Browsing by Author "Rawatlal, Randhir"

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    Open Access
    An approach of compartmentalisation in development of non-isothermal chemical reactor network models for the high speed simulation of iso-octane combustion
    (2011) Khan, Zamier Ahmed; Rawatlal, Randhir
    Every aspect of the modern day life relies on combustion, be it in motor vehicles, industrial equipment or power generation. The downside to the extensive use of combustion technology is the environmental pollution produced by the process. The lack of fast solving models to simulate combustion hampers the investigation into the optimisation of combustion processes. In this study, the compartment approach in developing a fast and accurate simulation is used to investigate combustion systems. A chemical reactor network (CRN) is proposed for the simulation of the combustion of iso-octane. The compartmentalisation of a combusting system involves proposing a reactor network based on the flow fields predicted by computational fluid dynamics (CFD). The first step in the development of such a model involves using of a reduced kinetic model representing thousands of combustion steps in a few elementary steps by lumping species. The reduced kinetic model used in this study consists of a five-step mechanism involving four pseudo species. The thermodynamic properties of the pseudo species in the system were regressed against experimental data and successfully validated using the plug flow and continuous stirred tank reactor sub-models. The reduced kinetic model was also further validated using Rapid Compression Machine data. The current study also modified the methodology for developing a CRN in order to make the CRN more predictive as compared to previous studies. This was achieved by incorporating non-isothermal sub-models into the network instead of isothermal sub-models that rely on the CFD temperature field. The network parameters were also correlated to the inlet Reynolds number in order to further increase the predictive nature of the network for industrial applications and to allow for the systems performance to be predicted over a wide range of input conditions. The investigation begins by conducting a CFD simulation of iso-octane combustion in a furnace and double inlet reactor assuming a one-step global reaction. On the basis of the CFD flow fields, a CRN was proposed and coupled to the reduced kinetics.
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    Open Access
    Development of a computationally efficient bubble column simulation approach by way of statistical bubble micro-flow modelling
    (2013) Coetzee, Waldo; Rawatlal, Randhir; Coetzer, Roelof LJ
    The intimate contact achieved between the gas and liquid phases in bubble columns, coupled with the inherent efficient mixing these reactors offer, yield excellent heat and mass transfer characteristics. These attributes have been exploited commercially for decades, however, due to the complexity of the underlying hydrodynamics, the prediction of bubble columns based on empirical models can be unreliable outside of the operating ranges used to fit these models. Computational Fluid Dynamics (CFD) has emerged as an attractive tool for simulating these reactors and is based on numerically approximating the fundamentally based Navier-Stokes equations on a discretized domain. The application of CFD has become more practical as the cost of computational resources has declined and has lead to the establishment of three distinct modelling approaches which have been evaluated for the purpose of bubble column simulation in a number of research papers over the past two decades. Here the Euler-Euler approach has been recommended for the simulation of large scale columns, however, this approach is based on the most assumptions and yields the least amount of flow field information. The Euler-Lagrange approach treats bubbles as discrete particles which allows for the incorporation of a deterministic bubble size distribution and the direct consideration of heat and mass transfer effects. The most fundamental approach, Direct Numerical Simulation (DNS), predicts flow properties at the bubble scale, however, is extremely computationally expensive and is therefore only practically applicable to the investigation of a very small number of bubbles. The objective of this study is to contribute to the simulation of gasliquid flow interaction occurring in bubble columns by proposing a novel technique for simulating bubble scale flow information at a significantly reduced computational expense. For this purpose, it is proposed to predict the micro-flow fields around individual bubbles, within an Euler-Lagrange framework, with an algebraic model termed the Bubble Cell Model (BCM). The high gradient regions around individual bubbles are thereby accounted for with an algebraic flow model that can be rapidly evaluated as opposed to the two-phase partial differential Navier-Stokes equations, thereby reducing the numerical complexity of the problem. Since no such flow models currently exist and accuracy and fast evaluation are imperative, a statistical approach to the construction of the BCM is justified.
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    Development of a computationally efficient model for the control of Ziegler-Natta catalysed industrial production of high density polyethylene
    (2016) McCoy, John Themba; Rawatlal, Randhir; Soares, Joao B P
    High density polyethylene is commonly produced by the slurry phase co-polymerisation of ethylene and other alkenes, using heterogeneous titanium-based Ziegler-Natta catalysts. During grade transitions, when reactor conditions are manipulated to change polymer properties, significant quantities of off-specification product result. Implementing a model-predictive controller based on a dynamic reactor model may allow for minimising losses during unsteady-state operation. Such a model must be developed from a fundamental understanding of polymerisation reaction kinetics and the interaction of effects at various scales, including those of catalyst sites, catalyst/polymer particles and reactor hydrodynamics. The model must also be computationally efficient enough for application to real-time control. The recently-developed pseudo-sites model was used as a fundamental kinetic explanation of polymer property distributions and catalyst activity profiles, in contrast to empirical multi-site models. Laboratory polymerisation experiments were performed at industrially-relevant conditions. Kinetic parameters were fitted to the data, using a novel proposed regression procedure to extract meaningful kinetic parameters. A dynamic reactor model was developed, based on the Segregation Approach. Whereas the more common Population Balance Model must consider multivariate distributions of population members within a chosen volume and requires partial differential equation solution, the Segregation Approach can generate the moments of a distribution by evaluating the evolution of properties without requiring solution over the whole volume. The Segregation Approach and PBM were rigorously compared in the context of Particle Size Distributions, and the Segregation Approach shown to be an order of magnitude more computationally efficient. Steady-state industrial data was used to reconcile model predictions for laboratory and industrial polymerisation. This was the first application of the pseudo-sites model to laboratory data, and first extension to industrial scale. Unsteady-state data from three industrial grade transitions was used to validate the reactor model, which closely matched industrial reactor performance. The model simulated 30-40 hours of real time in 15-25 seconds of calculation time. The reactor model was used to propose improved grade transition strategies; transition duration and waste production were improved by 20-40%. The reactor model has been shown to accurately reproduce real-world results, and is computationally efficient enough to be applied to model-based control applications.
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    A fundamental approach to predicting mass transfer coefficients in bubble column reactors
    (2014) Manjo, Persis Yefon; Rawatlal, Randhir
    A bubble column reactor is a vertical cylindrical vessel used for gas-liquid reactions. Bubble Columns have several applications in industry due to certain obvious advantages such as high gas-liquid interfacial area, high heat and mass transfer rates, low maintenance requirements and operating costs. On the other hand, attempts at modelling and simulation are complicated by lack of understanding of hydrodynamics and mass transfer characteristics. This complicates design scale-up and industrial usage. Many studies and models have attempted to evolve understanding of the hydrodynamic complexity in Bubble Columns reactors. A closer look at these studies and models reveals a variety of solution methods for different systems (Frössling, 1938; Clift et al., 1978; Hughmark, 1967; Dutta, 2007; Ranz and Marshall, 1952; Benitez, 2009; Buwa et al., 2006; Suzzia et al., 2009; Wylock et al., 2011). Numerous correlations (Frössling, 1938; Clift et al., 1978; Hughmark, 1967; Dutta, 2007; Ranz and Marshall, 1952; Benitez, 2009; Buwa et al., 2006) exist but to date in literature, there is no general approach to determining accurate estimates of average mass transfer coefficient values. Good estimates of the average mass transfer coefficient will improve the predictive capacity of the associated models. Recent attempts at modelling micro-scale bubble-fluid interaction resulted in the Bubble Cell Model, BCM, (Coetzee et al., 2009) which simulates the velocity vector field around a single gas bubble in a flowing fluid stream using a Semi-Analytical model. The aim of the present study is to extend the BCM applications by integrating the mass balance into the framework to predict the average mass transfer coefficient in bubble columns. A nitrogen-water steady state system was simulated in an axisymmetric grid where mass transfer occurs between the gas and liquid.
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    Hybridization of electrical resistance tomography to population balance model for accurate bubble column reactor hydrodynamic parameter predictions
    (2016) Adetunji, Olubode Caleb; Rawatlal, Randhir; Adler, Andy; Mainza, Aubrey
    A novel approach of obtaining bubble size and spatial distribution is developed by hybridising techniques of Electrical Resistance Tomography and the Gas Disengagement Technique using a Population Balance as a framework. As a result, detailed hydrodynamic predictions suitable for Bubble Column Reactor [BER] optimisation results with minimal computing effort. Electrical Resistance Tomography [ERT] is a technique for creating 3D images of objects occurring in space. The images are obtained through current stimulations through a body surface electrodes and measurements of resulting voltage signals due to interior spatial conductivity field distribution. The use of ERT imaging method for hydrodynamic parameter predictions in a BCR has a benefit of yielding high temporal resolution but low spatial resolution. The low spatial resolution in electrical imaging accounts for underestimated or overestimated hydrodynamic parameter predictions similar to results obtained from the use of alternative techniques. The population balance model [PBM] is a mathematical framework with which the spatial transport of properties of bubble population can be described. The PBM also allows for the description of the time-variant bubble population properties by a division of bubble population into size classes. Moreover, the PBM allows for the inclusion of models of bubble coalescence and breakage phenomena, which affect the distribution of bubble population properties during bubble swarming. The included source terms enable accurate modelling of the bubble evolution either in a steady or unsteady state fluid flow regime. The objective of the present study is to develop an ERT interpretation technique yielding a high accuracy reconstruction of bubble population distribution through coupling ERT measurements to a PBM. It is hypothesized that a higher accuracy interpretation of ERT measurements will result from coupling ERT measurements to a PBM. The ERT technique has the capacity to image the steady and time-dependent gas void fractions in column sections as bubbles swarm and during dynamic gas disengagement [DGD]. This ERT potential is explored in hybridizing ERT and a PBM in the present work.
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    The influence of heat transfer limitations on the properties of PET yarn produced by melt spinning
    (2008) Kotze, Tyrone; Rawatlal, Randhir
    The production of synthetic yarns requires a cost efficient process whilst simultaneously incorporating process methods which ultimately lead to a high quality fibre. A critical part of the production process is the spinning of the molten polymer into individual filaments which are brought together to form the filament bundle. During this process a quench air stream is blown across the filament bundle to aid in cooling the molten polymer. Here, heat transfer limitations may cause inter-filament property variations, which will adversely affect the quality of the yarn. This thesis focuses on the development of a model which allows for an a priori prediction of the influence of major process variables on the degree of fibre property uniformity. Fibre quality is characterised by the high degree of uniformity in the properties which affect the structural features of the yarn. Yarn morphology is dictated by the degree of crystallinity and molecular alignment of the polymer macro-molecules parallel to the fibre axis. These properties are strongly influenced by online tensile stress and local temperature which are, in turn, affected by heat transfer effects between the quench air and filament surface. A model that predicts the influence of heat transfer limitations on the uniformity of the as-spun fibre is therefore needed. Previous research in this field is limited with most work focussed on single filament model development. In this investigation, a monofilament model developed by previous workers (Jarecki et al., 2000) is integrated into a multifilament framework. This model assumes Newtonian behaviour of the polymer with viscosity strongly dependent on local temperature and crystallinity. The development of the multifilament model involves dividing the spinning zone into a number of cells, in which the filament properties are modelled using the monofilament model. The change in quench air temperature is estimated by means of an energy balance incorporating air flow terms and heat transfer through forced convection from the filament surface. A novel iteration approach is proposed in which the temperature of the quench air exiting each cell is iterated for until convergence is met. In simplifying the model, it was found that uniform quench air flow profile could be assumed, since the quench flow channel length was found to fall far short of the length required for turbulent flow to develop. However, it is known that increased contact time for heat transfer would occur if air were dragged down with the filament. Although modelling this effect is beyond the scope of the project, the heat transfer gradients are worsened by air-dragging and hence the model presented in this thesis reveals whether polymer uniformity is possible even under the best possible flow patterns. A negative result therefore indicates that non-uniformity will definitely occur.
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    An investigation into the minimum dimensionality required for accurate simulation of proton exchange membrane fuel cells by the comparison between 1- and 3-dimension models.
    (2013) Shekhar, Karthik; Rawatlal, Randhir; Conrad, Olaf
    Hydrogen has been studied intensively as a potential energy carrier as it allows for a reduced carbon footprint in the environment. Fuel cell (FC) technology has been studied in detail to implement hydrogen as well as other renewable sources as a feasible fuel. Further development in fuel cell design is hampered by the lack of fundamental models which reveal the physical and chemical interactions. While computational fluid dynamics simulations are available, the timeframe for solving these simulations renders them unfeasible in any rigorous FC design optimisation. The objective of the present investigation was to determine the minimum dimension of a mathematical model that can accurately simulate processes occurring within a proton exchange membrane fuel cell (PEMFC). To this end, 1-D (directional axis perpendicular to the membrane) and 3-D steady state isothermal mathematical models were developed and simulated in order to investigate the transport of reactant species through the various layers of the cell at the anode side.
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    Investigation of polymer grade blending in Ziegler-Natta Catalysed ethylene polymerisation systems
    (2014) Nacerodien, Mogamat Thaabit; Rawatlal, Randhir
    Polyethylene is one of the most widely used polymers to date and it is an important commodity in a variety of fields. Most existing polyethylene plants operate on technology involving heterogeneous Ziegler-Natta catalysts. Plants often change operating conditions to produce different polymer grades; this allows them to cater to a larger polymer market. A side-effect of this practice is the unwanted formation of off-spec polymer during the grade transition periods. Numerous studies have been conducted to address the issue of off-spec polymer formation. These studies involve applying optimal control theory to minimise the grade transition time or to minimise the amount of off-spec polymer generated during the transient period. This field of study is known as grade transition optimisation. The current study aims to provide an alternative approach to addressing the problem of offspec accumulation. It is proposed that stored off-spec polymer is blended with virgin polymer to provide a saleable and desirable product. The approach might be different, but the same techniques used in grade transition optimisation are applied. Polyethylene produced using Ziegler-Natta catalysts have relatively linear chains, thus a chain length distribution coefficient is sufficient to characterise the polymer product. The number average chain length and polydispersity index are adequate representatives of this distribution for reporting the properties of a polyethylene grade. For the purpose of applying optimal control theory, a polyethylene production process model was developed to calculate these average properties using a kinetic scheme based on fundamental principles. This process model is able to predict the polymer properties under both steady-state and unsteady-state behaviour. A key feature of the model is its ability to solve the system with low computational expense due to the use of the segregation approach to link particle properties to the overall bulk phase. This is especially useful since optimisation algorithms used in optimal control theory are iterative by nature. The Differential Evolution Algorithm (DEA) was used to minimise the objective functions that were developed for the optimisation schemes due to its ability to evaluate objective functions in parallel. A model of the blending aspect of the process was developed where it was derived that the polymer moments are additive on a mass basis. Pure grades were blended in a laboratory in various mass ratios and analysed using GPC to determine their molecular weight distribution curves. It was found that the model-predicted curves and the experimentally-determined curves were an excellent match, thus validating the model. In the current study, three procedures for blending off-spec material under standard industry conditions are proposed. The first method involves the introduction of off-spec polymer on a continuous basis to the virgin polymer stream during steady-state operation.
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    Microbial oxidation of dodecane and tridecane into a,w-dicarboxylic acids using recombinant Yarrowia lipolytica
    (2007) Diedericks, Danie; Harrison, STL; Smit, Martie; Rawatlal, Randhir
    a,w-Dicarboxylic acids are reactive intermediates, widely used as raw materials to synthesise products such as perfumes, hot-melting adhesives, engineering plastics and high quality lubricants. These acids can be obtained via chemical or biological routes by using various feedstocks such as linear alkanes. Linear alkanes are chemically inert; hence, the production of reactive products requires complex and sophisticated reactions catalysed by either catalysts or enzymes. However, simultaneous by-product formation on chemical synthesis increases production cost and limits commercial availability, preventing their widespread application. Biological routes alternatively, selectively transform linear alkanes into fatty and a,w-dicarboxylic acids. Linear alkanes, due to their relative abundance and increased availability, following the expansion of gas-to-liquid fuels technology, are viewed as prospective feedstocks for the microbial production of a,w-dicarboxylic acids. The commercialisation of the biological conversion of linear alkanes is constrained by the low turnover frequency of the cytochrome P450 hydroxylase complex responsible for catalysing the first and rate limiting step of the monoterminal and diterminal pathways. Low product yields may be caused by the further catabolism of a,w-dicarboxylic acids, through the ~-oxidation pathway into energy, carbon dioxide and water. To prevent this, metabolic engineering techniques can be applied to prevent ~-oxidation by disrupting the genes encoding the enzyme catalysing the first step in the~-oxidation pathway. The specific productivity of bioconversion can then be increased further by over-expressing the genes encoding the cytochrome P450 hydroxylase complex. Recombinant Yarrowia lipolytica strains TVN 497, TVN 499, TVN 501 and TVN 502 were developed in such a manner by the collaborating research group at the University of the Free State and made available for this research.
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    Modelling the flow behaviour of gas bubbles in a bubble column
    (2009) McMahon, Andrew Martin; Rawatlal, Randhir; Harrison, STL; Chinyoka, Tiri
    The bubble column reactor is commonly used in industry, although the fluid dynamics inside are not well understood. The challenges associated with solving multi phase flow problems arise from the complexity of the governing equations which have to be solved, which are typically mass, momentum and energy balances. These time-dependent problems need to include effects of turbulence and are computationally expensive when simulating the hydrodynamics of large bubble columns. In an attempt to reduce the computational expense in solving bubble column reactor models, a "cell" model is proposed which predicts the velocity flow field in the vicinity of a single spherical bubble. It is intended that this model would form the fundamental building block in a macroscale model framework that does predict the flow of multiple bubbles in the whole column. The non-linear Navier-Stokes (NVS) equations are used to model fluid flow around the bubble. This study focusses on the Reynolds number range where the linear Stokes equations can be used to accurately predict the flow around the bubble. The Stokes equations are mathematically easier to solve than the NVS equations and are thus less computationally expensive. The validity of the NVS model was tested against experimental data for the flow of water around a solid sphere and was found to be in close agreement for the Reynolds number range 25 to 80. The simulation results from the Stokes flow model were compared with those from the NVS flow model and were similar at Reynolds numbers below 1. The application is then in the partitioning of the bubble column into regions governed by either Stokes or NVS equations.
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    Numerical simulation of bubble columns by integration of bubble cell model into the population balance framework
    (2014) Khama, Mopeli; Rawatlal, Randhir
    Bubble column reactors are widely used in the chemicals industry including pharmaceuticals, waste water treatment, flotation etc. The reason for their wide application can be attributed to the excellent rates of heat and mass transfer that are achieved between the dispersed and continuous phases in such reactors. Although these types of contactors possess the properties that make them attractive for many applications, there still remain significant challenges pertaining to their design, scale-up and optimization. These challenges are due to the hydrodynamics being complex to simulate. In most cases the current models fail to capture the dynamic features of a multiphase flow. In addition, since most of the developed models are empirical, and thus beyond the operating conditions in which they were developed, their accuracy can no longer be retained. As a result there is a necessity to develop eneric models which can predict hydrodynamics, heat and mass transfer over a wide range of operating conditions. With regard to simulating these systems, Computational Fluid Dynamics (CFD) has been used in various studies to predict mass and heat transfer characteristics, velocity gradients etc (Martín et al., 2009; Guha et al., 2008; Olmos et al., 2001; Sanyal et al., 1999; Sokolichin et al., 1997).The efficient means for solving CFD are needed to allow for investigation of more complex systems. In addition, most models report constant bubble particle size which is a limitation as this can only be applicable in the homogenous flow regime where there is no complex interaction between the continuous and dispersed phase (Krishna et al., 2000; Sokolichin & Eigenberger., 1994). The efficient means for solving CFD intimated above is addressed in the current study by using Bubble Cell Model (BCM). BCM is an algebraic model that predicts velocity, concentration and thermal gradients in the vicinity of a single bubble and is a computationally efficient approach The objective of this study is to integrate the BCM into the Population Balance Model (PBM) framework and thus predict overall mass transfer rate, overall intrinsic heat transfer coefficient, bubble size distribution and overall gas hold-up. The experimental determination of heat transfer coefficient is normally a difficult task, and in the current study the mass transfer results were used to predict heat transfer coefficient by applying the analogy that exists between heat and mass transfer. In applying the analogy, the need to determine the heat transfer coefficient experimentally or numerically was obviated. The findings indicate that at the BCM Renumbers (Max Re= 270), there is less bubble-bubble and eddy-bubble interactions and thus there is no difference between the inlet and final size distributions. However upon increasing Re number to higher values, there is a pronounced difference between the inlet and final size distributions and therefore it is important to extend BCM to higher Re numbers. The integration of BCM into the PBM framework was validated against experimental correlations reported in the literature. In the model validation, the predicted parameters showed a close agreement to the correlations with overall gas hold-up having an error of ±0.6 %, interfacial area ±3.36 % and heat transfer coefficient ±15.4 %. A speed test was also performed to evaluate whether the current model is quicker as compared to other models. Using MATLAB 2011, it took 15.82 seconds for the current model to predict the parameters of interest by integration of BCM into the PBM framework. When using the same grid points in CFD to get the converged numerical solutions for the prediction of mass transfer coefficient, the computational time was found to be 1.46 minutes. It is now possible to predict the intrinsic mass transfer coefficient using this method and the added advantage is that it allows for the decoupling of mass transfer mechanisms, thus allowing for more detailed designs.The decoupling of mass transfer mechanisms in this context refers to the separate determination of the intrinsic mass transfer coefficient and interfacial area.