Department of Chemical Engineering

Permanent URI for this community

https://scholar.sun.ac.za/handle/10019.1/321

Department Process Engineering now has a new name, and will be known from March 2023, as Department of Chemical Engineering.

Browse

Now showing 1 - 20 of 615

Acoustic monitoring of DC placma arcs
(Stellenbosch : Stellenbosch University, 2008-03) Burchell, John James; Eksteen, J. J.; Niesler, T. R.; Aldrich, C.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: The arc, generated between the cathode and slag in a dc electric arc furnace (EAF), constitutes the principal source of thermal energy in the furnace. Steady state melting conditions rely on efficient control of the arc's power. This is achieved by keeping the arc's length constant, which is currently not directly measured in the industry, but relies on an external voltage measurement. This voltage measurement is often subject to inaccuracies since it may be influenced by voltage fluctuations that are not necessarily related to the arc itself, such as the variable impedance of the molten bath and the degradation of the graphite electrode. This study investigated whether or not it is possible to develop a sensor for the detection of arc length from the sound that is generated by the arc during operation. Acoustic signals were recorded at different arc lengths using a 60 kW dc electric arc furnace and 600 g of mild steel as melt. Using a filterbank kernel (FB) based Fisher discriminant analysis (KFD) method, nonlinear features were extracted from these signals. The features were then used to train and test a k nearest neighbour (kNN) classifier. Two methods were used to evaluate the performance of the kNN classifier. In the first, both test and train features were extracted from acoustic signals recorded during the same experimental run and used a ten fold bootstrap method for integrity. The second method tested the generalized performance of the classifier. This involved training the kNN classifier with features extracted from the acoustic recordings made during a single or multiple experimental runs and then testing it with features drawn from the remaining experimental runs. The results from this study shows that there exists a relationship between arc length and arc acoustic which can be exploited to develop a sensor for the detection of arc length from arc acoustics in the de EAF. Indications are that the performance of such a sensor would rely strongly on how statistically representative the acoustic data are, used to develop the sensor, to the acoustics generated by industrial dc EAFs during operation.
Adaptive process monitoring using principal component analysis and Gaussian Mixture Models
(Stellenbosch : Stellenbosch University, 2019-04) Addo, Prince; Auret, Lidia; Kroon, R. S. (Steve); Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: Principal component analysis (PCA) is a well-known technique used in combination with monitoring statistics for fault detection. Moving window PCA and recursive PCA are adaptive extensions of PCA that operate by periodically updating the monitoring model to incorporate new observations. This allows the monitoring model to cope with process behaviours that change slowly over time such as equipment aging, catalyst deactivation, and reaction kinetics drift and thereby improving monitoring performance. Recent demands and advancements in process industries, however, may result in multimodal operations, where distinct clusters are present in measurement data. The performance of the aforementioned PCA-based monitoring techniques is hindered due to the violation of the implicit assumption that all the observed process data belong to the same Gaussian distribution. To improve monitoring performance, multimodal techniques are required. The Gaussian mixture model (GMM) is a probabilistic model that can account for the observed modes in the process data and therefore be used in the monitoring of multimode processes. However, multimodal processes also exhibit behaviours that change slowly over time, which is challenging. This work develops a monitoring approach that extends adaptive PCA techniques to GMM, which effectively addresses the aforementioned challenge. This is done by continuously refreshing the model parameters and monitoring statistics for the PCA and GMM. Other key areas that the work focuses on are in improving the specifications for adaptive PCA protocol (taking into consideration the various model update methods) and Gaussian mixture model methods (taking into consideration the monitoring model types and data types). Also, the performance of unimodal and multimodal process monitoring approaches was assessed. The performance of the developed approach and the improved implementations of the pre-existing methods were assessed using various case studies including unimodal and multimodal processes both with and without drift as well as various fault types. The Tennessee Eastman process and the non-isothermal continuously stirred tank reactor process are the two main simulators considered. Results for the considered cases show improved performance for the developed approach (adaptive PCA-based GMM) as compared to PCA, adaptive PCA, and traditional GMM, in fault detection. The GMM, as expected, performed better for multimodal cases than the PCA approaches. Also, the adaptive PCA approach performed better than PCA when there is process drift.
ADM1 Parameter Calibration Method based on partial least squares regression framework for industrial-scale anaerobic digestion modelling
(Stellenbosch : Stellenbosch University, 2019-12) Xu, Zhehua; Burger, A. J.; Louw, Tobias M.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: Anaerobic Digestion Model 1 (ADM1) is the mainstay modelling tool for Anaerobic Digestion research and development. Its growing popularity is attributed to its sophisticated yet expandable structure. Not only does ADM1 encompass a broad range of biochemical, physicochemical and inhibition reactions, it provides the modeller a structured framework to add or remove reactions per application requirements. Two major challenges that ADM1 faces are the difficulty in translating common quality indicators into ADM1’s 26 state variables, and the complication with calibrating a large number of model parameters – 58 by default. There is currently no consensus with regards to the parameter calibration approach. Researchers utilise various sensitivity analysis techniques to identify sensitive parameters, but the selection of parameters to be calibrated relies largely on the modeller’s discretion. In some cases, decisions are simply made based on prior or expert knowledge. Since the installation, operation and maintenance of advanced instrumentation are often expensive, most industrial digesters are inadequately monitored and thus intentionally over-designed. A model that can be used on-site with acceptable accuracy could serve as a soft sensor to forecast inhibition risks and automate preventive actions. Therefore, this study aimed to develop a standardised way to calibrate parameters when optimising ADM1 models built for industrial-scale digesters. The proposed method, Partial Least Squares (PLS) Method, consists of four steps. In Step 1, a series of Monte Carlo simulations is carried out. For each Monte Carlo run, ADM1 is executed with all its model parameters sampled from independent probability distributions. These probability distributions were obtained by conducting a literature survey across 62 publications and all published parameters compiled into a domain which represents the uncertainty range of each parameter. In Step 2, a multivariate regression technique called PLS Regression (PLSR) is applied to the Monte Carlo results. The motives for employing PLSR are to reduce parameter dimensionality and to identify the underlying relationships between the model parameters and the model outputs. In Step 3, these relationships, which are mathematically described as PLS weights, loadings and latent variables, are utilised to guide parameter calibration. Lastly, the calibrated parameter set is validated against unseen data. This method successfully improved, in the absence of any modeller’s bias, the overall accuracy of a model based on data from an industrial-scale digester. The model is tasked to fit six typical plant measurements: Volatile Fatty Acids (VFA), ammonia, Volatile Suspended Solids (VSS), pH, methane gas flow & carbon dioxide gas flow. A configuration consisting of at least 500 Monte Carlo runs and two latent variables is required to produce a reasonably accurate fit. Although the use of more latent variables could enable PLSR to capture interactions of lesser weighted output variables, the model becomes increasingly prone to overfitting. However, it is envisaged that more latent variables would be necessary if more outputs are modelled. It is recommended to start the PLSR algorithm with one latent variable and only introduce more if necessary. Different parameter calibration methods produce different model outcomes. The PLS Method was benchmarked against two other methods, namely the Group Method and the “Brute Force” Method. In the former method, kinetic parameters were grouped into the three groups of sensitivities (High, Medium, Low) as suggested in the ADM1 Scientific and Technical Report. The three groups are then calibrated sequentially in order of decreasing sensitivity. The “Brute Force” Method involved calibrating all 58 parameters without any particular sequence, prioritisation or expert inputs. Lower and upper limits are, however, set as per the minimum and maximum values identified from the literature. Besides proving to be a suitable method for industrial-scale digester modelling, the PLS Method was found to exhibit several unique traits: • It is the only method that did not show signs of overfitting. • It is the only method that concluded the model optimisation with all calibrated parameter values within the surveyed minimum and maximum range. • It converges on the objective function 30-60% faster than the Group Method and 14 times quicker than the “Brute Force” Method The success is attributed to the fundamentals of PLS regression. Unlike other regression methods where parameters are adjusted independently, PLS enables parameters to be manipulated collectively in a manner that ensures maximum impact on the outputs while considering collinearities among the parameters. This guided approach effectively mitigates the so-called “curse of dimensionality” and, potentially, overfitting and thereby speeds up the calibration process.
The adsorption and elution of Pt-, Pd- and Au cyanide using activated carbon
(Stellenbosch : Stellenbosch University, 2015-03) Snyders, Cornelius Albert; Bradshaw, S. M.; Akdogan, G.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: In order to exploit lower grade and complex platinum group metal resources, cheaper and more efficient alternatives to the conventional mill-float-smelt-refine route are being sought. Leaching of platinum and palladium with cyanide has been proposed a number of times as a promising precious group metals (PGM) process option, and although platinum extractions are problematic, progress into the understanding of cyanide leaching of PGM containing ore and concentrate has been made. The platinum and palladium leaching will typically take place at elevated temperatures, which can range from 55°C on heaps to 180°C in autoclaves, with a better degree of leaching occurring with higher temperatures. Although this process for Pt and Pd extraction is a promising process option, research regarding the feasibility of the subsequent upgrading and recovery of the pregnant PGM leach solution, however, has been lacking. Since the carrier-phase extraction of gold using activated carbon offers significant advantages over other processes in terms of simplicity, the high pre-concentration factor, rapid phase separation, and relatively low capital and operating costs, activated carbon was deemed the most suitable sorbent for a Pt and Pd adsorption and stripping process. Very little is published on the adsorption of PGM cyanides onto activated carbon and when the effect of impurities such as base metals and thiocyanate together with a suitable elution method, are considered, no information could be found in the open literature. This study was launched and in general it was found that the activated carbon process does seem to be a viable process consideration for the upgrading of PGMs in a cyanide leach stream. Adsorption rates for dilute PGM solutions (0.15mg/L Pt, 0.38 mg/L Pd, 0.1 mg/L Au) in a stirred vessel indicated a high rate of adsorption within the first 60 minutes (giving more than 98% recovery of precious metals). A comparison of the Pt isotherm (25°C) to Au isotherms from literature indicated a similar loading capacity, while that of Pd was found to be significantly lower. In common with most diffusion controlled processes, an increase in the adsorption rate of platinum, palladium and gold cyanide with an increase in temperature was observed, while experiments with consecutive contacts of the PGM cyanide solution onto the activated carbon revealed that with an increase in temperature, the amount of PGMs that were adsorbed, decreased with each loading. In the absence of free cyanide and base metals, it was found that after 4 consecutive contacts, 99% of the total amount of platinum and palladium adsorbed at 25°C, compared to 85% of the platinum and 83% of the palladium at 50°C. No difference could be seen between the adsorption of gold cyanide at 25 and 50°C after 4 contacts. It has also been established that the detrimental effect of free cyanide on the adsorption of PGMs will increase as the temperature increases. The detrimental effect of the presence of Cu and Ni was found to depend on the amount of these base metals adsorbed, which in turn will depend on the cyanide concentration and the solution temperature. Adsorption of Pt and Pd has been found to be significantly more affected by temperature, cyanide and base metals than the adsorption of gold and needs to be carefully taken into consideration with the design of a PGM adsorption circuit to ensure sufficient Pt and Pd recovery. It is therefore highly likely that an activated carbon recovery process for Pt and Pd cyanide will not be as robust as the gold CIS (carbon-in-solution) process, which is considered to be one of its main advantages. The feasibility of eluting platinum and palladium cyanide complexes from activated carbon was investigated. It was found that platinum and palladium elute from activated carbon almost to completion in 4 to 5 bed volumes (BV) at 80°C, while the elution of gold at this temperature is slow, with a significant amount of gold (≈ 55 %) still to be eluted after 16 bed volumes. An increase in Pt and Pd elution kinetics was demonstrated with an increase in temperature with 99% recovery achieved at 4 BVs with an elution temperature of 95°C. Cyanide pre-treatment has been found to have a large influence on PGM elution. The effect of the NaCN concentration shows an increase in the recovery of Pt, Pd and Au as the cyanide increases from 0 to 2 %, after which the recovery starts decreasing again as the NaCN concentration increases from 2 to 4%. The NaOH concentration was also found to affect the PGM recovery and at 0% NaCN, an increase in the recovery is seen, while at a higher cyanide concentration (2 and 3% NaCN) a decrease in the PGM recovery occurs when the NaOH concentration is increased from 0.22% to 1.65%. A general decrease in Pt, Pd and Au recovery was seen as the ionic strength of the elution water increased and is consistent with literature on Au elution. The effect of a hydrochloric acid pre-treatment, which forms part of the process to remove calcium build-up from the activated carbon, was investigated, and for all the cases the Pt and Pd recovery increased when an acid pre-treatment was performed, compared to no acid pre-treatment. In none of the cases did any of the Pt, Pd or Au elute with the acid or the following rinsing water. The acid pre-treatment performed at 70°C removed a significant 64% to 75% of the Ni present and an additional 9.1% to 10.5% in the following rinsing water step. In the presence of copper cyanide, the elution order has been found to be copper, palladium, platinum and gold, which is the opposite order of adsorption preference. The cyanide pre-treatment has also been found to have a major influence on the elution of Cu and can be explained by the difference in the absorbance strength between the different copper cyanide complexes. The presence of Cu did not have a negative effect on the elution of the PGMs at strong pre-treatment (2% NaCN and 0.55% NaOH) conditions, but at weak pre-treatment conditions (0% NaCN) the recovery of Pt and Pd was reduced by between 10 and 18% after 5 BVs when Cu was present. The presence of 100 mg/L KSCN salt added to the leach solution during the adsorption stage, reduces the elution recovery of the PGMs at 4 BVs from 90% for Pt and Pd, when not present, to approximately 70% when present. The addition of the additional K+ ions reduced the recovery by less that 4% at 4 BV, which indicates that the possible formation of a PGM bonding with thiocyanate ([Pt(SCN)4]2- and [Pd(SCN)4]2-), which adsorb onto carbon, but doesn’t adsorb with water, cannot be ruled out completely. A maximum amount of 0.15% for Pt, 0.28% Pd and 0.6% Au was found to report to the pre-treatment solution at 25°C. For higher pre-treatment temperatures, the amount of Pt and Pd reporting to the pre-treatment solution increased significantly to approximately 8% at 80°C, while the increase in gold was marginal to 0.8% at 80°C. For the higher loading on the activated carbon (7000 mg/kg Pt and Pd), which is expected to be a better representation of plant conditions, 0.07% Pt, 0.11% Pd and 0.12% Au reported to the pre-treatment solution. The PGMs reporting to the pre-treatment solution is attributed to the distribution of the PGMs on the carbon particle, and even though very small, a certain amount of these PGMs would readily desorb or wash off the carbon. It has thus been established here that the stripping of adsorbed platinum cyanide complexes from activated carbon consists of a two step batch process, which involves the pre-treatment of the metal-loaded activated carbon with a relatively strong sodium cyanide and sodium hydroxide solution, prior to the elution step with de-ionized water at 80°C. Through the development of a mathematical model to describe this process, it was found that the rate of release of the platinum ions is governed by the amount of platinum and sodium on the activated carbon and the concentrations of these ions in the bulk of the liquid. This is mathematically described by a modified Freundlich isotherm equation and the mass transfer diffusion equation. The dependency of the platinum elution rate on the sodium concentration on the activated carbon, as suggested by gold related literature (Van Der Merwe and Van Deventer, 1990, Stange, 1990), is confirmed. Furthermore it has been found that the rate of platinum elution interchangeably depends on the equilibrium of the Pt ions at the carbon-liquid interface and the mass transfer of these Pt ions from the interface to the bulk liquid. As both of these rate-limiting factors were found to depend on the sodium concentration, the dominant platinum elution rate limiting factor shifts as the sodium concentrations change as the elution progresses. Four main time periods are used to simplify and to describe this process. The benefits of fundamentally understanding this process can ultimately lead to improved elution, better process control, shorter elution times, smaller elution columns or assist in the development of a continuous elution process.
The adsorption characteristics of precious and base metals on four different ion-exchange resins
(Stellenbosch : Stellenbosch University, 2000-12) Els, Ellis Raymond; Lorenzen, L.; Aldrich, C.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: Adsorption tests were conducted with four different ion-exchange resins to determine the equilibrium adsorption of a range of precious and base metals. The adsorption characteristics were determined for synthetic single metal, as well as for multicomponent and base metal solutions. The effect of the el- concentration on the equilibrium adsorption was established for three different Hel concentrations in the above solutions. From the ion-exchange characteristics determined, a selective adsorption sequence is proposed for the separation of precious and base metals. Pure platinum, palladium and gold were dissolved in aqua regia and diluted to 2000 ppm (as metal) in 4M Hel. Ruthenium, rhodium and iridium were dissolved from pure salts in Hel. A 2000 ppm base metal solution was prepared by dissolving all the required components, including precious metals, to match an in-plant industrial basemetals solution composition. For each precious metal the equilibrium adsorption was determined for a couple of solution concentrations. Data points for adsorption curves were established by varying the amount of resin added to the test solution of a specific concentration. The equilibrium solution concentrations were determined by Iep analysis after 24 hours of exposure, using the bottle-roll technique. The experimental results obtained indicate a possible process route for the separation of precious metals with ion-exchange resin. The XAD7 resin is highly selective for gold from mixed solutions containing precious and base metals. It is also evident that, with the gold removed from the solution, the A22 resin adsorbs only palladium. IR200 resin adsorbs only the base metals from the solution. With all other precious metals removed from the solution (platinum and ruthenium must be extracted by other means), iridium can be adsorbed from the solution by IRA900 resin which is highly selective for iridium over rhodium. For all of the anion resins, XAD7, IRA900, and A22, the chloride concentration of the solution did not have a big effect on the adsorption capacity. However, the adsorption of base metals on IR200 is sensitive to chloride concentration, with a rapid reduction in adsorption at higher chloride concentrations. Statistical models were developed for the adsorption of each of the precious metals, as well as for the base metal solution. All adsorption data, obtained for a resin (typically 250 equilibrium data points), was used in the development of the model. The SPSS statistical software package was used to develop linear regression models. The interaction between all the input parameters, e.g. the interaction of gold and chloride ions, was modelled by specifying the product of the gold and the chloride concentrations as an input variable. The variables that determine the adsorption quantities were identified. High solution concentrations of the target adsorption component increase the adsorption quantity. It has been established that a higher platinum concentration increases the adsorption quantity of gold on XAD7 resin. However, the adsorption quantity is reduced at higher ruthenium concentrations. The adsorption quantity of iridium on IRA900 is reduced with increased rhodium concentration. The adsorption quantity of palladium on A22 is increased by the presence of rhodium and decreased by larger concentrations of iridium and platinum. The adsorption of base metals on IR200 is decreased at higher acid concentrations. Higher concentrations of gold in the base metal solution also decrease the adsorption quantity of base metals. The model predicted adsorption of each component compares well with the actual measured values. In batch adsorption tests the counter ion is not removed from the resin. The resin capacity for a specific ion concentration could therefore not be determined. As such, the adsorption models are only valid for the initial part of the ion-exchange process. The effect of kinetics on the adsorption was not determined.
Adsorption of 3,7-dimethyl-1-octanol in single and binary mixtures using Selexsorb CD®
(Stellenbosch : Stellenbosch University, 2023-03) Louw, Anke; Schwarz, Cara Elsbeth; Stellenbosch University. Faculty of Engineering. Dept. of Chemical Engineering.
ENGLISH ABSTRACT: The petrochemical industry is considered to be one of the large contributors to the global economy. The hydrocarbons produced by it are readily used as fuels. The product streams engendered by hydrocarbon production can contain low concentrations of by-products such as alcohols, which have inherent industrial value. Adsorption is a favoured method of separating 1-alcohols from an n-decane stream, as it is the most versatile, economic, and environmentally friendly among separation methods. It is a three-step process consisting of an external mass transfer, an internal mass transfer and adsorption onto active sites. The process typically occurs by means of physisorption or chemisorption. The aim of this study is to expand the limited 1-alcohol adsorption database by investigating the adsorption of 3,7-dimethyl-1-octanol (3,7- DMO), 1-octanol&3,7-DMO and 1-decanol&3,7-DMO from n-decane while using Selexsorb CD® (SCD). The project scope includes the investigation of these systems at different temperatures and initial concentrations and adsorbate ratios for the binary component systems through experimental work and kinetic and equilibrium Modelling. The experimental work was conducted using a bench-scale water bath batch-adsorption system. Mesh baskets were filled with 10 g adsorbent and fully submerged in beakers containing a solution of 0.5-3.3 alcohol and the remainder n-decane. Kinetic and equilibrium studies were conducted along with displacement tests for the two binary systems. Kinetic and equilibrium isotherm models were fitted to the datasets by using nonlinear regression. Certain project shortcomings were identified when it was consistently seen that the kinetic data generated for 3,7-DMO, 1-decanol&3,7-DMO and 1-octanol&3,7-DMO adsorption onto SCD was accompanied by a drop in adsorbate loading from 7 h to 24 h. The major project shortcoming was the primary batch experimental setup which had beakers open to atmosphere that facilitated evaporation of the water in the water bath and subsequent condensation of said water vapour dripping into the solution. Additionally, solution evaporation also took place which meant that the assumption of constant volume of solution throughout the 24 h experiment was incorrect. A secondary batch experimental setup, where the feed stock was submerged in a sealed Schott bottle, minimised the potential of evaporation or condensate droplets forming in the solution and the kinetic profiles generated at 45 °C approached equilibrium with no drop in adsorbate loading between 7 to 24 h. For the adsorption of 3,7-dimethyl-1-octanol, it was found that an increase in initial concentration increased the equilibrium adsorbent loading achieved but that it plateaued beyond 1.5 mass%. An increase in temperature increased the adsorbent loading achievable for the first 7 h. The maximum adsorbate loading achievable for 3,7-DMO onto SCD was found to be approximately 114 mg.g-1. The pseudo-second-order model (R2 = 0.98) was the best fitting kinetic model and the Langmuir and Redlich-Peterson equilibrium isotherm models (R2 = 0.9) fitted the single equilibrium data best. Stellenbosch University https://scholar.sun.ac.za iv In the case of the two binary component systems, it was found that temperature had no discernible effect on the adsorbent loading. An increase in overall initial concentration increased the adsorbent loading for the first 7 h, but the equilibrium adsorbent loading appeared to fluctuate with no discernible trend. The binary component systems both indicated that the Elovich model fitted the data well at 25 Σ and the pseudo-second-order model fitted best at 45 Σ . The rate constant and maximum loading were higher at 45 Σ as compared to 25 Σ . The binary component isotherm models that fit the two binary component systems best were the extended Freundlich and modified competitive Langmuir model indicating that both systems were heterogeneous in nature and interaction does occur between adsorbate molecules. could not predict the binary component adsorbate loadings as accurately as the single component models. Displacement tests showed that linear, smaller molecules are preferentially adsorbed when compared to branched, larger molecules. The displacement potential ranked from largest to smallest was 1-octanol, 1-decanol and 3,7-DMO. Recommendations for future studies include quantifying through experimental work some thermodynamic properties such Gibbs free energy and entropy of adsorption. All future batch adsorption tests are recommended to be performed on experimental setups that seal the adsorption system and prevents water ingress or solution evaporation. Lastly, semi-continuous experiments can be performed to obtain 3,7-DMO adsorption data when the solution is allowed to flow through a packed bed rather than stirred.
Adsorptive separations in the production of neutral wine alcohol
(Stellenbosch : Stellenbosch University, 2002-03) Goliath, Elroy Mario; Cloete, F. L. D.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: This study describes the design, construction, complete industrialisation and operation of a dual bed vacuum swing adsorption (VSA) demonstration plant, which operates at atmospheric and sub-atmospheric conditions. All design objectives as set out initially were met. The plant removes contaminants such as methanol and water from neutral wine spirit. Neutral wine spirit is a key component of various local and international spirituous products which include liqueurs, gin, vodka, fortified wines and brandy. Neutral wine spirit can chemically be described as the azeotropic mixture of ethanol and water, which occurs at an ethanol content of 96.4 vol. %. Methanol is naturally present in all products from the vine. Fermentation and distillation concentrate methanol even more, and due to physical and chemical characteristics, its separation consumes as much as 45 % of total production costs. Neutral wine spirit is produced by the proven technology of continuous atmospheric distillation. Continuous improvement of the distillation process is limited due to the physical constraints of an old facility, but also due to previous design philosophies and approaches. The VSA plant consists of two adsorbers, packed to a total height of 1.71 m and a diameter of 0.4 m. Adsorption took place at 100 °C and regeneration at the same bed temperature with purified nitrogen gas at 170 °C and a vacuum of 17 kPa (abs). Experiments were divided into Group I and Group II experiments. Group I investigated the ability to separate methanol and water from the azeotrope and to which efficiency it occurred. It consisted of 120 adsorption cycles of 5 minutes each and 60 samples were drawn for analyses. Breakthrough was not allowed to occur. The azeotropic feed was consistently dehydrated to a water content < 0.05 wt %, while methanol was reduced to < 4 mg/100mLAA. The type of 3A molecular sieve (MS 564 CS) was specifically selected to ensure analytic as well as organoleptic compliance with the product specification. Molecular sieve 4A was removed due to organoleptic problems with the product. Group" experiments were performed in the format of a sensitivity analysis. The effects of various process parameters on the methanol breakthrough curves were individually assessed. Eighteen experiments were performed over a period of 8 days, with 86 samples drawn. The duration of an adsorption cycle was 30 minutes, allowing methanol breakthrough to occur. Water was preferentially adsorbed. Negative methanol bed loadings during high water loadings confirmed that water was able to displace methanol molecules. In the presence of water, molecular sieve 3A was capable of adsorbing 0.6 mg methanol/100mLAA, while in the absence of water with synthetically dosed methanol, molecular sieve 3A achieved a maximum loading of 12.3 mg methanol/100mLAA. The latter corresponded with a maximum methanol feed content of 1118 mg/100mLAA. In general, quicker breakthrough occurred at higher flow rates and feed concentrations. Continuous breakthrough caused bed contamination and a 24-hour thermal regeneration was performed following experiment 12. The feed flow rate was increased from the theoretical 50 f/hr to 70 f/hr without any additional capital layout. Selected process conditions were found to be effective in continuously separating methanol from ethanol. Depending on the strategy of integration, profitability studies shows a Return on Investment of between 110.1% - 220.8% for the adsorption project. Adsorption is superior to distillation in the separation of methanol. Due to the level of innovation involved, it is recommended that the contents of this study remain confidential and patent protection is to be extended. This dissertation speaks to both the wine making as well as the chemical engineering fraternity. It seeks to provide credibility to both parties, by clarifying the unknown issues fundamental to the respective disciplines.
Advancing Lignocellulosic Biorefineries through Co-Production of Hemicellulosic Biopolymers and Bioenergy
(Stellenbosch : Stellenbosch University, 2022-04) Mihiretu, Gezahegn Teklu; Görgens, Johann Ferdinand; Chimphango, Annie Fabian Abel; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH SUMMARY: This research project was conceived in the context of advancing a lignocellulosic biorefinery for co-production of xylan biopolymers, bioethanol and electricity from two agro-industrial materials, namely sugarcane residues (SCT) and aspen wood (AW). The research was primarily designed to include two full-fledged experimental studies and one techno-economic case study. Accordingly, two biomass pretreatment approaches, namely: microwave-assisted pressurised hot water (MWA-PHW) and alkalinised steam explosion pretreatment (ASEPT) methods were experimentally investigated for their effect on the extraction of xylan from SCT and AW. Extraction experiments (via MWAPHW and ASEPT) were conducted by varying temperatures between 165 – 205 ℃ and retention times 3 - 22 min at test points identified using Central Composite Design (CCD) as response surface methodology (RSM). Pretreatment conditions were intended for a dual purpose: maximizing xylan extraction yield while simultaneously enhancing cellulose digestibility. Experimental results on xylan yield and cellulose digestibility were analysed using ANOVA method to establish optimal conditions for significantly enhanced values. Accordingly, under the MWA-PHW method, maximum xylan yields of 66 and 50%, and highest cellulose digestibility of 78 and 74%, were respectively attained for AW at (195℃, 20 min) and SCT at (195 ℃, 15 min). Whereas maximum xylan yields of 51 and 24%, and highest cellulose digestibility of 92 and 81%, were attained for SCT and AW respectively, following their pretreatment under ASEPT at (204 ℃, 10 min). Under both methods, the xylan extracts were predominantly non-monomeric with insignificant formation of degradation products. This strongly suggested both MWA-PHW and ASEPT were viable approaches for xylan extraction purposes. ANOVA results also revealed that temperature was the dominant factor influencing the xylan yield and cellulose digestibility. The techno-economic case study was aimed at evaluating the economic viability of the biorefinery for co-production of xylan biopolymers, bioethanol and electricity (i.e. main-case scenario, MCS) against two benchmark processes, i.e. Base-case (BCS) and Intermediate-case (ICS) scenarios, where only bioethanol and electricity are produced from sugarcane residues (Basis: daily capacity of 1000 tons of dry biomass subjected to ASEPT condition of 204 ℃ and 10 min). The study results showed that co-production of xylan biopolymers substantially improved the economic performance of the main biorefinery case (i.e. MCS) by lowering the selling price of ethanol against higher values under the benchmark processes. A minimum hemicellulose selling price (MHSP) of 809 USD/ton of xylan co-product was determined by fixing ethanol selling price at 0.70 USD/L (market price of ethanol in 2019); higher MHSP values certainly lead to further lower prices. Minimum ethanol selling prices (MESP) under the MCS, BCS and ICS were respectively estimated at 0.61, 0.95 and 0.81 USD/L, where the xylan price was assumed at 1000 USD/ton (=> MCS). Even though the economic viability of the main biorefinery case was significantly enhanced with co-production of xylan than without, this multiproduct biorefinery complex was rendered rather energy-intensive as a result of such coproduction scheme where the recovery of xylan biopolymers necessitated substantial thermal and electrical energy demands. From environmental point of view, the coproduction of xylan biopolymers along with bioethanol and electricity was shown to have a positive contribution towards mitigating GHG emissions from fossil sources. The GHG emissions savings under the MCS, BCS and ICS were estimated around 69, 64 and 65% against gasoline as fossil baseline of 90 gCO2eq/MJ (RSB-Global), but there was only marginal difference between the savings under the main biorefinery case and that under the benchmark processes.
Advantages associated with the implementation and integration of environmental management systems in small manufacturing businesses
(Stellenbosch : Stellenbosch University, 2003-12) Bezuidenhout, Sol; Lorenzen, L.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: TheSouthAfrican economy islargely dependant on small enterprisesas a valuable source of job creation, gross domestic product as well as product development and innovation, However, unfortunately there existsan extremeiy high failure rate among small businesswith 20%of startup businessesfailing within the firstyear of operation, and an almost 60% failure rate within the first6 years of existence, Thesestatisticshave initiated several research studies,and have been the focus of many businessbooks, in itseif, creating a vast industry of small businesssuccesstools and quick fix solutions, When considering the high failure rates of small businesses,the concepts surrounding sustainable development come into question by pure method of association, Sustainable development issueshave become a top priority globally and have moved up the corporate agenda in recent years. When trying to "marry" these two concepts, questions arise regarding the effect of integrating sustainability principles and management systems,with contemporary small businessstrategy. Theaim of thisstudy isto investigate existingcritical successmodels and to integrate some simple initial stages of sustainable development business strategy within these models. Expectantly, some of the principles contained in the formalisation of management systems that address sustainability issues,could be incorporated in traditional management models in an attempt to identify possible interventions and tools that might positivelyimpact on the successrate of small businessenterprises. These concepts would be tested by means of implementing a formal environmental management system (based on the ISO 14001standard) as an initial approach to addressingsustainabilitygoals, as a case study, The successful implementation of an ISO 14001 environmental management system at this small businessenterprise, realised several advantages for the company, and have been used to adapt traditional management models to include for some of the simple concepts of sustainable development.
Aerosol synthesis of ceramic particles by seed growth : analysis of process constraints
(Stellenbosch : Stellenbosch University, 2002-04) Human, Chris; Bradshaw, S. M.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: Aerosol synthesis involves the formation of condensable product species by gas-phase reaction, and the simultaneous growth of particles by coagulation. For the production of ceramic particles, reaction temperatures higher than 700 K are commonly used, and a maximum fusible particle size is observed. Coagulation-controlled growth yields spherical particles up to the maximum fusible size (approximately < 50 nm). Such particles coalesce rapidly and completely upon collision with other particles, whereas larger particles reach a meta-stable equilibrium for solid-state coalescence. Agglomerates with weak Van der Waal's bonds between particles inevitably form in the cooling/collection process. Coagulation of particles larger than the maximum fusible particle size yields agglomerates with significant neck growth between the primary particles. Spherical ceramic particles in the order of 1 J-Lm are favourable precursors for bulk electronic applications that require high purity. Such large spherical particles may possibly be produced in conditions of seed growth, which involves the deposition of small newly formed clusters onto larger existing particles. The central focus of the present work is to evaluate whether spherical ceramic particles significantly larger than the maximum fusible size may be produced by seed growth. The evaluation is done by modelling of process constraints and interpretation of published results. The modelling of constraints is based on a mathematical framework for comparison of different values of reactor design parameters. This framework comprises a simplified model system, a typology of quantities, and isolation of a set of independent design parameters. Comparison is done on the basis of fixed initial (seed) and final (product) particle sizes. The reactor design framework is used to evaluate the hypothesis on spherical seed growth, by assessing whether a reactor can be designed that satisfies all the process constraints. Future extension of the framework may allow optimisation for seed growth in general. The model system assumes laminar flow and isothermal conditions, and neglects the effect of reactor diameter on wall-deposition. The constraints are graphically represented in terms of the design parameters of initial reactant concentration and seed concentration. The effects of different temperatures and pressures on the constraints are also investigated. In a separate analysis, the suitability of turbulent flow for seed growth is assessed by calculating Brownian and turbulent collision coefficients for different colliding species. As turbulent intensity is increased, the seed coagulation rate is the first coagulation rate to be significantly enhanced by turbulence, resulting in a lowering of the maximum seed concentration allowed by the constraint for negligible seed coagulation. This tightening of a constraint by turbulence is the justification for considering only laminar flow for evaluating the hypothesis on spherical seed growth. Quantitative application of the model of constraints, as well as experimental and modelling results from the literature, did not demonstrate that significant spherical seed growth is possible without seed coagulation (agglomeration). As part of the conceptual effort in becoming familiar with aerosol reactor engineering, a simple two-mode plug-flow aerosol reactor model was developed, and verified with published results. This model has some novel value in that it translates the equations for aerosol dynamics into the terminology of reactor engineering.
Alkaline polyol fractionation of sugarcane bagasse and eucalyptus grandis into feedstock for value added chemicals and materials
(Stellenbosch : Stellenbosch University, 2017-03) Pius, Moses Tuutaleni; Gorgens, Johann F.; Chimphango, Annie F. A.; Tyhoda, Luvuyo; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH SUMMARY: The main components of lignocellulosic biomass cellulose, hemicellulose and lignin are feedstock for chemical and material manufacturing processes. Integrated biorefinery processes incorporate the production of these valuable components from lignocellulose feedstock in good yield and quality. The nature and complexity of lignocellulose materials and its components require a well-designed process to fractionate these components into individual streams, while special attention is paid to the easily hydrolysed component, hemicelluloses. In the present study, a novel process for the fractionating sugarcane (Saccharum officinarum) bagasse (SCB) and Eucalytpusgrandis (EC) biomass into their main constituents (cellulose pulp, aqueous hemicellulose and lignin) is designed. Research focused on obtaining hemicelluloses in polymeric form or as biopolymers, while maintaining high yields and quality of cellulose and lignin polymers. This was achieved by following organosolv technique using high boiling point alcohols, xylitol and ethylene glycol as the fractionating solvents at concentrations between 20-30% (w/w) and 50-70% (v/v) respectively. The fractionation process’ central composite design incorporated mild conditions, i.e. fractionation time between 2-4 hours, temperatures at 140-180 ºC catalysed by sodium hydroxide between 1-2 wt.% and also subsequently investigated the option of pre-extracting hemicelluloses from the feedstock at previously established conditions prior to further fractionation with ethylene glycol given its hemicellulose destructing nature from literature studies. Results show hemicellulose alkaline pre-extraction to provide higher dissolutions and recoveries of hemicelluloses as compared to those extracted by direct fractionation with the two solvents. At optimum conditions xylitol fractionations achieved higher component recoveries as compared to ethylene glycol. However, ethylene glycol fractionations are more severe in dissolving not only hemicellulose and lignin from both materials but also cellulose. Ethylene glycol fractionations were also accompanied by a high degree of cellulose dissolutions, in some runs up to 39% of the initial, mostly at extreme conditions. Hemicelluloses from all processes were recovered as biopolymers with weight-average molecular weight (Mw) evaluation revealing that alkaline pre-extracted hemicelluloses had highest weight-average molecular weights, 33 638 and 61 644 gmol-1 for sugarcane bagasse and Eucalytpus grandis respectively, as compared to direct raw material fractionation processes which all gave below 23 000 gmol-1 with xylitol processes giving higher molecular weights than ethylene glycol processes. Enzymatic hydrolysis of cellulose revealed ethylene glycol residues to be more digestible (≥60%) than xylitol derived residues (≤60%). Digestibility is further improved with fractionation of hemicellulose pre-extraction solids (≥80%). In terms of cellulose crystallinity, a general increase after fractionation was observed. Residual solids from ethylene glycol treatments displayed higher crystallinity (50.08% EC, 48.44% SCB) as compared to xylitol processes (32.44% EC, 43.98% SCB). Residual solids from the NaOH hemicellulose pre-extraction step also had high crystallinities (43.58% EC and 47.81% SCB) than the xylitol process but just lower than EG derived residual solids (≥48%). There is a major decline in the amount of syringyl and guaiacyl groups in the lignin residues after treatment for all processes supported by low intensity bands in Fourier Transform Infrared Resonance (FTIR). Minimal degradation of lignin fraction by both processes was observed with low fixed carbon content of lignin rich solids, below 20%. In conclusion, xylitol fractionations overweighed ethylene glycol in hemicellulose, lignin and cellulose recoveries, and lignin and hemicellulose quality while ethylene glycol produced good quality cellulose. When compared to conventional organosolv fractionations (i.e. ethanol), these two polyols overweigh organosolv in aspects such as quality of cellulose, hemicellulose and lignin but comes short in terms of component recoveries particularly with ethylene glycol fractionations.
Ammonium thiosulphate leaching of gold from printed circuit board waste
(Stellenbosch : Stellenbosch University, 2017-03) Albertyn, Pierre Wouter; Dorfling, Christie; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH SUMMARY: Technological innovation leads to a reduced lifespan of older electrical and electronic equipment, which in turn leads to the generation of vast quantities of electronic waste (e-waste). The recycling of e-waste is becoming increasingly important as it provides certain economic benefits apart from the obvious environmental benefits. Printed circuit boards (PCBs) are found in most forms of e-waste and contain especially high concentrations of base and precious metals. Hydrometallurgy is one of the major processing routes for the recovery of valuable metals from e-waste. This processing route normally implements several leaching stages to selectively recover certain metals. A two-step base metal leaching stage was implemented that utilized two different lixiviants. The first step used nitric acid to mainly recover Pb and Fe, while the second step used sulphuric acid in combination with hydrogen peroxide to mainly recover Cu, Zn and Ni. The Au and Ag were subsequently recovered in an additional leaching stage with ammonium thiosulphate in the presence of copper(II) sulphate. This study focused on the use of a less environmentally hazardous lixiviant than the traditional alternative, cyanide, to promote the development of a more sustainable recovery process. The primary objective of this study was to determine how the variation of copper in the first stage residue will affect the gold leaching in the second stage. The extent of interactions between process conditions was also studied. These process conditions included temperature, thiosulphate concentration, ammonium concentration, cupric ion concentration, pH and pulp density. The secondary objective of this study was to determine how the degradation of thiosulphate was affected by the change in certain process conditions. The screening phase determined that only a change in S2O3 concentration, pH range and pulp density had a statistically significant effect on the Au extraction. Statistically significant interactions existed between the Cu on the PCBs and Cu(II) concentration; and the Cu on the PCBs and pulp density. These results were used together with recommendations from literature to determine what factors to include in the full factorial design. The S2O32- concentration (0.1 and 0.2 M), NH3 concentration (0.2 and 0.4 M), pH range (9 – 9.5 and 10 – 10.5) and pulp density (25 and 50 g/L) were chosen. The investigation of the S2O32- and NH3 concentrations determined that Au leaching was dependent on the S2O32-/NH3 ratio. S2O32- concentrations that were too high relative to NH3 resulted in the Cu(S2O32-)35- complex becoming more prominent, which hindered Au dissolution. NH3 concentrations that were too high resulted in a decrease in the oxidation potential of the Cu(II)-Cu(I) couple, which in turn reduced the driving force for the Au leaching reaction. NH3 concentrations that were too low reduced the amount of Cu(NH3)42+ (oxidizing agent for gold) that was available, which in turn also reduced Au leaching. The optimum S2O32-/NH3 ratio for the range of parameters that were investigated was found to be 0.5. A change in NH3 concentration was found to have a more significant effect on Au extraction at the lower pH range of 9 – 9.5. This was believed to be due to a higher concentration of NH4+ relative to NH3 being present at lower pH values, which caused faster Au leaching. The lower pH range of 9 – 9.5 also generally produced better Au leaching. An increase in pulp density from 25 to 50 g/L resulted in a decrease in Au extraction, which could be attributed to the fact that the amount of reagent per unit weight of PCB decreased. The importance of the interactions between S2O32- and NH3; and pH range and NH3 were confirmed in the statistical analysis of the full factorial design. The statistical analysis produced a model with a R2 value of 0.94 that predicted an optimum Au extraction of 78.04 % at the same conditions that produced the optimum Au extraction during testing. The predicted an optimum compared well with actual value of 78.47 %, which was obtained at 0.2 M S2O32-, 0.4 M NH3, 0.02 M Cu(II), 25 g/L, 25°C, 1 – 10 % leftover Cu and pH range of 9 – 9.5. The optimum conditions were used to determine the effect of a variation in Cu in the first stage residue, temperature and Cu(II) concentration. Au extraction decreased with an increase in Cu leftover content, temperature and Cu(II) concentration. Increased amounts of Cu inhibited Au leaching through the dissolution of Cu to Cu(NH3)2+ with the consumption of Cu(NH3)42+. Increased rates of thiosulphate consumption/degradation were encountered at higher temperatures, Cu(II) concentrations and leftover Cu.
Anaerobic co-digestion of fish sludge originating from a recirculating aquaculture system
(Stellenbosch : Stellenbosch University, 2022-12) Netshivhumbe, Rudzani; Goosen, Neill Jurgens; Faloye, F.; Gorgens, Johann F.; Mamphweli, N.S.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: Recirculation aquaculture systems (RAS) are considered as sustainable and environmentally friendly aquaculture systems capable of meeting the growing demand of seafood for human consumption. However, RAS produce large quantities of waste sludge from uneaten feed and fish faecal matter, which need to be removed from the recirculating water and treated to prevent adverse environmental impacts. Anaerobic digestion (AD) has been considered as an alternative method to stabilize the amount of organic waste in the environment before its disposal, with the simultaneous production of bio-methane that can serve as a source of energy within RAS. However, there are some drawbacks in the mono-digestion process of fish sludge (FS) such as process inhibition, unbalanced nutrient contents, and low methane yields. The biomethane production from FS, food waste (FW), and fruit & vegetable waste (FVW) was optimized during anaerobic co-digestion using a mixture design. The synergistic and antagonistic interaction effects of the three substrates on specific methane yield, volatile solids reduction, and process stability were evaluated in both batch and semi-continuous mode. A mixture design was used to determine the best mixture compositions of FS, FW, and FVW for specific methane yield and volatile solids removal during the anaerobic co-digestion process based on biomethane potential (BMP) measurements. The results showed that the optimum mixture proportions of FS, FW, and FVW were 63 %, 18 %, and 19 %, respectively. The results showed the maximum methane production and VS removal of 401 mL CH4/gVS and 64%, respectively under the optimum mixture. Anaerobic co-digestion of FS with FW and FVW enhanced the methane yields by 8 folds compared with mono-digestion of FS. The optimum mixture proportions obtained from batch BMP tests were further evaluated in 50 L batch and 30 L semi-continuous pilot-scale digesters to evaluate the effect of organic loading rate (OLR) on biogas production and process performance stability. The methane yield obtained from the batch pilot-scale digester was 272 NmLCH4 /gVS. This was 71 % of the methane yield obtained from the BMP test under the same optimum mixture condition. The batch digester showed no substantial inhibition of the system due to its strong buffering capacity. In semi-continuous mode, the digester was conducted under different OLRs of 1, 2, and 3 𝑔𝑉𝑆𝐿−1𝑑−1 to investigate the impacts of OLR on biogas and methane production, and process performance stability of the anaerobic co-digestion of FS, FV, and fruit and FVW. The highest total biogas and methane production of 388 L/gVS and 67 L/gVS, with a methane content of 66.8% obtained at an OLR of 2 𝑔𝑉𝑆𝐿−1𝑑−1 compared to OLRs of 1 and 3 𝑔𝑉𝑆𝐿−1𝑑−1. The digester showed instabilities or failure at an OLR of 3 𝑔𝑉𝑆𝐿−1𝑑−1 due to acid crash and accumulation of VFA of 11g/L. An OLR of 1- 2 𝑔𝑉𝑆𝐿−1𝑑−1 is recommended for anaerobic co-digestion of FS, FW, and FVW in semi-continuous digesters because of less inhibitor indicators observed.
Anaerobic co-digestion of fruit juice industry wastes with lignocellulosic biomass
(Stellenbosch : Stellenbosch University, 2019-04) Kell, Carissa Jordan Kayla; Gorgens, Johann F.; Louw, Tobias M.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: The fruit juice industry in South Africa forms an important part of the South African economy, however it generates large quantities of liquid and solid organic wastes. Landfilling is typically used to dispose of these wastes, resulting in uncontrolled greenhouse gas emissions (GHG). Anaerobic digestion (AD) offers an alternative waste disposal method and produces two valuable by-products: biogas (a renewable energy source) and a liquid fertiliser. The high sugar content of fruit waste alone often results in AD failure due to acidification, resulting in poor quality biogas. Consequently, there is relatively little information available on the AD of apple fruit juice process wastes (FJPW). Identification of substrate combinations that improve the energy value of the resultant biogas may mitigate GHG emissions and generate valuable by-products which provide additional revenue streams to industry. This study thus aimed to identify optimal substrate combinations to aid in waste disposal of FJPW and energy value of biogas from fruit juice industry waste based on seasonal availability of waste streams. Five waste streams: manure, food waste, retentate, pomace and waste apples were incorporated into a five-factor mixture design to assess food waste and manure as co-substrates of FJPW. This design was carried out in a series of biomethane potential (BMP) tests performed in 100 mL serum bottles. A second mixture design was performed using BMP tests in 100 mL bottles to evaluate lignocellulosic biomass (LCB) as a potential co-substrate of FJPW. A biogas and methane optimisation substrate mixture (50% manure, 30% LCB, 20% Retentate) and a manure minimisation mixture (30% manure, 30% LCB, 30% retentate, 10%waste apples) were selected and scaled up in 50 L CSTR reactors in batch process for 32 days with intermittent mixing. Two substrate combinations based on biogas optimisation and manure minimisation were scaled-up in 50 L reactors in semi-continuous process and fed increasing organic loading rates (OLRs) from 1-4 gVS/L/day over the course of 32 days to identify the maximum OLR that can be stably operated for each point. The results indicated food waste was highly variable and behaved similarly to FJPW when digested, thus food waste was deemed unsuitable as a co-substrate for FJPW. An ANOVA was performed on the results of the LCB mixture design revealing both biogas and methane production to be significant (p< 0.05). The standardised effect estimates of all five feedstocks revealed manure, LCB and retentate to have a significant (p<0.05) effect on biogas and methane production. LCB addition was found to significantly improve biogas production and prevent acid crash, however it mainly did so when compensating for the fruit waste fraction rather than the manure fraction except for two mixtures: 20% manure, 30% LCB, 30% pomace and 20% retentate and 20% manure; 30% LCB, 30% waste apples and 20% retentate. The highest yields obtained from the LCB supplementation experiment were 410.01 mL.gVS-1 fed biogas and 167.10 mL.gVS-1 fed methane for the fruit-juice producing season and 325.69 mL.gVS-1 fed and 131.95 mL.gVS-1 fed for the non- juice producing season. The improved biogas and methane yields in the batch experiment compared to lab-scale were as a result of slow intermittent mixing at 125 rpm for 5-10 minutes twice daily. The biogas optimisation point gave the highest yields at an OLR of 4 gVS/L/day. The manure minimisation point demonstrated the highest biogas and methane production at an OLR of 3.5 gVS/L/day, with the system showing signs of organic overloading at a higher OLR. To conclude, this study found a 30% LCB addition to improve digestibility of fruit process waste mixture for certain combinations of pomace and retentate, and waste apples and retentate with 20% manure. As this study only investigated 0%, 20% and 30% LCB supplementation, future research should focus on a broader array of supplementation levels in order to further maximise fruit waste disposal via AD.
Analysis and modelling of mining induced seismicity
(Stellenbosch : University of Stellenbosch, 2006-12) Bredenkamp, Ben; Aldrich, C.; University of Stellenbosch. Faculty of Engineering. Dept. of Process Engineering.
Earthquakes and other seismic events are known to have catastrophic effects on people and property. These large-scale events are almost always preceded by smallerscale seismic events called precursors, such as tremors or other vibrations. The use of precursor data to predict the realization of seismic hazards has been a long-standing technical problem in different disciplines. For example, blasting or other mining activities have the potential to induce the collapse of rock surfaces, or the occurrence of other dangerous seismic events in large volumes of rock. In this study, seismic data (T4) obtained from a mining concern in South Africa were considered using a nonlinear time series approach. In particular, the method of surrogate analysis was used to characterize the deterministic structure in the data, prior to fitting a predictive model. The seismic data set (T4) is a set of seismic events for a small volume of rock in a mine observed over a period of 12 days. The surrogate data were generated to have structure similar to that of T4 according to some basic seismic laws. In particular, the surrogate data sets were generated to have the same autocorrelation structure and amplitude distributions of the underlying data set T4. The surrogate data derived from T4 allow for the assessment of some basic hypotheses regarding both types of data sets. The structure in both types of data (i.e. the relationship between the past behavior and the future realization of components) was investigated by means of three test statistics, each of which provided partial information on the structure in the data. The first is the average mutual information between the reconstructed past and futures states of T4. The second is a correlation dimension estimate, Dc which gives an indication of the deterministic structure (predictability) of the reconstructed states of T4. The final statistic is the correlation coefficients which gives an indication of the predictability of the future behavior of T4 based on the past states of T4. The past states of T4 was reconstructed by reducing the dimension of a delay coordinate embedding of the components of T4. The map from past states to future realization of T4 values was estimated using Long Short-Term Recurrent Memory (LSTM) neural networks. The application of LSTM Recurrent Neural Networks on point processes has not been reported before in literature. Comparison of the stochastic surrogate data with the measured structure in the T4 data set showed that the structure in T4 differed significantly from that of the surrogate data sets. However, the relationship between the past states and the future realization of components for both T4 and surrogate data did not appear to be deterministic. The application of LSTM in the modeling of T4 shows that the approach could model point processes at least as well or even better than previously reported applications on time series data.
Analysis of process data with singular spectrum methods
(Stellenbosch : University of Stellenbosch, 2003-12) Barkhuizen, Marlize; Aldrich, C.; University of Stellenbosch. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: The analysis of process data obtained from chemical and metallurgical engineering systems is a crucial aspect of the operating of any process, as information extracted from the data is used for control purposes, decision making and forecasting. Singular spectrum analysis (SSA) is a relatively new technique that can be used to decompose time series into their constituent components, after which a variety of further analyses can be applied to the data. The objectives of this study were to investigate the abilities of SSA regarding the filtering of data and the subsequent modelling of the filtered data, to explore the methods available to perform nonlinear SSA and finally to explore the possibilities of Monte Carlo SSA to characterize and identify process systems from observed time series data. Although the literature indicated the widespread application of SSA in other research fields, no previous application of singular spectrum analysis to time series obtained from chemical engineering processes could be found. SSA appeared to have a multitude of applications that could be of great benefit in the analysis of data from process systems. The first indication of this was in the filtering or noise-removal abilities of SSA. A number of case studies were filtered by various techniques related to SSA, after which a number of neural network modelling strategies were applied to the data. It was consistently found that the models built on data that have been prefiltered with SSA outperformed the other models. The effectiveness of localized SSA and auto-associative neural networks in performing nonlinear SSA were compared. Both techniques succeeded in extracting a number of nonlinear components from the data that could not be identified from linear SSA. However, it was found that localized SSA was a more reliable approach, as the auto-associative neural networks would not train for some of the data or extracted nonsensical components for other series. Lastly a number of time series were analysed using Monte Carlo SSA. It was found that, as is the case with all other characterization techniques, Monte Carlo SSA could not succeed in correctly classifying all the series investigated. For this reason several tests were used for the classification of the real process data. In the light of these findings, it was concluded that singular spectrum analysis could be a valuable tool in the analysis of chemical and metallurgical process data.
Antimicrobial lipopeptide production by Bacillus spp. for post-harvest biocontrol
(Stellenbosch : Stellenbosch University, 2014-12) Pretorius, Danielle; Clarke, Kim G.; Stellenbosch University. Faculty of Engineering. Department of Process Engineering.
ENGLISH ABSTRACT: As overpopulation threatens the world’s ability to feed itself, food has become an invaluable resource. Unfortunately, almost a third of the food produced for human consumption is lost annually. Pests including insects, phytopathogens and weeds are responsible for more than a third of the annual major crop losses suffered around the world. The majority of current post-harvest control strategies employ synthetic agents. These compounds, however, have been found to be detrimental to the environment as well as human health, which has led researchers to investigate alternative strategies. Biocontrol agents are environmentally compatible, have a lower toxicity and are biodegradable, making them an attractive alternative to the synthetic control agents. The lipopeptides produced by Bacillus spp. in particular, have shown great potential as biocontrol agents against various post-harvest phytopathogens. Most biocontrol strategies apply the biocontrol organism, for example Bacillus, directly, whereas this study focused on the use of the lipopeptide itself as an antifungal agent. This is advantageous as the lipopeptides are less sensitive to their surroundings, such as temperature and pH, compared to living organisms, allowing for the production of a standardized product. This study investigated the production of the Bacillus lipopeptides surfactin, fengycin and iturin under controlled batch conditions. Parameters increasing lipopeptide production were quantified, focussing on antifungal lipopeptides (iturin and fengycin), and lipopeptide production was optimized. Experiments were performed in a fully instrumented 1.3 L bench-top bioreactor and lipopeptide analyses were performed via high pressure liquid chromatography (HPLC) and liquid chromatography-mass spectroscopy (LC-MS). After screening four Bacillus spp., Bacillus amyloliquefaciens DSM 23117 was found to be the best antifungal candidate. This was based on it outperforming other candidates in terms of maximum antifungals produced, Yp/x,antifungals (yield per cells), and antifungal productivity. Nitrate, in the form of NH4NO3, was critical for lipopeptide production and an optimum concentration was observed above which the CDW (cell dry weight) no longer increased significantly and both μmax (maximum specific growth rate, h-1) and lipopeptide production decreased. For μmax, the optimum NH3NO4 concentration was 10 g/L and for lipopeptides it was 8 g/L. At these respective NH4NO3 concentrations μmax = 0.58 (h-1), the maximum antifungals (fengycin and iturin) were 285.7 mAU*min and the maximum surfactin concentration was 302 mg/L. The lipopeptides produced by B. amyloliquefaciens, the antifungals (fengycin and iturin) and surfactin, are secondary metabolites, regardless of the optimization treatment, i.e. increased NH4NO3 concentrations. Using 30% enriched air extended the nitrate utilization period, suggesting that when increasing supply concentration, more oxygen was available to act as electron acceptors, allowing nitrate to be used for lipopeptide production. The number of iturin and fengycin homologues generally increased with an increase in nitrate concentration. This suggested that process conditions, such as nitrate concentration, can be used to manipulate homologue ratios, allowing for the possibility to tailor-make biocontrol-agent upstream, during the production process, and possibly increase the efficacy of the biocontrol strategy. The lipopeptides produced by B. amyloliquefaciens showed complete inhibition against Botryotinia fuckeliana and diminished the growth capabilities of Botrytis cinerea. No inhibition was observed against Penicillium digitatum. These results indicate potential of the biocontrol strategy, although scale-up and fed-batch studies are recommended, especially when considering commercial implementation. Studies regarding the lipopeptide application method, i.e. a single application or multiple applications, should also be investigated as this will influence the efficacy of the lipopeptides against the target organisms.
The applicability of nanofiltration for the treatment and reuse of textile reactive dye effluent
(Water Research Commission, 2015) Chollom, M. N.; Rathilal, S.; Pillay, V. L.; Alfa, Dorcas
The main aim of the study was to test the feasibility of using nanofiltration (NF) processes for the treatment of reactive dyebath effluents from the textile industry, in order to recover the water and chemicals (salts) for reuse purposes. The study of the reusability of nanofiltered water for dyeing has been given little or no attention. About 30% of reactive dyes remain unfixed on fibres; the unfixed dyes are responsible for the colouration in effluents. Membrane processes were employed to treat reactive dye-bath effluents to recover the salts and water. Investigations were conducted firstly with ultrafiltration (UF) used as a pretreatment for NF. Secondly, evaluations were performed for 2 types of NF membranes (SR90 and NF90), in terms of quality of permeate produced and fluxes achieved for 2 different samples of effluent. The effect of cleaning on membrane performance was assessed. A reusability test was carried out on both permeate samples for dyeing light and dark shade recipes. The use of UF as pre-treatment to NF resulted in rejection of colloidal substances > 90% and a 15% flux improvement. Permeate from NF90 had a conductivity of 76 µS/cm and total organic carbon (TOC) of 20 mg/ℓ, as compared to SR90 which had a conductivity of 8.3 mS/cm and a TOC of 58 mg/ℓ. Light shade from NF90 gave satisfactory results on dyeing, with no colour difference. However a variation in colour was noticed when the medium sample was used to dye the light shade. Both NF permeates gave satisfactory results when used to dye the dark shades. Permeate from NF90 was within the accepted range for reuse, while permeate from SR90 had a higher salt recovery. Chemical cleaning resulted in 80% flux recovery. From the reusability test it was concluded that permeate from NF90 met the reuse criteria for feed water to the dye bath.
The application of activated carbon for the adsorption and elution of platinum group metals from dilute cyanide leach solutions
(Southern African Institute of Mining and Metallurgy, 2013) Snyders, C. A.; Mpinga, C. N.; Bradshaw, S. M.; Akdogan, G.; Eksteen, J. J.
ENGLISH ABSTRACT: The research presented in this paper investigated the practical aspects of the recovery of platinum group metals (PGMs) from a dilute cyanide leach solution containing base metals, in a manner similar to that used for gold extraction in a typical CIP process, and focuses on both the adsorption and elution stages. The carrierphase extraction of precious metals using activated carbon offers significant advantages over other processes in terms of simplicity, the high pre-concentration factor, rapid phase separation, and relatively low capital and operating costs. As a sorbent, activated carbon is still by far the most important material because of its large surface area, high adsorption capacity, porous structure, negligible environmental toxicity, low cost, and high purity standards. Adsorption tests were conducted on a pregnant alkaline leach solution (0.15 ppm Pt, 0.38 ppm Pd, 0.1 ppm Au) resulting from cyanide extraction performed in column leach tests. The initial adsorption rates of Pt, Pd, and Au were very fast and recoveries of these three metals were approximately 90 per cent after 2 hours, and 100 per cent for Pt, 97.4 per cent for Pd, and 99.9 per cent for Au after 72 hours. The parameters that influence the extraction of PGMs and Au were examined to assess their relative importance during the adsorption process in order to provide the basis for process optimization. The concentration of thiocyanate was not identified as significant factor for PGMs adsorption, while Ni concentration was the most significant extraction process parameter. Base metal cyanide complexes adsorb and compete with the PGM complexes for sites on activated carbon, and while copper adsorption can be minimized by adjusting the residence time, Ni adsorbs at approximately the same rate as the PGMs, influencing the loading capacity and adsorption kinetics of the PGMs. The feasibility of eluting platinum and palladium cyanide complexes from activated carbon using an analogue of the AARL process was investigated. Platinum and palladium elute from activated carbon almost to completion in 4 to 5 bed volumes at 80°C, while the elution of gold at this temperature is slow, with a significant amount of gold still to be eluted after 16 bed volumes. The equilibrium loading of gold is exothermic in nature (Fleming and Nicol, 1984) which will result in an increase in gold elution kinetics with an increase in temperature at similar pre-treatment conditions. A similar result was found for the elution of Pt and Pd. Cyanide pre-treatment was found to have a significant influence on PGM elution. Higher cyanide concentration in the pre-treatment step results in more efficient elution up to a point, and results suggest the possibility of an optimum cyanide concentration, beyond which elution efficiency starts decreasing due to increased ionic strength.
Application of data analytics and knowledge-based systems in mineral processing
(Stellenbosch : Stellenbosch University, 2015-12) Aldrich, Christiaan; Burger, A. J.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.
ENGLISH ABSTRACT: This dissertation covers research carried out over the past 20 years in the area of knowledge engineering in mineral processing, specifically with regard to process data as a form of knowledge. This focus on data-driven plant automation includes the acquisition, interpretation and application of data in the development of decision support systems in mineral processing, as well as the development of data analytical methodologies required to accomplish this. The following subthemes have been covered: o Inferential sensors - predominantly the development of computer vision systems for froth flotation and the analysis of particulate systems, but also acoustic sensors and the interpretation of electrochemical noise. My research into inferential sensors has centred on the development of methodologies and algorithms to interpret image data and not the development of hardware, such as camera systems or other types of sensing devices. A major part of this pioneering research has focused on the interpretation of froth flotation images. Instead of attempting to identify individual objects (bubbles) in these images, we have treated the froth images as statistical patterns. These patterns could be interpreted by suitable feature extraction algorithms and models that could relate these features to meaningful process indicators. The novelty and impact of my research in this area can be inferred not only from the corpus of highly cited papers that associated with the technology, but also from the commercialization of the technology. o Exploratory data analysis - Focusing on unsupervised learning, such as applied in data visualization, cluster analysis and feature extraction. In exploratory data analysis, the main issue is attempting to make sense of many measurements of large sets of variables. Standard multivariate statistical methods have their limitations when dealing with complex data, and a significant part of my research has concentrated on the extension of linear methods to their nonlinear variants by use of neural networks or other machine learning approaches. Work in this area has formed the basis of a sizeable number of industrial workshops and has significantly influenced the development of commercial process systems software. o Data-based process modelling - Machine learning approaches to predictive and diagnostic modelling. The construction of process models plays a key role in process systems engineering. This is the case in advanced control systems, where the ability to predict future process states is critical. Models also play an important role in the interpretation of process data and hence the acquisition of insight into process behaviour and mechanisms. Such models can be developed from first principles, but this is costly and with the abundance of process data, often not necessary. The primary impact of this research has been in the development and application of methods to predict process states or key performance indicators for mineral processing systems. o Process monitoring and fault diagnosis - Multivariate statistical process control from a machine learning perspective. Process monitoring and fault diagnosis has evolved into a key element of process control over the last couple of decades, and is currently experiencing strong growth, with commercial application still lagging significantly behind the advances in academia. My research in this area has centred on the application of neural networks, kernel-based systems, random forests and other machine learning methods to extend current approaches. It has led to the foundation of the Anglo American Platinum Centre for Process Monitoring at Stellenbosch University and the development of algorithms that were adopted by industry on a proprietary basis. o Intelligent decision support and advanced control - Fuzzy decision support systems and neurocontrol based on the use of reinforcement learning. Apart from data that are generated by instruments, tacit knowledge in the form of plant operator experience and theoretical knowledge is also a valuable resource that can be used in the automation of plant operations. This is the domain of knowledge-based or expert systems and research was undertaken in the development and application of these systems in mineral processing. The novelty of this research has mainly been in the proof-of-concept studies published in academic journals and conference proceedings. It goes without saying that in my research, I have been assisted by many colleagues, industrial collaborators, students and assistants. The contributions of these co-workers were often critical to the investigations indicated in this thesis and are indicated as such, hopefully without omission, where appropriate.

Browse

Browsing Department of Chemical Engineering by Title

Results Per Page

Sort Options