Masters Degrees (Chemical Engineering)

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    Pre-treatment of sugarcane bagasse for conversion to single cell protein through one-step enzymatic hydrolysis and bioconversion
    (Stellenbosch : Stellenbosch University, 2023-12) Lourens, Veronica; Van Rensburg, Eugene; Görgens, Johann Ferdinand; Stellenbosch University. Faculty of Engineering. Dept. of Chemical Engineering. Process Engineering.
    ENGLISH ABSTRACT: Lignocellulosic biomass (LCB), as an abundant agro-processing residue, holds promise for addressing the challenges of waste and food security through its bioconversion to single-cell protein (SCP), offering an alternative protein source while minimising waste. However, the effective utilisation of LCB for SCP production requires the LCB to undergo pre-treatment to render the LCB fibre amenable to enzymatic digestion. This project addresses the challenges of utilising LCB for SCP production by investigating various pre-treatment strategies for enhancing the enzymatic digestibility of LCB for the purposes of SCP production through high-solids microbial bioconversion of pre-treated LCB using three selected microbes. The study found that disk refining and ball milling increased the digestibility of bagasse by an average of 4.30 g sugar/100 g DM. In contrast, the chemical pre-treatment method of deacetylation was found to significantly increase the digestibility of bagasse from 9.10 g sugar/100 g DM to a maximum of 75.74 g sugar/100 g DM (p < 0.05). Furthermore, the study found that combining deacetylation with disk refining (DDR) and ball-milling (DBM) significantly increased the digestibility of bagasse 8.8- and 5.6-fold, respectively, in comparison to untreated bagasse. Steam explosion, which served as a benchmark for pre-treatment efficiency, resulted in an enzymatic digestibility of 75.17 g sugar/100 g DM, indicating that deacetylation and DDR are suitable alternatives in comparison to this benchmark. The protein yields achieved from the microbial bioconversions of DDR and deacetylated bagasse were 2.47 ± 0.17 and 2.36 ± 0.2 g protein/100 g DM using Pleurotus ostreatus, and 3.29 ± 0.33 and 2.86 ± 0.21 g protein/100 g DM using Fusarium venenatum, respectively, indicating that DDR was the preferred pre-treatment strategy for protein production using fungal microorganisms. Furthermore, the study indicated that DDR had no substantial advantages for protein production from Saccharomyces cerevisiae, achieving protein yields of 1.91 ± 0.07 and 2.12 ± 0.15 g protein/100 g DM from the bioconversion of DDR and deacetylated bagasse, respectively. The optimal process conditions for protein production from these microorganisms were determined using 2 2 -factorial designs with solid and enzyme loadings as the independent variables. It was determined that the effects of the solid and enzyme loadings on the protein yields obtained from P. ostreatus and F. venenatum were more pronounced for DDR bagasse compared to deacetylated bagasse. Additionally, it was noted that changes in the solid loadings had consistently larger effects on the protein yields compared to those of the enzyme loadings, regardless of the microorganism used. Validation experiments of these factorial designs indicated consistent protein yields achieved for the replicate bioconversions using S. cerevisiae and F. venenatum, whereas the protein yields obtained from the replicate bioconversions of P. ostreatus varied by an average of 14.45 and 19.45% for deacetylated and DDR bagasse, respectively. The study thus identified F. venenatum as the most suitable option for protein production from the bioconversion of DDR bagasse using rotating drum bioreactors, achieving a maximum protein yield of 3.68 g protein/100 g DM at a solid and enzyme loading of 30% (w/w) and 16 FPU/g DM, respectively.
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    The application of the lipopeptide Surfactin in heavy metal extraction from mine wastewater
    (2023-12) Schlebusch, Izak David; Tadie, Margreth; Pott, Robert William McClelland; Stellenbosch University. Faculty of Engineering. Dept. of Chemical Engineering. Process Engineering.
    ENGLISH ABSTRACT: Heavy metals (HMs) are a common contaminant present in wastewater generated by mining operations. HMs can be toxic and carcinogenic, and do not naturally degrade. They, therefore, tend to accumulate in environments where they are discharged. Conventional HM separation processes can be effective, however several drawbacks including poor selectivity, high process costs, or generation of secondary pollutants can limit their efficacy in industry. Surfactin is a lipopeptide biosurfactant which shows great promise for application in HM separation processes. Surfactin is capable of coordinating HM cations into stable complexes, and the mechanism of cation coordination is hypothesized to render the complex insoluble in aqueous solutions. These properties, in tandem with the environmentally benign nature of biosurfactants, makes surfactin an attractive alternative to synthetic reagents using in conventional separation processes. The aim of this dissertation is to determine which HM extraction methods can successfully utilise surfactin to extract HMs from aqueous solution and investigate the efficacy of these processes. Based on the hypothesis that surfactin forms insoluble complexes with HM ions, a chelating precipitation process was identified as one potential mode of HM extraction. The ability of surfactin to bind HMs into a hydrophobic complex also suggests that it may be functional as a collector in an ion flotation process. To test the potential of these processes, single ion copper, nickel, and cobalt solutions were used simple model contaminated wastewaters. The ability of surfactin to coordinate and precipitate the metal ions was first confirmed by mixing equimolar concentrations of surfactin with each respective copper, nickel, and cobalt solution. The precipitates that spontaneously formed were dried and analysed by FTIR spectroscopy to determine the binding sites which coordinated the HM ions. It was found that the carboxylate groups and the amide groups present in the hydrophilic cyclic heptapeptide moiety were both capable of coordination, and coordination of the HMs at these sites would decrease aqueous solubility of the complex. The extent of precipitation of copper, nickel, and cobalt by surfactin was then quantified to determine the efficacy of the precipitation process with surfactin as a precipitant. Up to 84% and 88% of nickel and cobalt respectively was extracted by the surfactin precipitation process, and up to 100% of copper was extracted by surfactin precipitation in conjunction with alkaline precipitation. Initial relative surfactin concentration and pH were shown to be key operating parameters that should be controlled in the surfactin-aided precipitation process. The value of the ion flotation process utilising a surfactin collector was investigated by determining how far the ion flotation process could lower the concentration of HMs in the residual solution. The reduction in copper, nickel, and cobalt concentrations in the residual solution was 67%, 82%, and 96% respectively. It was further found that the extent of ion extraction could be improved by optimisation of the flotation pH, air flowrate, and initial concentration of surfactin. Based on these results, it appears that precipitation and ion flotation have the potential to effectively utilise the promising properties of surfactin to treat HM contaminated wastewater.
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    Phase behaviour and physical properties (density and viscosity) of supercritical CO2 + (1-octanol and/or n-alkanes)
    (Stellenbosch : Stellenbosch University, 2023-12) Jayeola, Omofolasewa Hillary; Schwarz, Cara Elsbeth; Motang, Neo; Stellenbosch University. Faculty of Engineering. Dept. of Chemical Engineering. Process Engineering.
    ENGLISH ABSTRACT: The detergent-range alcohols (C8 to C20) obtained downstream in the synthesis gas manufacturing industry often contain substantial amounts of n-alkanes that must be separated. Supercritical fluid technology has proven to be a reliable alternative to traditional separation techniques. Prior research concluded that supercritical CO2 yields better results for separating alkanes from alcohols than traditional, volatile organic solvents. The design of supercritical fractionation columns requires a fundamental understanding of phase equilibria and hydrodynamics. Unlike phase equilibria data – partially available in literature – there is a scarcity of data on the physical properties (density and viscosity) of detergent-range alcohol systems under high-pressure. This study aimed to accurately measure the physical properties (density and viscosity) of binary and ternary mixtures of supercritical CO2 with (1-octanol and/or (n-dodecane or n-tetradecane)) accurately and to obtain a fundamental understanding of the phase behaviour of the relevant mixtures. To that end, improvements were made to an already existing static high-pressure cell equipped with a quartz crystal viscometer and high-pressure bubble- and dew-point data (HPBPDP) were measured visually and nonvisually, as well as density and viscosity data. The systems investigated in this study include binary systems of CO2 with 1-octanol, n-dodecane and n-tetradecane and ternary systems of CO2 + (50 wt.% 1-octanol + 50 wt.% n-dodecane), (50 wt.% 1-octanol + 50 wt.% n-tetradecane) and (50 wt.% n-dodecane + 50 wt.% n-tetradecane). Solute mass fractions and temperatures ranging from 0.015 to 0.65 g/g and 308 to 348 K, respectively, were investigated. The measured HPBPDP and vapour density data were modelled using the RK-ASPEN model, the liquid density data, using the COSTALD model and the viscosity data, using the Chung-Lee-Starling and the TRAPP models; all these models are readily available in Aspen Plus®. The binary HPBPDP data results revealed that the solubility of n-dodecane and n-tetradecane decreases inversely with temperature in conformity to the norm; however, the CO2 + 1-octanol exhibited a temperature inversion at 308.2 K. The increase in carbon-chain length in the n-alkanes decreased its solubility in CO2 ; additional energy (pressure) was required to allow for solvation. Although the carbon chain of 1-octanol is shorter than the relevant n-alkanes, its phase transition pressures are higher due to the tendency of its hydroxyl functional group to form multimer bonds. The ternary systems’ results revealed that introducing n-alkanes to the 1-octanol inhibits the formation of these multimers and, in turn, nulls the effects of temperature inversion. The RK-ASPEN model performed well in predicting the binary and, with the inclusion of the solute-solute binary interaction parameters, the ternary HPBPDP data. In addition, the nonvisual HPBPDP data compared well with the visual measurements, with %𝐴𝐴𝐷𝑃s less than 3 %. Furthermore, this study presented new density and viscosity data for all the relevant systems; however, the chosen models performed poorly in predicting these physical properties. The density and viscosity data for the CO2 + 1-octanol exhibited an inversion, introducing a non-ideal, non-linear relationship between the physical properties and the temperature. The addition of n-alkanes to 1-octanol for the CO2 + 1-octanol + n-alkane systems removed the density and viscosity inversion effects identified in its CO2 + 1-octanol binary subsystem.
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    Phase equilibria measurements and modelling of {water + cyclohexane + ethanol + 1-propanol} system
    (Stellenbosch : Stellenbosch University, 2023-12) Erasmus, Amanda Stephanie; Schwarz, Cara Elsbeth; de Klerk, Danielle Lee; Stellenbosch University. Faculty of Engineering. Dept. of Chemical Engineering. Process Engineering.
    ENGLISH ABSTRACT: The industry has a growing demand for short-chain anhydrous alcohols as fuel additives to increase the octane rating and reduce carbon monoxide emissions. These alcohols are often found in dilute aqueous streams from processes like Fischer-Tropsch reaction water and bio-alcohol production. Due to the azeotropic nature of water and alcohols, enhanced separation techniques like heterogeneous azeotropic distillation (HAD) are necessary. Reliable thermodynamic models and/or experimental data are required to design HAD separation sequences. This work aimed to investigate the liquid-liquid equilibrium (LLE), vapour-liquid equilibrium (VLE), and vapour-liquid-liquid equilibrium (VLLE) of a quaternary system: {water + cyclohexane + ethanol + 1-propanol} at atmospheric pressure. Data were measured at four ethanol:1-propanol ratios. The capability of the Non-Random Two-Liquid (NRTL) and the Universal Functional Activity Coefficient (UNIFAC) thermodynamic models in describing the quaternary LLE phase behaviour was assessed. LLE measurements were conducted using shake flasks in a temperature-controlled (298.2 K to 328.2 K) water bath, while VLE and VLLE measurements were performed with a dynamic Gillespie still equipped with an ultrasonic homogenizer. The data underwent validation and thermodynamic consistency tests, confirming its reliability. The LLE data revealed that the presence of a second alcohol affected the phase behaviour of the respective ternary systems. The total alcohol exhibited evolutionary behaviour between the constituent ternary systems in the size of the heterogeneous region and the distribution between the aqueous and organic phases. Less polar 1-propanol molecules increased the recovery of more polar and smaller ethanol molecules into the organic phase, while the smaller, more polar ethanol molecules increased the recovery of 1-propanol molecules into the aqueous phase. These findings indicate significant interactions between ethanol and 1-propanol in the respective ternary systems. The temperature dependence observed in the quaternary system aligned with expectations from the ternary systems. The mutual solubility between the aqueous and organic phases and the total alcohol recovered to the organic phase increased with an increase in temperature. Both VLE and VLLE data demonstrated the absence of a quaternary azeotrope, with all vapour phases in the VLE data tending toward the {water + cyclohexane + ethanol} ternary heterogeneous azeotrope. The higher the proportion of 1-propanol within the total alcohol in the quaternary system the greater the relative volatility between water and the total alcohol. This increased relative volatility facilitates easier separation in HAD. The VLLE data showed similar alcohol behaviour to the LLE data. The ability of the UNIFAC, UNIQUAC and NRTL thermodynamic models to describe LLE phase behaviour was assessed. Different sets of model parameters for the NRTL model were assessed, which included default Aspen Plus V11 parameters, literature-published parameters, and correlation with ternary LLE data in this work. The NRTL model using BIPs correlated to ternary LLE exhibited the best qualitative and quantitative performance for both {water + cyclohexane + alcohol} ternary systems. These results highlight the need for semi-empirical models like NRTL over the predictive group contribution UNIFAC model. Suggestions for future research include refining the NRTL model parameters and exploring different combinations of short-chain alcohols and entrainers to deepen the understanding of alcohol-alcohol and entrainer-alcohol interactions, ultimately improving the design of HAD separation processes.
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    State estimation and model-based fault detection in a submerged arc furnace
    (Stellenbosch : Stellenbosch University, 2023-12) Kristensen, Isabella; Louw, Tobias Muller; Bradshaw, Steven Martin; Stellenbosch University. Faculty of Engineering. Dept. of Chemical Engineering. Process Engineering.
    ENGLISH ABSTRACT: Model-based state estimators use noisy plant measurements and a process model to calculate accurate and timely estimates of the state variables for process monitoring, model-based fault detection, and model predictive control. The aim of this project was to perform model-based fault detection using state estimation in a complex chemical unit operation and compare the model-based fault detection to a datadriven technique under plant-model mismatch. A system observability analysis and fault detectability analysis was first conducted. The performance of the various nonlinear state estimation techniques, namely the extended Kalman filter (EKF), the unscented Kalman filter (UKF), the particle filter (PF), and the moving horizon estimator (MHE), was then assessed, enabling the selection of appropriate state estimation techniques for model-based fault detection. Model-based fault detection was employed using the residuals generated from the state estimators followed by residual evaluation using PCA. The modelbased fault detection was compared to data-driven fault detection using PCA on the measurements and the effect of plant-model mismatch on the performance of model-based fault detection was investigated. A submerged arc furnace (SAF) for platinum group metal smelting was used as a case study to apply these techniques. The state observability analysis found the SAF system to be locally observable and the measured states to have a higher degree of observability than the unmeasured states. Upon implementation of the state estimation algorithms, the least observable states corresponded to states estimates with the largest estimation error. The fault detectability analysis identified all faults investigated to be structurally detectable. Upon implementation of model-based fault detection, it was concluded that the more structurally detectable a fault is, the better the fault detection performance. The investigation into state estimation in the SAF showed that the EKF, UKF, and PF display good estimation accuracy and fast computation times. The PF showed superior estimation accuracy under low process noise conditions and was selected for model-based fault detection. The EKF, being the most popular algorithm in literature and displaying fairly good estimation accuracy, was selected as the second method. The computational requirements of the MHE proved to be its greatest limitation. Investigations were carried out into reducing the computational load of the method using alternative singular perturbation SAF model with larger integration steps which halved the computational requirements. However, the computation times remained inappropriate for application in model-based fault detection. Lastly, this study found that the model-based fault detection using the PF residuals outperformed the model-based fault detection using the EKF residuals and the data-driven PCA method for detection of faulty conditions within the SAF process. Due to the sensitivity of the PF residuals resulting from the nature of the algorithm, this method showed exceptionally poor robustness to plant-model mismatch. The investigation then demonstrated that residual evaluation of the PF and EKF residuals in a reduceddimensional space using PCA improved the classification performance of the method when plant-model mismatch was present. However, when no modelling error is present, the classification of PF and EKF residuals showed the best performance in the original dimension space.