2018
DOI: 10.1021/acs.iecr.8b00148
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Extensive Study of the Capabilities and Limitations of the CPA and sPC-SAFT Equations of State in Modeling a Wide Range of Acetic Acid Properties

Abstract: The accurate description of many thermodynamic properties of acetic acid and its mixtures can be a challenge to model with standard thermodynamic models like local-composition activity coefficient models and cubic equations of state. A possible solution is offered by association equations of state, e.g. those belonging to the Statistical Associating Fluid Theory (SAFT) family. While several researchers have studied the use of SAFT variants to model acetic acid properties (pure compound and mixtures), with few … Show more

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Cited by 14 publications
(15 citation statements)
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“…A general approach to address the degenerate parameter problem is to include one or more properties in addition to saturated liquid density and vapor pressure data for parameter estimation. Thermodynamic properties such as speed of sound, second virial coefficient, enthalpy of vaporization, and heat capacity can be included when parameterizing both nonassociating and associating systems. , Practical challenges with this approach include the availability of experimental data as well as assigning weights to each additional property in the objective function. Strategies are available to guide the optimal selection of weights (Pareto optimal solutions visualized on a Pareto front), but these techniques have not yet been widely applied to parameterizing thermodynamic models. , …”
Section: Applied Thermodynamicsmentioning
confidence: 99%
“…A general approach to address the degenerate parameter problem is to include one or more properties in addition to saturated liquid density and vapor pressure data for parameter estimation. Thermodynamic properties such as speed of sound, second virial coefficient, enthalpy of vaporization, and heat capacity can be included when parameterizing both nonassociating and associating systems. , Practical challenges with this approach include the availability of experimental data as well as assigning weights to each additional property in the objective function. Strategies are available to guide the optimal selection of weights (Pareto optimal solutions visualized on a Pareto front), but these techniques have not yet been widely applied to parameterizing thermodynamic models. , …”
Section: Applied Thermodynamicsmentioning
confidence: 99%
“…Román-Ramírez et al [27] modeled the propanoic acid + water system at temperatures up to 483 K and pressures up to 1.9 MPa with CPA and the CR1 combining rule. More recently, Ribeiro et al [28] evaluated the performance of CPA in modeling saturated pressure, density, speed of sound, second virial coefficient, compressibility factor, enthalpy of vaporization, and isobaric heat capacity of acetic acid. The authors concluded that it is not possible to obtain a single set of pure component parameters that can describe accurately all the properties of pure acetic acid and its phase equilibria.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, the performance of PR with pure component parameters fitted to saturated pressures and volumes (as commonly obtained for modern equations of state) is evaluated to discern whether this approach can improve the predictive capability of PR. The CPA model as proposed by Kontogeorgis et al [21] is employed in this work with both compounds modeled as 2B based on former studies [22,27,28].…”
Section: Introductionmentioning
confidence: 99%
“…Another example is the thermodynamic sound speed, which is essential for the design of venting systems from pressure vessels, and yet is a property difficult to predict accurately with cubic EOSs. Besides, sound speed has been recently used in our group , as input data in the PC-SAFT parametrization of associative compounds, and has led to a large enhancement of the predictive capacity of phase equilibria between ionic liquids and CO 2 , and in the parametrization of acetic acid . It was observed that the PC-SAFT model was unable to correlate the isobaric heat capacity accurately together with the other properties, and authors recommended the use of the parameter set obtained by fitting vapor pressure, density, and speed of sound.…”
Section: Introductionmentioning
confidence: 99%
“…It was observed that the PC-SAFT model was unable to correlate the isobaric heat capacity accurately together with the other properties, and authors recommended the use of the parameter set obtained by fitting vapor pressure, density, and speed of sound. Therefore, among the properties cited hitherto, only calorimetric properties are not used, mainly because of our previous results . Therefore, vapor pressure, density, and speed of sound are the focus of this work, which assesses the performance of the MTC EOS , in their calculation for all linear alkanes in the range C2–C20, after a prescreening of parameter fitting strategies based on n -hexane.…”
Section: Introductionmentioning
confidence: 99%