Measurement, modelling and uncertainty propagation of low-pressure phase equilibrium data for 1-alcohols and n-alkanes

Date
2024-03
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Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: Phase equilibrium data are important to the design of chemical separation processes. Good thermodynamic models are required to determine the phase equilibrium data of the components being separated. The Non-Random Two-Liquid (NRTL) model is a popular activity coefficient model (ACM) used to model a wide variety of systems at low pressures. This is due to the inclusion of a non-randomness parameter and temperature in(dependent) parameters (TDPs). Experimental phase equilibrium data are required to parameterise the NRTL model. These data are associated with uncertainties and as a result the model parameters and process design outputs are associated with uncertainties. Accelerating research is being performed on the propagation of these uncertainties to the thermodynamic model and process design outputs. Out of the various uncertainty propagation (UP) techniques employed, Monte Carlo Simulation (MCS) is the most popular. However, in addition to experimental uncertainties, there are uncertainties inherent in the regression of model parameters. A few uncertain regression elements have been investigated in literature, but to the best of the author’s knowledge none of the UP studies have performed a thorough investigation on the comparison of these two types of uncertainties. The aim of this work is to investigate the effect of model parameterisation and experimental uncertainties in the thermodynamic modelling of low-pressure phase equilibrium data for 1-alcohol + n-alkane systems using the NRTL model. The systems are chosen to present a series of systems showing varying degrees of non-ideal phase behaviour. This work considers binary systems comprising of either ethanol, 1-propanol and 1-butanol, each paired with n-hexane, n-heptane and n-octane. Experimental vapour-liquid equilibrium (VLE) data are measured at 101.3 kPa for four systems: 1-propanol + n-hexane, 1-propanol + n-heptane, 1-butanol + n-hexane and 1-butanol + n-heptane with ethanol + n-heptane serving as the verification system. Experimental uncertainties are rigorously calculated for the systems measured and are used in the experimental UP performed using MCS. This work uses the isobaric PTxy data as the uncertain input variables in the MC approach. This work shows that neglecting correlation between the input variables can lead to the overestimation of the model output uncertainties. While the magnitude of the input uncertainties is important, the inclusion of vapour pressure data uncertainties is less important. For the model parameterisation, the effect of model parameter initial guesses is important. While the choice of objective function is less important in the modelling of the reported VLE data, it is important in the experimental UP. A temperature independent modelling approach can model the less non-ideal systems in this work well. However, for the most non-ideal system, ethanol + n-octane, a more flexible modelling approach is required to obtain a good enough model fit to the VLE data. The experimental UP results are specific to the TDP modelling approach and are system specific. It is thus encouraged that engineers investigate the model parameterisation before performing the experimental UP. The insight provided in this work can be used to extend the investigations to other thermodynamic models and systems.
AFRIKAANSE OPSOMMING: Geen opsomming beskikbaar.
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Thesis (MEng)--Stellenbosch University, 2024.
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