (GCMs) allow engineers to reduce time and other resources spent on conducting experiments for parameterisation of thermodynamic models, because GCMs grant users the ability to build new model fluids using previously parameterised functional groups (FGs). GCMs have widely been applied to semi-empirical cubic equations of state (EoS), activity coefficient models, and simpler variants of statistical associating fluid theory (SAFT) EoS, yet these models remain limited in regard to the types of systems and properties they can describe. The rigorous SAFT-VR Mie EoS has a variable-range Mie-potential reference fluid and a complex dispersion term that enable it to accurately model second-derivative dependent properties, and properties in the near-critical region, but its model parameters are specific to components. The latter trait poses a problem when no pure-component data are available. A group-contribution (GC) variant of SAFT-VR Mie, SAFT-γ Mie, was recently developed in an attempt to combine the convenience of a GC model with the holistic predictions of SAFT-VR Mie. However, this model is relatively new and prior to this investigation, effects of the GC approach in the SAFT-VR Mie framework had not been evaluated in detail. The purpose of this project was to investigate whether assumptions made by the GC approach benefit or deteriorate different applications of this complex SAFT formulation. A general comparison between SAFT-γ Mie and SAFT-VR Mie was done to identify characteristics posing a unique challenge to SAFT-γ Mie by modelling components of increasing complexity: nonpolar, non-associating n-alkanes and 1-alkenes; polar, non-self-associating n-alkyl acetates; and polar, self-associating 1-alcohols. It was found that SAFT-γ Mie is able tomodel alkanes, alkenes, and acetates accurately, but it failed to produce equally accurate results for 1-alcohols, suggesting that the modelling of small polar molecules poses a problem for SAFT-γ Mie. This notion cannot be verified without doing a comparison involving a larger sample of polar, non-self-associating components. Ketones and esters were modelled to evaluate the performance of SAFT-γ Mie for polar components. This part of the study also provided the opportunity to evaluate the performance of the pseudo-association approach used to account for dipolar interactions, as well as the consistency in modelling accuracy between linear isomers. SAFT-VR Mie with the Gross & Vrabec (GV) polar term was used as a benchmark. SAFT-γ Mie cannot distinguish between structural isomers using exactly the same functional groups; therefore, new groups were defined for 2-ketones, 3-ketones, and n-alkyl propanoates. Results mirrored the 1-alcohol results, indicating that the modelling of smaller, more polar molecules poses a challenge for SAFT-γ Mie likely due to the disregarding of proximity effects — a change in functional group characteristics based on its environment, i.e. its surrounding groups or atoms. One likely solution to the problem is to introduce second-order group contributions to act as adjustments to first-order contributions, but this empirical adjustment would reduce the model’s fundamental predictive capability. Besides proximity effects, SAFT-γ Mie also disregards structural considerations such as steric hindrance and the order of intramolecular bond formation; this is also expected to have an impact on SAFT-γ Mie’s performance. It was found that these structural considerations are vital for accurate modelling of branched alkanes, and that significant differences can be observed in properties of branched alkane isomers. While SAFT-VR Mie models all of the considered branched alkanes accurately, SAFT-γ Mie does not. It was found that the homosegmented approach followed in SAFT-γ Mie’s chain term prevents the model from making any distinctions based on a molecule’s layout. A new heterosegmented chain term was proposed: Bonding contributions would be calculated between segments of unique groups instead of between approximated molecular-average segments. Different methods for weighing the contributions of intra- and intergroup bonds were discussed. Although preliminary results suggest that a heterosegmented chain term would allow the model to distinguish between isomers, further investigation is required to evaluate the consequences of the proposed changes.