M A Baseer, 2017 "Wind resource assessment and GIS-based site selection methodology for efficient wind power deployment"
An enormous and urgent energy demand is predicted due to the growing global population, increase in power intensive industries, higher living standards, electrification of remote areas, and globalisation (transportation). Moreover, the global consciousness about the harmful effects of traditional methods of power generation on the environment. That, in turn, has created a need to strategically plan and develop renewable and sustainable energy generation systems. This study presents a wind resource assessment of seven locations proximate to the largest industrial hub in the Middle East, Jubail Industrial City, Kingdom of Saudi Arabia, and a Geographic Information System, GIS based model considering a multi-criteria wind farm site suitability approach for the entire Kingdom of Saudi Arabia and elsewhere.
The hourly mean wind speed data at 10, 50 and 90 m above the ground level (AGL) over a period of five years was used for a meteorological station at the Industrial Area (Central) of Jubail. At the remaining six sites, the meteorological data were recorded at 10 m AGL only. Five years of wind data were used for five sites and three years of data were available for the remaining one site. At the Industrial Area (East), the mean wind speeds were found to be 3.34, 4.79 and 5.35 m/s at 10, 50 and 90 m AGL, respectively. At 50 and 90 m AGL, the availability of wind speed above 3.5 m/s was more than 75%. The local wind shear exponent, calculated using measured wind speed values at three heights, was found to be 0.217. The mean wind power density values at measurement heights were 50.92, 116.03 and 168.46 W/m2, respectively. After the assessment and comparison of wind characteristics of all seven sites, the highest annual mean wind speed of 4.52 m/s was observed at Industrial Area (East) and the lowest of 2.52 m/s at the Pearl Beach with standard deviations of 2.52 and 1.1 m/s, respectively.
In general, at all sites, the highest monthly mean wind speed was observed in February/June and the lowest in September/October. The period of higher wind availability coincides with a high power demand period in the region attributable to the air conditioning load. The wind rose plots show that the prevailing wind direction for all sites was from the north-west. Weibull parameters for all sites were estimated using maximum likelihood, least-squares regression method (LSRM), and WAsP algorithm. In general, at all sites, the Weibull parameter, c, was the highest in the months of February/June and the lowest in the month of October. The most probable and maximum energy carrying wind speed was determined by all three methods. The highest value of most probable wind speed was found to be in the range of 3.2 m/s to 3.6 m/s at Industrial Area (East) and the highest value of maximum energy carrying wind speed was found to be in the range 8.6 m/s to 9.0 m/s at Industrial Area 2 (South) by three estimation methods. The correlation coefficient (R2), root mean square error (RMSE), mean bias error (MBE), and mean bias absolute error (MAE) showed that all three methods represent wind data at all sites accurately. However, the maximum likelihood method is slightly better than LSRM, followed by WAsP algorithm. The wind power output at all seven sites, from five commercially available wind turbines of rated power ranging from 1.8 to 3.3 MW, showed that Industrial Area (East) is most promising for wind farm development. At all sites, based on percentage plant capacity factor, PCF, the 1.8 MW wind turbine was found to be the most efficient. At Industrial Area (East), this wind turbine was found to have a maximum PCF of 41.8%, producing 6,589 MWh/year energy output. The second best wind turbine was 3 MW at all locations except the Al-Bahar Desalination Plant and Pearl Beach. At both of these locations, 3.3 MW was the next best option. The energy output from the 3 MW wind turbine at Industrial Area (East) was found to be 11,136 MWh/year with a PCF of 41.3%. The maximum duration of rated power output from all selected wind turbines was observed to be between 8 to 16.6% at Industrial Area 2 (South). The minimum duration of rated power output, less than 0.3% for all wind turbines, was observed at Pearl Beach. The maximum duration of zero power output of between 35 to 60% was also observed at Pearl Beach. The minimum duration of zero power output of between 12 to 23% was obtained in Industrial Area (East). Even though the 1.8 MW wind turbine is found to be most efficient, installation of a higher rated power wind turbine such as the 3 MW is a smart option as it would occupy less of the scarce land in the Industrial City. The cost of electricity, COE per kWh was estimated at each of the seven locations in Jubail, based on present value cost, PVC method for five selected wind turbines, and annual power output at these locations. The minimum cost of 0.023 US$ per kWh is obtained for Industrial Area (East) for the wind turbine of capacity 2,000 kW.
This study also presents a multi-criteria wind farm site suitability analysis by developing a model based on a geographic information system (GIS). The site suitability analysis considered different parameters, such as climatic, economic, aesthetic and environmental conditions, and formulated a criterion based on wind resource, accessibility by roads/highways, proximity to the electrical grid, and optimum/safe distance from various settlements and airports. The developed model was then applied to the entire Kingdom of Saudi Arabia by using long-term historical wind speed data from 29 meteorological stations across the country. The wind speed used in the criterion was interpolated to 100 m from 10 m AGL by using traditional one-seventh power law. To predict the wind speed in locations for which data are not available, a spatial interpolation technique, inverse distance weighted, was used to convert wind speed point data to raster structure. The data and GIS shape files of other criteria mentioned above were obtained from governmental organisations. The GIS shape files for roads and highways were merged as identical constraints were applied to both criteria. Subsequently, the data of all the criteria were reclassified into suitability scores. Two different modelling approaches were adopted, one in which equal weightage was given to all the components of the criteria, and the other in which different weightage selected based on the literature, were given to the different components of the criteria of site selection. The resulting suitability maps were distributed into six classes, from the most suitable to least suitable. In the suitability map, based on Method 1, 1.03% of the total classed area fell under the most suitable wind farm area, whereas in Method 2, the percentage was 1.86%. The percentages of the next best areas were 29.13% and 14.65% in the maps based on Method 1 and 2, respectively.
The wind farm site suitability indexed map reveals that the most suitable sites for wind farms are (i) Ras Tanura and Safwa along the Arabian Gulf coast in the Eastern Province, (ii) Turaif, Kaf and Al-Isawiyah in the Al-Jawf region along the northern borders, and (iii) Al-Wajh and Yanbu along the Red Sea coast in the western region. These three regions are windy, adequately populated, and well connected by roads/highways and the national electricity grid. Some central and south-eastern regions failed to qualify to be considered for wind farm development mainly because of scarce wind resources, low population, and poor connectivity by roads and electrical grid.
Supervisor:Prof JP Meyer
Co-Supervisors:Dr. S. Rehman, Dr. M.M. Alam
M. Moghimi Ardekani, 2017 "OPTICAL, THERMAL AND ECONOMIC OPTIMISATION OF A LINEAR FRESNEL COLLECTOR"
Solar energy is one of a very few low-carbon energy technologies with the enormous potential to grow to a large scale. Currently, solar power is generated via the photovoltaic (PV) and concentrating solar power (CSP) technologies. The ability of CSPs to scale up renewable energy at the utility level, as well as to store energy for electrical power generation even under circumstances when the sun is not available (after sunset or on a cloudy day), makes this technology an attractive option for sustainable clean energy. The levelised electricity cost (LEC) of CSP with thermal storage was about 0.16-0.196 Euro/kWh in 2013 (Kost et al., 2013). However, lowering LEC and harvesting more solar energy from CSPs in future motivate researchers to work harder towards the optimisation of such plants. The situation tempts people and governments to invest more in this ultimate clean source of energy while shifting the energy consumption statistics of their societies from fossil fuels to solar energy.
Usually, researchers just concentrate on the optimisation of technical aspects of CSP plants (thermal and/or optical optimisation). However, the technical optimisation of a plant while disregarding economic goals cannot produce a fruitful design and in some cases may lead to an increase in the expenses of the plant, which could result in an increase in the generated electrical power price.
The study focused on a comprehensive optimisation of one of the main CSP technology types, the linear Fresnel collector (LFC). In the study, the entire LFC solar domain was considered in an optimisation process to maximise the harvested solar heat flux throughout an imaginary summer day (optical goal), and to minimise cavity receiver heat losses (thermal goal) as well as minimising the manufacturing cost of the plant (economic goal). To illustrate the optimisation process, an LFC was considered with 12 design parameters influencing three objectives, and a unique combination of the parameters was found, which optimised the performance. In this regard, different engineering tools and approaches were introduced in the study, e.g., for the calculation of thermal goals, Computational Fluid Dynamics (CFD) and view area approaches were suggested, and for tackling optical goals, CFD and Monte-Carlo based ray-tracing approaches were introduced. The applicability of the introduced methods for the optimisation process was discussed through case study simulations. The study showed that for the intensive optimisation process of an LFC plant, using the Monte Carlo-based ray-tracing as high fidelity approach for the optical optimisation objective, and view area as a low fidelity approach for the thermal optimisation objective, made more sense due to the saving in computational cost without sacrificing accuracy, in comparison with other combinations of the suggested approaches.
The study approaches can be developed for the optimisation of other CSP technologies after some modification and manipulation. The techniques provide alternative options for future researchers to choose the best approach in tackling the optimisation of a CSP plant regarding the nature of optimisation, computational cost and accuracy of the process.
Supervisor:Prof. KJ Craig
C0-Supervisor:Prof JP Meyer
M. Mahdavi, 2017 "Study of flow and heat transfer features of nanofluids by CFD models: Eulerian multiphase and discrete Lagrangian approaches"
Choosing correct boundary conditions, flow field characteristics and employing right thermal fluid properties can affect the simulation of convection heat transfer using nanofluids. Nanofluids have shown higher heat transfer performance in comparison with conventional heat transfer fluids. The suspension of the nanoparticles in nanofluids creates a larger interaction surface to the volume ratio. Therefore, they can be distributed uniformly to bring about the most effective enhancement of heat transfer without causing a considerable pressure drop. These advantages introduce nanofluids as a desirable heat transfer fluid in the cooling and heating industries. The thermal effects of nanofluids in both forced and free convection flows have interested researchers to a great extent in the last decade.
Investigating the interaction mechanisms happening between nanoparticles and base fluid is the main goal of the study. These mechanisms can be explained via different approaches through some theoretical and numerical methods. Two common approaches regarding particle-fluid interactions are Eulerian-Eulerian and Eulerian-Lagrangian. The dominant conceptions in each of them are slip velocity and interaction forces respectively. The mixture multiphase model as part of the Eulerian-Eulerian approach deals with slip mechanisms and somehow mass diffusion from the nanoparticle phase to the fluid phase. The slip velocity can be induced by a pressure gradient, buoyancy, virtual mass, attraction and repulsion between particles. Some of the diffusion processes can be caused by the gradient of temperature and concentration.
The discrete phase model (DPM) is a part of the Eulerian-Lagrangian approach. The interactions between solid and liquid phase were presented as forces such as drag, pressure gradient force, virtual mass force, gravity, electrostatic forces, thermophoretic and Brownian forces. The energy transfer from particle to continuous phase can be introduced through both convective and conduction terms on the surface of the particles.
A study of both approaches was conducted in the case of laminar and turbulent forced convections as well as cavity flow natural convection. The cases included horizontal and vertical pipes and a rectangular cavity. An experimental study was conducted for cavity flow to be compared with the simulation results. The results of the forced convections were evaluated with data from literature. Alumina and zinc oxide nanoparticles with different sizes were used in cavity experiments and the same for simulations. All the equations, slip mechanisms and forces were implemented in ANSYS-Fluent through some user-defined functions.
The comparison showed good agreement between experiments and numerical results. Nusselt number and pressure drops were the heat transfer and flow features of nanofluid and were found in the ranges of the accuracy of experimental measurements. The findings of the two approaches were somehow different, especially regarding the concentration distribution. The mixture model provided more uniform distribution in the domain than the DPM. Due to the Lagrangian frame of the DPM, the simulation time of this model was much longer. The method proposed in this research could also be a useful tool for other areas of particulate systems.
Supervisor:Prof. Mohsen Sharifpur
Supervisor:Prof JP Meyer
J. Baloyi, 2017 "Thermodynamic Analysis of a Circulating Fluidised Bed Combustor"
The focus of the world is on the reduction of greenhouse gases, such as carbon dioxide, which contribute to the global warming currently experienced. Because most of the carbon dioxide emitted into the atmosphere is from fossil fuel combustion, alternative energy sources were developed and others are currently under study to see whether they will be good alternatives. One of these alternative sources of energy is the combustion of wood instead of coal. The advantages of wood are that it is a neutral carbon fuel source and that currently installed infrastructure used to combust coal can be retrofitted to combust wood or a mixture of wood and coal in an attempt to reduce the carbon dioxide emissions.
Spent nuclear fuel has to be cooled so that the decay heat generated does not melt the containment system, which could lead to the unintentional release of radioactive material to the surroundings. The heat transfer mechanisms involved in the cooling have historically been analysed by assuming that the fluid and solid phases are at local thermal equilibrium (LTE) in order to simplify the analysis.
The exergy destruction of the combustion of pine wood in an adiabatic combustor was investigated in this thesis using analytical and computational methods. The exergy destruction of the combustion process was analysed by means of the second law efficiency, which is the ratio of the maximum work that can be achieved by a Carnot engine extracting heat from the combustor, and the optimum work of the combustor. This was done for theoretical air combustion and various excess air combustions, with varied inlet temperatures of the incoming air. It was found that the second law efficiency reached an expected maximum for theoretical air combustion, and this held true for all varying air inlet temperatures. However, it was found that as the air inlet temperature was increased more and more, the maximum second law efficiency was the same for all excess air combustions, including the theoretical air combustion. It was also found that the results of the analytical and commercial computational fluid dynamics code compared well.
Another analysis was conducted of irreversibilities generated due to combustion in an adiabatic combustor burning wood. This was done for a reactant mixture varying from a rich to a lean mixture. A non-adiabatic non-premixed combustion model of a numerical code was used to simulate the combustion process where the solid fuel was modelled by using the ultimate analysis data. The entropy generation rates due to the combustion and frictional pressure drop processes were computed to eventually arrive at the irreversibilities generated. It was found that the entropy generation rate due to frictional pressure drop was negligible when compared with that due to combustion. It was also found that a minimum in irreversibilities generated was achieved when the air-fuel mass ratio was 4.9, which corresponded to an equivalent ratio of 1.64, which was lower than the respective air-fuel mass ratio and equivalent ratio for complete combustion with theoretical
Supervisor:Prof T Bello-Ochende
Supervisor:Prof JP Meyer
D H Diamond, 2017 "A Probabilistic Approach to Blade Tip Timing Data Processing"
Rotor blades are important structural components of axial flow turbomachinery. They experience immense loads and stresses due to harsh operating conditions. Rotor blade resonance occurs when the frequency of aerodynamic excitation coincides with a rotor blade’s natural frequency, leading to harmful blade vibrations. It is imperative to ensure the integrity of the rotor blades while at the same time reducing unnecessary maintenance outages. Blade Tip Timing (BTT) is a non-intrusive technique for measuring individual rotor blade vibration that can be used for condition monitoring. The technique uses stationary proximity sensors mounted circumferentially around the rotor casing to measure blade vibration. BTT data is, however, notoriously difficult to process. Rotor torsional vibration, limitations in data acquisition hardware, high levels of inherent noise and a limited number of proximity sensors are all factors that complicate BTT data analysis. These difficulties are impeding the widespread adoption of BTT. This thesis presents a new approach to BTT data processing. The overarching novelty in this work lies in the fact that several aspects of BTT data processing are performed probabilistically. This stands in stark contrast to the current state-of-the art processing methods, which are deterministic in nature. Four novel signal processing techniques using a probabilistic approach are derived and validated in this thesis. Several important needs are identified in the current BTT literature and novel probabilistic algorithms are derived which address those needs. The four algorithms focus on different aspects of BTT signal processing. Firstly, a novel algorithm is derived that can be used to compensate for the geometry of an incremental shaft encoder for signals acquired during arbitrary shaft speeds. Secondly, an algorithm is derived to calculate the blade tip deflection based on the shaft Instantaneous Angular Speed (IAS) as opposed to a constant speed assumption, and then to instantaneously determine if the rotor blades are experiencing resonance. Thirdly, a novel technique is developed to determine the blade tip deflection from the raw proximity sensor signals using local phase information in the signal, as opposed to conventional triggering criteria. Finally, a method is derived to calculate a rotor blade’s accumulated fatigue damage as a probability distribution from BTT data. All four algorithms are validated using laboratory and/or simulated experiments.
Supervisor: Prof. P S Heyns
Co-supervisor: Dr. A J Oberholster
O.O. Adewumi,2016 "Constructal design and optimisation of combined microchannels and micro-pin fins for microelectronic cooling"
Microchannels and micro pin fins have been employed for almost four decades in the cooling of microelectronic devices and research is still being done in this field to improve the thermal performance of these micro heat sinks. In this research, the constructal design and computational fluid dynamics code was used with a goal-driven optimisation tool to numerically investigate the thermal performance of a novel design of combining microchannels and micro pin fins for microelectronic cooling applications. Existing designs of microchannels were first optimised and thereafter, three to seven rows of micro pin fins were inserted into the microchannels to investigate whether there was further improvement in thermal performance. The microchannels and micro pin fins were both embedded in a highly conductive solid substrate.
The three-dimensional geometric structure of the combined micro heat sink was optimised to achieve the objective of maximised thermal conductance, which is also minimised thermal resistance under various design conditions. The micro heat sinks investigated in the study were the single microchannel, two-layered microchannels with parallel and counter flow configurations, three-layered microchannels with parallel and counter flow configurations, the single microchannel with circular-, square- and hexagonal-shaped micro pin-fin inserts and the two-layered microchannels with circular-shaped micro pin-fin inserts. A numerical computational fluid dynamics (CFD) package with a goal-driven optimisation tool, which employs the finite-volume method, was used to analyse the fluid flow and heat transfer in the micro heat sinks investigated in this work. The thermal performances of all the micro heat sinks were compared for different application scenarios.
Furthermore, the temperature variation on the heated base of the solid substrate was studied for the different micro heat sinks to investigate which of the heat sink designs minimised the temperature rise on the heated base best. This is very important in microelectronic cooling applications because temperature rise affects the reliability of the device. The heat sink design that best maximised thermal conductance and minimised temperature rise on the heated base was chosen as the best for microelectronic cooling. For all the cases considered, fixed volume constraints and manufacturing constraints were applied to ensure real-life applicability. It was concluded that optimal heat sink design for different application scenarios could be obtained speedily when a CFD package which had an optimisation tool was used.
Keywords: Microchannels, micro pin fins, computational fluid dynamics, goal-driven optimisation, heat transfer, fluid flow, constraints, optimal heat sink, thermal conductance, thermal resistance, constructal theory, temperature variation
Supervisor: Prof. T. Bello-Ochende
Co-Supervisor: Prof. J.Meyer
M. L. Combrinck,2016 "BOUNDARY LAYER RESPONSE TO ARBITRARY ACCELERATING FLOW"
This thesis was aimed developing a fundamental understanding of the boundary layer response to arbitrary motion. In this context arbitrary motion was defined as the unsteady translation and rotation of an object.
Research objectives were developed from the gaps in knowledge as defined during the literature survey. The objectives were divided into three main activities; mathematical formulations for non-inertial bulk flow and boundary layer equations, implementation of said formulations in a numerical solver and simulations for various applications in arbitrary motion.
Mathematical formulations were developed for the bulk flow and boundary layer equations in arbitrary motion. It was shown that the conservation of momentum and energy equation remains invariant in the non-inertial forms. The conservations of momentum equation can at most have six fictitious terms for unsteady arbitrary motion. The origins of the terms were found to be from transformation of the material derivative to the non-inertial frame. All fictitious terms were found to be present in the boundary layer equations; none could be eliminated during an order of magnitude analysis.
The vector forms of the non-inertial equations were implemented in a novel OpenFOAM solver. The non-inertial solver requires prescribed motion input and operate on a stationary mesh. Validation of the solver was done using analytical solutions of a steady, laminar flat plate and rotating disk respectively.
Numerical simulations were done for laminar flow on a translating plate, rotating disk and rotating cone in axial flow. A test matrix was executed to investigated various cases of acceleration and deceleration over a range of 70 g to 700 000g. The boundary layer profiles, boundary layer parameters and skin friction coefficients were reported.
Three types of boundary layer responses to arbitrary motion were defined. Response Type I is viscous dominant and mimics the steady state velocity profile. In Response Type II certain regions of the boundary layer are dominated by viscosity and others by momentum. Response Type III is dominated by momentum. In acceleration the near-wall velocity gradient increases with increasing acceleration. In deceleration separation occurs at a result of momentum changes in the flow.
The mechanism that causes these responses has been identified using the developed boundary layer equations. In acceleration the relative frame fictitious terms become a momentum source which results in an increase in velocity gradient at the wall.
In deceleration the relative frame fictitious terms become a momentum sink that induced an adverse pressure gradient and subsequently laminar separation.
Keywords:Non-Inertial Reference Frames, Fictitious Forces, Boundary Layer Equations, OpenFOAM, Laminar Flat Plate, Laminar Rotating Disk, Rotating Cone in Axial Flow.
Supervisor: Prof. L.N. Dala
Chabala Lloyd Ngo, 2016 "NATURAL CONVECTION AND RADIATION HEAT LOSS IN SOLAR CAVITY RECEIVERS – NUMERICAL MODELLING, PERFORMANCE ENHANCEMENT AND OPTIMISATION"
Energy access is increasingly seen as a vital catalyst to wider social and economic development, which enables education, health and sustainable agriculture, and creates jobs. Therefore, sustainable growth and development in society needs energy supply that is readily available, affordable, renewable and efficient without causing many negative societal impacts, such as environmental pollution and its consequences. In this regard, concentrating solar power technology has great potential to be used for energy production and it is a promising alternative to conventional fossil fuel-based energy technologies, such as coal power plants, due to the abundance of solar energy as an energy resource, as well as its minimal impact on the environment. The parabolic dish receiver assembly is one such promising concentrating solar power technology. It usually consists of a reflector in the form of a dish with a downward-facing receiver at the focus of the dish. A cavity receiver is used to maximise the absorption of the concentrated flux. However, the receiver is subjected to environmental variations, as well as changes in receiver inclination angle, which lead to heat losses that affect the overall receiver’s performance.
The need for the commercialisation of economically viable parabolic dish systems necessitates further in-depth investigation into cavity receiver designs. As the cavity receiver plays a critical role in transferring solar heat to the engine, any heat loss from the cavity receiver can significantly reduce the efficiency and, consequently, the system’s cost effectiveness. It is therefore essential to assess and effectively minimise heat loss in the cavity receiver to improve the thermal performance of the system, which can contribute to the commercialisation of this type of technology.
This research focused on the modified cavity receivers that are employed in medium- and high-temperature solar dish systems with operating temperatures of up to 1 200 K. Firstly, a three-dimensional numerical investigation was conducted on a modified cavity receiver to quantify the natural convection heat loss, and to determine the effects of the operating temperature, receiver inclination angle and aperture size on heat loss. Furthermore, visualisation results, such as temperature contours, were presented to gain insight into the effects of natural convection. The Boussinesq and non-Boussinesq fluid models were used in the numerical investigation and a comparison was made between them.
Secondly, a novel approach of suppressing natural convection heat loss in a cavity receiver was investigated. The proposed model has not been observed in literature. A cavity receiver with plate fins attached to the inner aperture surface was investigated as a possible low-cost means of suppressing natural convection heat loss in a cavity receiver. Employing air as the working fluid, laminar natural convection heat transfer from the cavity receiver with plate fins attached to the inner aperture surface was investigated for a range of Rayleigh numbers, inclination angles, and fin heights and thicknesses. Furthermore, visualisation results, such as fluid flow and temperature contours, were presented to gain insight into the suppression of natural convection. In addition, a numerical optimisation tool was used to select the best plate fin geometric configuration that improves cavity receiver performance at minimum natural convection heat loss.
Finally, a numerical study and optimisation of the combined laminar natural convection and surface radiation heat transfer in the cavity receiver with plate fins were conducted, and a three-dimensional simulation model was developed to estimate and optimise the convective and radiative heat loss. The influence of operating temperature, emissivity of the surface, orientation and the geometric parameters on total heat loss (convection and radiation) from the receiver were investigated. The results in steady state were obtained for a Rayleigh number range of 105 to 107. The overall thermal efficiency of the receiver was also analysed at different operating temperatures.
From this research, it can be concluded that there is a significant deviation between the Boussinesq and non-Boussinesq models of up to 20% at high temperatures. Therefore, natural convection at high temperature differences can accurately be predicted using the non-Boussinesq model. It was also observed that a significant reduction in natural convection heat loss (up to 20%) from the cavity receiver can be achieved through plate fins, which act as heat suppressors. The results obtained provide a novel approach for improving the design of cavity receivers for optimal performance.
When natural convection was studied together with radiation, the overall cavity efficiency marginally increased by approximately 2% with the insertion of fin plates in the cavity receiver, although the convective heat loss was suppressed by about 20%. This is due to the fact that radiation heat loss dominates at high operating temperatures compared to convective heat loss.
Keywords: parabolic dish; cavity receiver; natural convection; radiation; plate fin; Rayleigh number.
Supervisor: Prof Tunde Bello-Ochende
Co-Supervisor: Prof J.P. Meyer
O.O. Noah,2016 "EXPERIMENTAL, THEORETICAL AND NUMERICAL INVESTIGATION OF NATURAL CONVECTION HEAT TRANSFER FROM HEATED MICROSPHERES IN A SLENDER CYLINDRICAL GEOMETRY"
The ability of coated particles of enriched uranium dioxide (UO2) fuel to withstand high temperatures and contain the fission products in the case of a loss of cooling event is a vital passive safety measure over traditional nuclear fuel requiring active safety systems to provide cooling. As a possible solution towards enhancing the safety of light-water reactors (LWRs), it is envisaged that the fuel in the form of loose-coated particles in a helium atmosphere can be introduced inside Silicon-Carbide nuclear reactor fuel cladding tubes of the fuel elements. The coated particles in this investigation were treated as a bed from where heat was transferred to the cladding tube by means of helium gas and the gas movement was by natural convection. Hence it was proposed that light-water reactors (LWR) could be made safer by redesigning the fuel in the fuel assembly (see Fig. 1.3b).
As a first step towards the implementation of this proposal, a proper understanding of the mechanisms of heat transfer, fluid flow and pressure drop through a packed bed of spheres during natural convection was of utmost importance. Such an understanding was achieved through a review of existing literature on porous media. However, most heat transfer correlations and models in heated packed beds are for forced convectional conditions and as such characterise porous media as a function of Reynolds number only rather than expressing media heat transfer performance as a function of thermal properties of the bed in combination with the various components of the overall heat transfer. The media heat transfer performance considered as a function of thermal properties of the bed in the proposed design is found to be a more appropriate approach than the media as a function of Reynolds number.
The quest to examine the particle-to-fluid heat transfer characteristics expected in the proposed new fuel design led to implementing this research work in three phases, namely experimental, theoretical and numerical simulation. An experimental investigation of fluid-to-particle natural convection heat transfer characteristics in packed beds heated from below was carried out. Captured data readings from the experiment were analysed and heat transfer characteristics in the medium evaluated by applying the first principle heat transfer concept. A basic unit cell (BUC) model was developed for the theoretical analysis and applied to determine the heat transfer coefficient, h, of the medium. The model adopted a concept in which a single unit of the packed bed was analysed and taken as representative of the entire bed; it related the convective heat transfer effect of the flowing fluid with the conduction and radiative effect at the finite contact spot between adjacent unit cell particles. As a result, the model could account for the thermophysical properties of sphere particles and the heated gas, the interstitial gas effect, gas temperature, contact interface between particles, particle size and particle temperature distribution in the investigated medium. Although the heat transfer phenomenon experienced in the experimental set-up was a reverse case of the proposed fuel design, the study with the achievement in the validation with the Gunn correlation aided in developing the appropriate theoretical relations required for evaluating the heat transfer characteristics in the proposed nuclear fuel design.
A slender geometrical model mimicking the proposed nuclear fuel in the cladding was numerically simulated to investigate the heat transfer characteristics and flow distribution under the natural convective conditions anticipated in beds of randomly packed spheres (coated fuel particles) using a commercial code. Random packing of the particles was achieved by discrete element method (DEM) simulation with the aid of Star CCM+ while particle-to-particle and particle-to-wall contacts were achieved through the combined use of the commercial code and a SolidWorks CAD package. Surface-to-surface radiative heat transfer was modelled in the simulation reflecting real-life application. The numerical results obtained allowed for the determination of parameters such as particle-to-fluid heat transfer coefficient, Nusselt number, Grashof number and Rayleigh number. These parameters were of prime importance when analysing the heat transfer performance of a fixed bed reactor.
A comparison of three approaches indicated that the application of the CFD combined with the BUC model gave a better expression of the heat transfer phenomenon in the medium mimicking the heat transfer in the new fuel design
Keywords: nuclear fuel; light-water reactor; porous medium; numerical simulation; natural convection heat transfer
Supervisor: Prof J. Slabber
Co-Supervisor: Prof J.P. Meyer
B.H.Freyer, 2016. " Active tool vibration control and tool condition monitoring using a selfsensing actuator"
The studies consist of two simulations of active tool vibration control and tool condition monitoring
respectively and a hardware-in-the-loop laboratory demonstration of active tool vibration control
typical to turning.
Besides reducing the restricting effects of tool vibrations on productivity, work-piece surface finish
and tool life, it is desirable to handle lack of space at the tool tip and the cost of control systems in
turning processes in an effective way. These two aspects are here considered by means of the concept
of a self-sensing actuator (SSA) in the simulation of tool vibration control. In the simulation an IIRfilter
represents the structure of the passive tool holder. A known pre-filtering technique was applied
to the error in a feedback filtered-x LMS algorithm to maintain the stability of the control system. The
self-sensing path is modelled and illustrated. The IIR-filters and their inverses were used for
modelling this path, with equations resulting from the nodal displacements associated with nodes that
have forces acting on them. For the cantilever type structure a considerable reduction of 93% of the
displacement r.m.s. values of the tool tip, was obtained when using this control system.
Signal processing using orthogonal cutting force components for tool condition monitoring (TCM)
has established itself in literature. Single axis strain sensors however limit TCM to linear combination
of cutting force components. This situation may arise when a single axis piezoelectric actuator is
simultaneously used as an actuator and a sensor, e.g. its vibration control feedback signal exploited
for monitoring purposes. Processing of a linear combination of cutting force components to the
reference case of processing orthogonal components is compared. The same time-delay neural
network structure has been applied in each case. Reconstruction of the dynamic force acting at the
tool tip in a turning process is described. By simulation this dynamic force signal was applied to a
model of the tool holder equipped with a SSA. Using a wavelet packet analysis, wear-sensitive
features were extracted. The probability of a difference less than 5 percentage points between the
flank wear estimation errors of abovementioned two processing strategies is at least 95 %.
This study proves the basic concept of adaptive feedback active vibration control in combination with
a self-sensing actuator to control tool vibrations. The structure involved is representative of a tool post
clamped tool holder. The advantages that adaptive control hold when applied to non-stationary
vibrations motivate this investigation. Secondly the dual functionality of a piezoelectric element is
utilized for system simplification. Actuator linearization measures are considered and a model for the
system’s forward path identified. The tool vibrations signal for this work is of 100 Hz bandwidth
around the representative tool holder bending mode. A downscaled force based on real cutting force
characteristics was artificially applied to the representative tool holder. Limited form locking contact
with the tool holder restricted the actuator’s reaction to compressive forces only. Results of up to 70%
attenuation of vibration induced strain on the SSA were achieved. This method clearly shows concept
Supervisor: Prof. N.J. Theron
Co-supervisor: Prof. P.S. Heyns
Erfan Asaadi,2016. "Improved inverse methods in the characterisation of mechanical behaviour of materials"
The accuracy of finite element simulations of material-dependent processes depend heavily on applying properly determined material behaviour characteristics in the simulation process. Due to practical constraints in using the analytical direct methods in some applications, inverse identification methods are widely employed to identify the material behaviour model. In this study we develop and study improved inverse methods to characterise mechanical behaviour of materials, namely model class selection and model parameter identification.
First we propose a progressive inverse identification algorithm to characterize flow stress from the material response, independent of choosing an a priori hardening constitutive model. In contrast to the conventional forward flow stress identification methods, the flow stress is characterized by a multi-linear curve rather than a limited number of a hardening model parameters. The proposed algorithm optimises the slopes and lengths of the curve increments simultaneously. We employ the algorithm to identify flow stress of a 304 stainless steel tube in a tube bulge test as an example to illustrate application of the algorithm. Since there is no need for a priori choosing the hardening model, there is no risk for choosing an improper hardening model, which in turn facilitates solving the inverse problem. The progressive inverse identification approach is classified as the forward inverse identification approach, and it is limited to characterise flow stress.
An alternative but lesser-known approach to solve an inverse material behaviour identification problem, called a direct inverse map, directly maps the measured response to the parameters of a material model. Therefore, there is no need for optimisation, which reduces the computational burden of solving an inverse problem.
In this study we investigate the potential pitfalls of the well-known stochastic noise and lesser-known model errors when constructing direct inverse maps. We show how to address these problems, explaining in particular the importance of projecting the measured response onto the domain of the simulated responses before mapping it to the material parameters. The study concludes by proposing partial least squares regression as an elegant and computationally efficient approach to address stochastic and systematic (model) errors. This study also gives insight into the nature of the inverse problem under consideration.
The above-mentioned approaches to solve an inverse problem are classified as deterministic approaches. In order to incorporate the effects of uncertainties into the measured material response and the response of the inverse problem, probabilistic inverse problems are introduced.
Therefore, we set out and justify a unified framework for Bayesian inference in Mechanical properties of Materials Characterisation (BMMC), with the aim of model class comparison and model parameter distribution inference.
We integrate Bayes’ rule, nested sampling, Galilean Monte Carlo sampling, artificial neural networks and principal component analysis to construct a unified framework for BMMC. The specific design of the constructed framework justifies its application for material-characterisation-related problems in a computationally efficient way. We demonstrate the application of the developed framework in three cases. First we compare different error correlation models related to different material responses of a tube subjected to a tube punch test in a Bayesian framework. We then compare the material model classes, which comprise combination of a Ludwik and a bilinear hardening model, along with a Hill48 anisotropy and an isotropy yield model, in a Bayesian framework. Selecting the most supportable material model class, the corresponding model parameter distributions are inferred simultaneously with no need for additional effort. The proposed method can be applied for any model class comparison and parameter distribution inference. However, its application is in particular justified for material characterisation where the problem comprises high dimensional material responses obtained from different sensors. The unified framework for BMMC avoids choosing insupportable material model classes. Moreover, the uncertainty of the material models are identified which in turn determines the uncertainty of the finite element analysis of a system made of the characterised material. The study presented offers at least two main contributions. Firstly the design of the constructed unified framework for BMMC is novel. In
addition, its practical application in material characterisation problems, namely hardening and yield identification in multi-axial state of stress is justified and demonstrated.
Throughout this thesis we mostly illustrated application of the methods on mechanical behaviour of tubular materials characterisation. However, one can generalise them for other applications.
Supervisor: Prof P.S Heyns
G.J.Jansen van Rensburg, 2016. "Development and Implementation of State Variable Based User Materials in Computational Plasticity"
The Finite Element Method is a powerful tool that can be used to test, improve or better understand an industrially relevant problem. There are numerous Finite Element Analysis (FEA) software packages that operate either in the commercial, open source or research space. Different application specific codes also have specialised model formulations. Most software packages have a comprehensive list of material models already implemented. If a different material model is required, some form of user material can often be implemented and linked to the software package. In some cases the effective implementation and testing of a user implemented material requires knowledge on the effect and handling of strain formulations, element technologies and the desired material behaviour. With sophisticated material models available in the research space, this thesis focuses on the identification and implementation of existing computational plasticity models for use within FEA.
The effect of different strain formulation choices is first illustrated and discussed using different sample problems. Three different FEA software packages are also compared before discussion and implementation of a general numerical framework for corotated hypo-elastoplasticity in isotropic and combined hardening. The numerical framework allows expansion to include different, more sophisticated hardening behaviour by simply altering the scalar equation used to update the von Mises yield surface.
The Mechanical Threshold Stress (MTS) material model is implemented within the hypo-elastoplastic numerical framework. Material parameter identification is investigated using linear regression on data followed by numerical optimisation. The MTS model is a rate and temperature dependent state variable based material model. The model is tuned to fit imperfect cemented carbide data in compression, where material test frame compliance or some eccentricity caused inhomogeneous deformation through the test section of the specimen. The characterised model is then used on a sample problem to investigate the plastic deformation in the cemented carbide anvils during the High Pressure, High Temperature (HPHT) synthesis of diamond.
Further extensions, built on the dislocation density based modelling theory of the MTS model, are investigated by selecting an alternate form of the state dependent variable. A dislocation density ratio is used instead of the original stress like variable in the MTS model. The evolution of this internal state variable is altered, along with additional state dependent variables, to include additional deformation and thermal mechanisms. The model extensions in the case of rate and temperature dependent cyclic deformation as well as multiple waves of recrystallisation are discussed and implemented. The recrystallisation and through thickness microstructural variation of a High Strength, Low Alloy (HSLA) steel are finally investigated during the process of industrial hot rolling or roughing simulations.
Supervisors: Prof. S. Kok
Co-supervisor: Dr D.N. Wilke
Saheed Adewale Adio, 2016. "Experimental investigation and mathematical modelling of thermophysical properties of ethylene glycol and glycerol-based nanofluids"
Nanofluids are a new class of heat transfer fluids that aim to improve the poor thermal efficiency of conventional heat transfer fluids. The dispersion of nanoparticles into traditional heat transfer fluids, such as water, ethylene glycol, glycerol, engine oil and gear oil, improves the thermal conductivity of base fluids, which has attracted researchers to apply nanofluids in engineering systems. Nanofluids show higher thermal and electrical conductivity. However, in terms of heat transfer performance, viscosity is also important. The viscosity of nanofluids increases due to an increase in the nanoparticle volume fraction, which needs attention and proper experimental investigation to improve the efficiency of nanofluids in heat transfer applications. Consequently, investigation into the effective viscosity of nanofluids is as important as the thermal conductivity.
On the other hand, how nanofluids are prepared can have an effect on the resultant performance. Using an ultrasonication mixer for the dispersion of nanoparticles in the base fluid is one of the most effective and popular methods of preparing nanofluids, especially from the two-step method. Almost all the experimental studies available on nanofluids chose an arbitrary time for the preparation of nanofluids. Choosing an arbitrary time for ultrasonication or any other physical preparation mechanism may be counterproductive. Therefore, in this research, nanofluids are prepared through an optimised two-step method that is assisted with ultrasonic vibration. The resulting homogenised nanofluids are further investigated for the influence of temperature, particle size, volume fraction, base fluid type and particle type on the evolution of the viscosity, pH and electrical conductivity. The temperature range investigated in this thesis is 20 to 70 oC; the nanoparticle volume fraction is up to 5%; the base fluids are ethylene glycol (EG) and glycerol, while the nanoparticle types are MgO, Al2O3 and SiO2 in different sizes.
Viscosity is a very important parameter, especially in systems that involve fluid flow (forced or natural convection) and for numerical analysis. However, most generic models in the literature underpredicted the viscosity evolution of nanofluids. Therefore, it is essential that very accurate models need to be developed for the prediction of the viscosity of nanofluids. To this end, this research also models the viscosity of the different nanofluids using dimensional analysis and regression analysis based on the experimental input-output data. Furthermore, artificial intelligence methods, such as the group method of data handling-neural network (GMDH-NN), genetic algorithm-polynomial neural network (GA-PNN) and fuzzy C-mean clustering-based adaptive neuro-fuzzy inference system (FCM-ANFIS) methods, are used to model the relationships between the experimental input parameters and the viscosity of the nanofluids.
Generally, the viscosity of the nanofluids reduced exponentially with temperature increase and the trends are similar to those displayed by the respective base fluids. However, the viscosity of the nanofluids is higher depending on the concentration of the nanoparticles contained in the nanofluids. Suspending nanoparticles in the base fluid increased the viscosity of the resulting nanofluid, and a further increase in the volume fraction of the nanoparticles increased the effective viscosity of the nanofluids. The viscosity trend of the nanofluids of Al2O3-glycerol is non-linear to volume fraction increase while MgO-EG nanofluids displayed a linear dependence. Regarding the influence of particle size, smaller particles produced a higher energy dissipation rate due to the higher number density, increased Brownian velocity and particle-particle interactions. Therefore, the viscosity was higher in nanofluid samples prepared from smaller nanoparticles. When the same nanoparticle samples were dispersed in different base fluids, it was found that the relative viscosity is different in the different nanofluids, which suggests that base fluid properties are indispensable when discussing the viscosity of nanofluids.
The pH and electrical conductivity of the base fluids did not change much with an increase in temperature, and their values were smaller than unity. The suspension of nanoparticles saw an increase in the values of both the pH and electrical conductivity. As the volume fraction of suspended particles increased, the value of the electrical conductivity and pH also increased commensurately, until counterion condensation effects set in. Increasing the temperature of the nanofluids led to an increase in the electrical conductivity, while the pH generally reduced with an increase in temperature. Although smaller nanoparticles showed slightly higher electrical conductivity values, pH values were convincingly higher across all the volume fractions. The ionisation process is different for the different base fluids, therefore, the pH and electrical conductivity were different for the same nanoparticles suspended in different base fluids.
The viscosity correlations developed in this thesis through dimensional analysis with regression all gave good agreements with the experimental data. When the correlations were compared with some of the prominent, well-cited models in the open literature, they performed better in producing experimental results. Furthermore, the use of GMDH-NN, GA-PNN and FCM-ANFIS for modelling and predicting the effective viscosity for the nanofluids as a function of particle diameter, temperature and volume fraction are presented. The results of the GMDH-NN, GA-PNN and FCM-ANFIS models all showed very good agreement when compared with the experimental data. Therefore, these models come in handy when using these nanofluids for computational fluid dynamics or any other design analyses.
Keywords: Nanofluid, effective viscosity, electrical conductivity, pH, MgO, ethylene glycol, Al2O3, glycerol, SiO2, temperature, volume fraction, nanoparticle size, relative viscosity, ultrasonication, energy density, empirical models, dimensional analysis modelling, GMDH-NN, GA-PNN, FCM-ANFIS.
Supervisors : Dr Mohsen Sharifpur and Prof Josua P Meyer
Nicolin Govender, 2015. “Blaze-DEM: A GPU based large scale 3D
discrete element particle transport framework"
Understanding the dynamical behavior of particulate materials is extremely important to many industrial processes with a wide range of applications ranging from hopper flows in agriculture to tumbling mills in the mining industry. Thus simulating the dynamics of particulate materials is critical in the design and optimization of such processes. The mechanical behavior of particulate materials is complex and cannot be described by a closed form solution for more than a few particles. A popular and successful numerical approach in simulating the underlying dynamics of particulate materials is the discrete element method (DEM). However, the DEM is computationally expensive and computational viable simulations are typically restricted to a few particles with realistic particle shape or a larger number of particles with an often oversimplified particle shape. It has been demonstrated for numerous applications that an accurate representation of the particle shape is essential to accurately capture the macroscopic transport of particulates. The most common approach to represent particle shape is by using a cluster of spheres to approximate the shape of a particle. This approach is computationally intensive as multiple spherical particles are required to represent a single non-spherical particle. In addition spherical particles are for certain applications a poor approximation when sharp interfaces are essential to capture the bulk transport. An advantage of this approach is that non-convex particles are handled with ease. Polyhedra represent the geometry of most convex particulate materials well and when combined with appropriate contact models exhibit realistic mechanical behavior to that of the actual system. However detecting collisions between the polyhedra is computationally expensive often limiting simulations to only a few thousand of particles.
Driven by the demand for real-time graphics, the Graphical Processor Unit (GPU) offers cluster type performance at a fraction of the computational cost. The parallel nature of the GPU allows for a large number of simple independent processes to be executed in parallel. This results in a significant speed up over conventional implementations utilizing the Central Processing Unit (CPU) architecture, when algorithms are well aligned and optimized for the threading model of the GPU. This thesis investigates the suitability of the GPU architecture to simulate particulate materials using the DEM. The focus of this thesis is to develop a computational framework for the GPU architecture that can model (i) tens of millions of spherical particles and (ii) millions of polyhedral particles in a realistic time frame on a desktop computer using a single GPU. The contribution of this thesis is the development of a novel GPU computational frame-work Blaze-DEM, that encompasses collision detection algorithms and various heuristics that are optimized for the parallel GPU architecture. This research has resulted in a new computational performance level being reached in DEM simulations for both spherical and polyhedra shaped particles.
In terms of the particle shape there are no other freely available codes that can match the geometrical fidelity in terms of accurate representation on the GPU. To the authors best knowledge there is only one study on the GPU that takes particle shape into account with a physics model of similar fidelity to Blaze-DEM. That study uses the clumped sphere method. Blaze-DEM is able to simulate 2 orders of magnitude more particles compared to other published results while being 3 times faster. The only reported implementations for polyhedra are on the CPU platform. Blaze-DEM is hundreds of times faster compared to CPU codes with physics models of a similar fidelity and 24 times faster than CPU codes with physics models of a lower fidelity. For simulations involving spherical particles Blaze-DEM is 5 times faster than other GPU based codes that have physics models of a similar fidelity.
Keywords: DEM, GPU, Parallel Processing, Polyhedra, Particle transport framework, Semi-autogenous ball mill, Particle discharge
Supervisors: Dr. D.N. Wilke, Prof. S. Kok
Mehdi Mehrabi, 2015. "Modelling and optimisation of thermophysical properties and convective heat transfer of nanofluids by using artificial intelligence methods"
Nanofluids are modern heat transfer fluids which can significantly increase the thermal performance of a thermal system. It enhances the thermal conductivity of working fluids due to adding solid nanoparticles to the base fluid. In order to use nanofluids widely in industrial applications knowing the thermophysical properties of these new heat transfer fluids are essential. In this research, the GA-PNN and FCM-ANFIS methods are employed to present models for thermophysical properties of nanofluids. Furthermore, modified NSGA-II technique has been used to optimise the convective heat transfer of nanofluids in a turbulent flow regime.
In recent years considerable correlations have been suggested by different researchers for thermophysical properties of nanofluids based on the experimental and theoretical works, which a large number of those correlations are failed to predict the thermophysical properties of nanofluids for a wide range of particle size, temperature and nanoparticle volume concentrations. In this thesis, experimental data available in literature have been used to propose models for thermophysical properties of nanofluids to overcome this problem by using artificial intelligence-based techniques. Two models based on FCM-ANFIS and GA-PNN techniques have been proposed for the thermal conductivity and viscosity of nanofluids. To show the accuracy of the proposed models, the predicted result has been compared with experimental data as well as well-cited correlations in literature. Furthermore, the convective heat transfer of nanofluids was studied and different models based on artificial intelligence techniques have been proposed to model the Nusselt number and pressure drop of nanofluids in a turbulent regime. Finally, a multi-objective optimisation technique was used to optimise the convective heat transfer characteristics and pressure drop of nanofluids to find the best design point base on the Pareto front of the results. The predictions of the models for all cases agreed with the experimental data much better than the available correlations.
Keywords: Nanofluids, thermophysical properties of nanofluids, Brownian motion, nanolayering, artificial intelligence, multi-objective optimisation, GA-PNN (genetic algorithm-polynomial neural network) method, FCM-ANFIS (fuzzy C-means clustering- adaptive neuro-fuzzy inference system) technique, convection heat transfer, NSGA-II (modified non-dominated sorting genetic algorithm) multi-objective optimisation
Dr. Mohsen Sharifpur and Prof. Josua P. Meyer
Johnathan John Vadasz, 2015. "Vibration effects on Natural convection in a porous layer heated from below with application to solidification of binary alloys"
Directional solidification has a wide interest due to its importance to the iron and steel industry. Examples of further application can be found in the aerospace industry regarding the manufacture of turbine blades and the semiconductor industry regarding single-crystal growth applications. Solute convection in the solidification process results in channel formation, which has a freckle-like appearance in cross-section and has a critical effect on the mechanical strength of a casting. For a solidification process that occurs via planar solidification from a solid boundary, one may consider the presence of three distinct regions often identified as horizontal layers, i.e. a fluid binary mixture (the melt), the solid layer and a two-phase (fluid-solid) mushy layer, separating the other two. The mushy layer is practically a porous medium consisting of an interconnected solid phase having its voids filled with the melt binary fluid. Channelling in the mushy layer and the creating of freckles are being considered the main reasons for non-homogeneous solidification and production of defects in the resulting solid product. The production of defects adversely affects the mechanical properties of the solid product leading to undesirable constraints on its industrial use.
The purpose of this study is to evaluate the effect the vibrations have on the heat transfer during the solidification process as well as on the average density of the solid product and void formation. Experimental work on solidification of paraffin was performed. Theoretical results of heat convection in a porous layer heated from below and subject to vibrations are presented by using a truncated spectral method in space. The results show that the heat convection subject to vibration is generally reduced when compared with the corresponding convection without vibrations. The exception for a certain frequency range shows about a 10% enhancement in the weak turbulent regime of convection, however, a 10% enhancement is still lower than the heat transfer prior to the transition to weak turbulence. Therefore, the heat transfer mechanism can be excluded as the main reason behind the improvement in solidification when vibrations are applied.
KEYWORDS: vibration, solidification, mushy layer, porous media, natural convection.
Supervisors: Professor Josua P. Meyer, Dr. Saneshan Govender
Willem Gabriel le Roux, 2015. "THERMODYNAMIC OPTIMISATION AND EXPERIMENTAL COLLECTOR OF A DISH-MOUNTED SMALL-SCALE SOLAR THERMAL BRAYTON CYCLE"
The small-scale dish-mounted open solar thermal Brayton cycle (1-20 kW) with recuperator has an advantage in terms of cost and mobility and can offer an off-grid electricity solution to the people of the water-scarce southern Africa. South Africa has an advantage in terms of solar resource, but this solar resource is not used extensively due to high-cost and low-efficiency solar-to-electricity systems. The dish-mounted solar thermal Brayton cycle with recuperator offers a solution. However, heat losses and pressure losses in the cycle components can decrease the net power output of the system tremendously. In addition, the costs due to solar tracking and perfect dish optics can be high. The purpose of the study was to develop the small-scale (1-20 kW) dish-mounted open solar thermal Brayton cycle by optimising an open-cavity tubular solar receiver and counterflow plate-type recuperator with the method of total entropy generation minimisation. The optimised receiver was also tested in an experimental dish collector set-up. Modelling methods to predict the performance of the cycle and to optimise the solar receiver and recuperator were developed and tested so that the small-scale open solar thermal Brayton cycle could be developed further. SolTrace was used as ray-tracing method to determine the effects of inaccurate dish optics. An optimum concentration ratio of 0.0035 was identified for a collector with a maximum tracking error of 1° and an optical error of 10 mrad. It was shown that the open-cavity tubular solar receiver surface temperature and net heat transfer rate for heating air depended on the receiver size, mass flow rate through the receiver, receiver tube diameter, receiver inlet temperature and dish errors. Receiver efficiencies of between 43% and 70% were found for a receiver with mass flow rates of between 0.06 kg/s and 0.08 kg/s, tube diameters of between 0.05 m and 0.0833 m, air inlet temperatures of between 900 K and 1 070 K operating on a dish with 10 mrad optical error and maximum solar tracking error of 1°. With the use of Matlab and Flownex, it was shown that the small-scale open solar thermal Brayton cycle could generate a positive net power output with solar-to-mechanical efficiencies in the range of 10-20% with much room for improvement. The maximum receiver surface temperature was restricted to 1 200 K and the recuperator weight was restricted to 500 kg. An experimental set-up with a 4.8 m diameter parabolic dish with rim angle of 45° on a two-axis tracking system was constructed to test the receiver. An optimised open-cavity stainless steel tubular receiver with tube diameter of 88.9 mm was tested in the experiment. The experimental results showed the challenges regarding the design and construction of a solar thermal Brayton cycle collector. It was found that the insulation arrangement around the large receiver tube diameter influenced the heat loss due to convection and conduction. Results showed that with further research, the small-scale open solar thermal Brayton cycle could be a competitive small-scale solar energy solution to the people of South Africa.
Keywords: solar, Brayton, receiver, optimisation, entropy
Supervisors: Prof. T. Bello-Ochende, Prof. J. P. Meyer.
Aggrey Mwesigye, 2015. "Thermal Performance and Heat Transfer Enhancement of Parabolic Trough Receivers – Numerical Investigation, Thermodynamic and Multi-Objective Optimisation"
Parabolic trough systems are one of the most commercially and technically developed technologies for concentrated solar power. With the current research and development efforts, the cost of electricity from these systems is approaching the cost of electricity from medium-sized coal-fired power plants. Some of the cost-cutting options for parabolic trough systems include: (i) increasing the sizes of the concentrators to improve the system’s concentration ratio and to reduce the number of drives and controls and (ii) improving the system’s optical efficiency. However, the increase in the concentration ratios of these systems requires improved performance of receiver tubes to minimise the absorber tube circumferential temperature difference, receiver thermal loss and entropy generation rates in the receiver. As such, the prediction of the absorber tube’s circumferential temperature difference, receiver thermal performance and entropy generation rates in parabolic trough receivers therefore, becomes very important as concentration ratios increase.
In this study, the thermal and thermodynamic performance of parabolic trough receivers at different Reynolds numbers, inlet temperatures and rim angles as concentration ratios increase are investigated. The potential for improved receiver thermal and thermodynamic performance with heat transfer enhancement using wall-detached twisted tape inserts, perforated plate inserts and perforated conical inserts is also evaluated.
In this work, the heat transfer, fluid flow and thermodynamic performance of a parabolic trough receiver were analysed numerically by solving the governing equations using a general purpose computational fluid dynamics code. SolTrace, an optical modelling tool that uses Monte-Carlo ray tracing techniques was used to obtain the heat flux profiles on the receiver’s absorber tube. These heat flux profiles were then coupled to the CFD code by means of user-defined functions for the subsequent analysis of the thermal and thermodynamic performance of the receiver. With this approach, actual non-uniform heat flux profiles and actual non-uniform temperature distribution in the receiver different from constant heat flux profiles and constant temperature distribution often used in other studies were obtained.
Both thermodynamic and multi-objective optimisation approaches were used to obtain optimal configurations of the proposed heat transfer enhancement techniques. For thermodynamic optimisation, the entropy generation minimisation method was used. Whereas, the multi-objective optimisation approach was implemented in ANSYS DesignXplorer to obtain Pareto solutions for maximum heat transfer and minimum fluid friction for each of the heat transfer enhancement techniques.
Results showed that rim angles lower than 60o gave high absorber tube circumferential temperature differences, higher receiver thermal loss and higher entropy generation rates, especially for flow rates lower than 43 m3/h. The entropy generation rates reduced as the inlet temperature increased, increased as the rim angles reduced and as concentration ratios increased. Existence of an optimal Reynolds number at which entropy generation is a minimum for any given inlet temperature, rim angle and concentration ratio is demonstrated. In addition, for the heat transfer enhancement techniques considered, correlations for the Nusselt number and fluid friction were obtained and presented. With heat transfer enhancement, the thermal efficiency of the receiver increased in the range 5% – 10%, 3% – 8% and 1.2% – 8% with twisted tape inserts, perforated conical inserts and perforated plate inserts respectively. Results also show that with heat transfer enhancement, the absorber tube’s circumferential temperature differences reduce in the range 4% – 68%, 3.4 – 56% and up to 67% with twisted tape inserts, perforated conical inserts and perforated plate inserts respectively. Furthermore, the entropy generation rates were reduced by up to 59%, 45% and 53% with twisted tape inserts, perforated conical inserts and perforated plate inserts respectively. Moreover, using multi-objective optimisation, Pareto optimal solutions were obtained and presented for each heat transfer enhancement technique.
In summary, results from this study demonstrate that for a parabolic trough system, rim angles, concentration ratios, flow rates and inlet temperatures have a strong influence on the thermal and thermodynamic performance of the parabolic trough receiver. The potential for improved receiver thermal and thermodynamic performance with heat transfer enhancement has also been demonstrated. Overall, this study provides useful knowledge for improved design and efficient operation of parabolic trough systems.
Key words: Absorber tube; Computational fluid dynamics; Concentration ratio; Entropy generation rate; Heat transfer enhancement; Monte-Carlo ray tracing; Multi-Objective optimisation; Parabolic trough receiver; Perforated plate inserts; Perforated conical inserts; Rim angle, Twisted tape inserts.
Supervisors: Prof. T. Bello-Ochende, Prof. J. P. Meyer.
A Dymond, 2014. " TUNING OPTIMIZATION ALGORITHMS UNDER MULTIPLE OBJECTIVE FUNCTION EVALUATION BUDGETS "
The performance of optimization algorithms is sensitive to both the optimization problem's numerical characteristics and termination criteria. Given these considerations two tuning algorithms named tMOPSO and MOTA are proposed to assist optimization practitioners to find algorithm settings which are approximate for the problem at hand. For a specified problem tMOPSO aims to determine multiple groups of control parameter values, each of which results in optimal performance at a different objective function evaluation budget. To achieve this, the control parameter tuning problem is formulated as a multi-objective optimization problem. Furthermore, tMOPSO uses a noise-handling strategy and control parameter value assessment procedure, which are specialized for tuning stochastic optimization algorithms. The principles upon which tMOPSO were designed are expanded into the context of many objective optimization, to create the MOTA tuning algorithm. MOTA tunes an optimization algorithm to multiple problems over a range of objective function evaluation budgets. To optimize the resulting many objective tuning problem, MOTA makes use of bi-objective decomposition. The last section of work entails an application of the tMOPSO and MOTA algorithms to benchmark optimization algorithms according to their tunability. Benchmarking via tunability is shown to be an effective approach for comparing optimization algorithms, where the various control parameter choices available to an optimization practitioner are included into the benchmarking process.
Supervisors: Prof. P.S. Heyns, Prof. S. Kock
JJA Eksteen, 2014. " ADVANCES IN ITERATIVE LEARING CONTROL WITH APPLICATION TO STRUCTURAL DYNAMICS RESPONSE RECONTRUCTION "
Iterative learning control (ILC) is a repetitive control scheme that uses a learning capability to improve the tracking accuracy of a desired test system output over repeated test trials. ILC is sometimes used in response reconstruction on complex engineering structures, such as ground vehicles, for purposes of fatigue/durability testing. The compensator that is employed in ILC in such cases is traditionally an approximate, linear inverse model of the closed-loop test system. This research presents advances in ILC, particularly with respect to its application in response reconstruction for fatigue testing purposes. The contribution of this research focuses on three aspects: the use of a nonlinear inverse model in ILC as ILC compensator instead of a linear inverse model; the use of multiple inverse models, each one defined over a different part of the test frequency band, instead of one model that covers the entire test frequency band; and on the development and use of a new type of ILC algorithm. The contributions are implemented and demonstrated on a quarter vehicle road simulator, with favourable results for the use of nonlinear inverse models and multiple inverse models, and with the new ILC algorithm giving comparable to slightly worse results than the conventional ILC algorithm. In order to invert the nonlinear inverse models this research also presents advances in the stable inversion method that is used to invert such models.
Supervisor: Prof. P.S. Heyns
S Aye, 2014. " ACUSTIC EMISSION-BASED DIAGNOSTICS AND PROGNOSTICS OF SLOE ROTATING BEARINGS USING BAYESIAN TECHNIQUES"
Diagnostics and prognostics in rotating machinery is a subject of much on-going research. There are three approaches to diagnostics and prognostics. These include experience-based approaches, data-driven techniques and model-based techniques. Bayesian data-driven techniques are gaining widespread application in diagnostics and prognostics of mechanical and allied systems including slow rotating bearings, as a result of their ability to handle the stochastic nature of the measured data well. The aim of the study is to detect incipient damage of slow rotating bearings and develop diagnostics which will be robust under changing operating conditions. Further it is required to explore and develop an optimal prognostic model for the prediction of remaining useful life (RUL) of slow rotating bearings.
This research develops a novel integrated nonlinear method for the effective feature extraction from acoustic emission (AE) signals and the construction of a degradation assessment index (DAI), which are subsequently used for the fault diagnostics of slow rotating bearings. A slow rotating bearing test rig was developed to measure AE data under variable operational conditions. The proposed novel DAI obtained by the integration of the PKPCA (polynomial kernel principal component analysis), a Gaussian mixture model (GMM) and an exponentially weighted moving average (EWMA) is shown to be effective and suitable for monitoring the degradation of slow rotating bearings and is robust under variable operating conditions. Furthermore, this study integrates the novel DAI into alternative Bayesian methods for the prediction of remaining useful life (RUL). The DAI is used as input in several Bayesian regression models such as the multi-layer perceptron (MLP), radial basis function (RBF), Bayesian linear regression (BLR), Gaussian mixture
regression (GMR) and the Gaussian process regression (GPR) for RUL prediction. The combination of the DAI with the GPR model, otherwise, known as the DAI-GPR gives the best prediction. The findings show that the GPR model is suitable and effective in the prediction of RUL of slow rotating bearings and robust to varying operating conditions. Further, the models are also robust when the training and tests sets are obtained from dependent and independent samples.
Finally, an optimal GPR for the prediction of RUL of slow rotating bearings based on a DAI is developed. The model performance is evaluated for cases where the training and test samples from cross validation approach are dependent as well as when they are independent. The optimal GPR is obtained from the integration or combination of existing simple mean and covariance functions in order to capture the observed trend of the bearing degradation as well as the irregularities in the data. The resulting integrated GPR model provides an excellent fit to the data and improvements over the simple GPR models that are based on simple mean and covariance functions. In addition, it achieves a near zero percentage error prediction of the RUL of slow rotating bearings when the training and test sets are from dependent samples but slightly different values when the estimation is based on independent samples. These findings are robust under varying operating conditions such as loading and speed. The proposed methodology can be applied to nonlinear and non-stationary machine response signals and is useful for preventive machine maintenance purposes.
Supervisor: Prof. P.S. Heyns
Olabode Olakoyejo, 2013. " GEOMETRIC OPTIMISATION OF CONJUGATE COOLING CHANNELS WITH DIFFERENT CROSS-SECTIONAL SHAPES"
In modern heat transfer, shape and geometric optimisation are new considerations in the evaluation of thermal performance. In this research, we employed constructal theory and design to present three-dimensional theoretical and numerical solutions of conjugate forced convection heat transfer in heat generating devices with cooling channels of different cross-sectional shapes.
In recent times, geometric configurations of cooling channel have been found to play an important role in thermal performance. Therefore, an efficient ways of optimally designing these cooling channels shapes is required.
Experimentation has been extensively used in the past to understand the behaviour of heat removals from devices. In this research, the shapes of the cooling channels and the configurations of heat-generating devices were analytically and numerically studied to minimise thermal resistance and thus illustrate cooling performance under various design conditions.
The cooling channels of five different cross-sectional shapes were studied: Circular, square, rectangular, isosceles right triangular and equilateral triangular. They were uniformly packed and arranged to form larger constructs.
The theoretical analysis is presented and developed using the intersection of asymptotes method. This proves the existence of an optimal geometry of parallel channels of different cross-sectional shapes that penetrate and cool a volume with uniformly distributed internal heat generation and heat flux, thus minimising the global thermal resistance.
A three-dimensional finite volume-based numerical model was used to analyse the heat transfer characteristics of the cross-sectional shapes of various cooling channels. The numerical computational fluid dynamics (CFD) package recently provided a more cost-effective and less time-consuming means of achieving the same objective. However, in order to achieve optimal design solutions using CFD, the thermal designers have to be well experienced and carry out a number of trial-and-error simulations. Unfortunately, this can not always guarantee an accurate optimal design solution. In this thesis a mathematical optimisation algorithm (a leapfrog optimisation program and DYNAMIC-Q algorithm) coupled with numerical CFD was employed and incorporated into the finite volume solver, –FLUENT, and grid (geometry and mesh) generation package, – GAMBIT to search and identify the optimal design variables at which the system would perform optimally for greater efficiency and better accuracy. The algorithm was also specifically designed to handle constraint problems where the objective and constraint functions were expensive to evaluate.
The automated process was applied to different design cases of cooling channels shapes. These cooling channels were embedded in a highly conductive solid and the peak temperature was minimised.
The trend and performance of all the cooling channel shapes cases studied were compared analytically and numerically. It was concluded that an optimal design can be achieved with a combination of CFD and mathematical optimisation.
Furthermore, a geometric optimisation of cooling channels in the forced convection of a vascularised material (with a localised self-cooling property subjected to a heat flux) was also considered. A square configuration was studied with different porosities. Analytical and numerical solutions were provided. This gradient-based optimisation algorithm coupled with CFD was used to determine numerically the optimal geometry that gave the lowest thermal resistance. This optimiser adequately handled the numerical objective function obtained from numerical simulations of the fluid flow and heat transfer.
The numerical results obtained were in good agreement with results obtained in the approximate solutions based on scale analyses at optimal geometry dimensions. The approximate dimensionless global thermal resistance predicted the trend obtained in the numerical results. This shows that there were unique optimal design variables (geometries) for a given applied dimensionless pressure number for fixed porosity.
The results also showed that the material property had a significant influence on the performance of the cooling channel.
Therefore, when designing the cooling structure of vascularised material, the internal and external geometries of the structure, material properties and pump power requirements would be very important parameters to be considered in achieving efficient and optimal designs for the best performance.
Finally, this research investigated a three-dimensional geometric optimisation of conjugate cooling channels in forced convection with an internal heat generation within the solid for an array of cooling channels. Three different flow orientations based on constructal theory were studied numerically- firstly, an array of channels with parallel flow; secondly, an array of channels in which flow of every second row was in a counter direction and finally, an array of channels in which the flow direction in every channel was opposite to that of previous channel. The geometric configurations and flow orientations were optimised in such a way that the peak temperature was minimised subject to the constraint of fixed global volume of solid material. The optimisation algorithm coupled with CFD was also used to determine numerically the optimal geometry that gave the lowest thermal resistance.
The use of the optimisation algorithm coupled with the computational fluid dynamics package; render the numerical results more robust with respect to the selection of optimal structure geometries, internal configurations of the flow channels and dimensionless pressure difference.
Keywords: Geometric configurations, computational fluid dynamics, mathematical optimisation, thermal conductivity, constraints, laminar flow, forced convection, optimal geometry, peak temperature, constructal theory, thermal resistance, Dynamic-Q, flow orientation
Supervisors: Prof. T. Bello-Ochende/Prof. J.P. Meyer
Mr. SO OBAYOPO 2012 "Performance enhancement in proton exchange membrane fuel cell – numerical modelling and optimisation"
Sustainable growth and development in a society requires energy supply that is efficient, affordable, readily available and, in the long term, sustainable without causing negative societal impacts, such as environmental pollution and its attendant consequences. In this respect, proton exchange membrane (PEM) fuel cells offer a promising alternative to existing conventional fossil fuel sources for transport and stationary applications due to its high efficiency, low-temperature operation, high power density, fast start-up and its portability for mobile applications. However, to fully harness the potential of PEM fuel cells, there is a need for improvement in the operational performance, durability and reliability during usage. There is also a need to reduce the cost of production to achieve commercialisation and thus compete with existing energy sources. The present study has therefore focused on developing novel approaches aimed at improving output performance for this class of fuel cell.
In this study, an innovative combined numerical computation and optimisation techniques, which could serve as alternative to the laborious and time-consuming trial-and-error approach to fuel cell design, is presented. In this novel approach, the limitation to the optimal design of a fuel cell was overcome by the search algorithm (Dynamic-Q) which is robust at finding optimal design parameters. The methodology involves integrating the computational fluid dynamics equations with a gradient-based optimiser (Dynamic-Q) which uses the successive objective and constraint function approximations to obtain the optimum design parameters. Specifically, using this methodology, we optimised the PEM fuel cell internal structures, such as the gas channels, gas diffusion layer (GDL) - relative thickness and porosity - and reactant gas transport, with the aim of maximising the net power output. Thermal-cooling modelling technique was also conducted to maximise the system performance at elevated working temperatures.
The study started with a steady-state three-dimensional computational model to study the performance of a single channel proton exchange membrane fuel cell under varying operating conditions and combined effect of these operating conditions was also investigated. From the results, temperature, gas diffusion layer porosity, cathode gas mass flow rate and species flow orientation significantly affect the performance of the fuel cell. The effect of the operating and design parameters on PEM fuel cell performance is also more dominant at low operating cell voltages than at higher operating fuel cell voltages. In addition, this study establishes the need to match the PEM fuel cell parameters such as porosity, species reactant mass flow rates and fuel gas channels geometry in the system design for maximum power output.
This study also presents a novel design, using pin fins, to enhance the performance of the PEM fuel cell through optimised reactant gas transport at a reduced pumping power requirement for the reactant gases. The results obtained indicated that the flow Reynolds number had a significant effect on the flow field and the diffusion of the reactant gas through the GDL medium. In addition, an enhanced fuel cell performance was achieved using pin fins in a fuel cell gas channel, which ensured high performance and low fuel channel pressure drop of the fuel cell system. It should be noted that this study is the first attempt at enhancing the oxygen mass transfer through the PEM fuel cell GDL at reduced pressure drop, using pin fin.
Finally, the impact of cooling channel geometric configuration (in combination with stoichiometry ratio, relative humidity and coolant Reynolds number) on effective thermal heat transfer and performance in the fuel cell system was investigated. This is with a view to determine effective thermal management designs for this class of fuel cell. Numerical results shows that operating parameters such as stoichiometry ratio, relative humidity and cooling channel aspect ratio have significant effect on fuel cell performance, primarily by determining the level of membrane dehydration of the PEM fuel cell. The result showed the possibility of operating a PEM fuel cell beyond the critical temperature ( 80°C), using the combined optimised stoichiometry ratio, relative humidity and cooling channel geometry without the need for special temperature resistant materials for the PEM fuel cell which are very expensive.
The study methodology is the first of its kind in South Africa on PEM fuel cell system and deemed to pave way for enhanced sustainable energy development through fuel cell technology.
Supervisors: Prof. T. Bello-Ochende/Prof. J.P. Meyer
Shafiqur Rehman 2012 "WIND POWER RESOURCE ASSESSMENT, DESIGN OF GRID-CONNECTED WIND FARM AND HYBRID POWER SYSTEM"
An exponentially growing global population, power demands, pollution levels and, on the other hand, rapid advances in means of communication have made the public aware of the complex energy situation. The Kingdom of Saudi Arabia has vast open land, an abundance of fossil fuel, a small population but has always been among the front-runners where the development and utilisation of clean sources of energy are concerned. Several studies on wind, solar and geothermal sources of energy have been conducted in Saudi Arabia. Solar photovoltaic (pv) has been used for a long time in many applications such as cathodic protection, communication towers and remotely located oil field installations. Recently, a 2MW grid-connected pv power plant has been put online and much larger solar desalination plants are in planning stage.
Wind resource assessment, hub height optimisation, grid-connected wind farm and hybrid power system design were conducted in this study using existing methods. Historical daily mean wind speed data measured at 8 to 12metres above ground level at national and international airports in the kingdom over a period of 37 years was used to obtain long-term annual and monthly mean wind speeds, annual mean wind speed trends, frequency distribution, Weibull parameters, wind speed maps, hub height optimisation and energy yield using an efficient modern wind turbine of 2.75MW rated power. A further detailed analysis (such as estimation of wind shear exponent, Weibull parameters at different heights, frequency distribution at different heights, energy yield and plant capacity factor and wind speed variation with height) was conducted using wind speed measurements made at 20, 30 and 40metres above ground level.
As a first attempt, an empirical correlation was developed for the estimation of near-optimal hub height (HH = 142.035 * (α) + 40.33) as a function of local wind shear exponent (α) with a correlation coefficient of 97%. This correlation was developed using the energy yield from a wind turbine of 1 000kW rated power and wind speed and local exponent for seven locations in Saudi Arabia. A wind-pv-diesel hybrid power system was designed and specifications were made for a remotely located village, which is being fed 100% by diesel power generating units. The proposed system, if developed, will offset around 35% of the diesel load and therefore will result in decreased air pollution by almost the same amount.
The developed wind speed maps, the frequency distributions and estimated local wind shear exponents for seven locations and energy yield will be of great help in defining the further line of action and policy-building towards wind power development and utilisation in the kingdom. The study also recommends conducting a wind measurement campaign using tall towers with wind measurements at more than one height and estimating the local wind shear exponents and developing a wind atlas for the kingdom. The study further states that a grid-connected wind farm of moderate capacity of 40MW should be developed using turbines of varying rated powers. The wind speed data was also analysed using wavelet transform and Fast Fourier Transform (FFT) to understand the fluctuation in wind speed time series for some of the stations. It is also recommended that policy-makers should take firm decision on the development of hybrid power systems for remotely located populations which are not yet connected with the grid. There are two challenges which need research: one is the effect of dust on the moving and structural elements of the wind turbines and the second is the effect of high prevailing temperatures on the performance and efficiency of the same.
Supervisor: Dr. Md. Mahbub Alam
Co-supervisors: Prof. JP Meyer and Dr. Luai M. Al-Hadhrami
C Kat 2012 "Validated leaf spring suspension models "
As all simulation models in this study are required to be validated against experimental measurements a thorough experimental characterisation of the suspension system of interest, as well as two different leaf springs, are performed. In order to measure the forces between the suspension attachment points and the chassis two six component load cells were developed, calibrated, verified and validated.
This study will primarily focus on the modelling of multi-leaf and parabolic leaf springs. The study starts with a literature study into the various existing modelling techniques for leaf springs. A novel multi-leaf spring model, which is based on a macro modelling view point similar to that used for modelling material behaviour, is developed. One of the modelling techniques found in the literature i.e. neural networks is also used to model the leaf spring. The use of neural networks is applied and some of the challenges associated with the method is indicated. The accuracy and efficiency of the physics-based elasto-plastic leaf spring model and the non physics-based neural network model are compared. The accuracy is calculated using a new quantitative validation metric that is able to give an intuitive and reliable account of the accuracy between two signals. The quantitative validation metric is based on the well-known, and frequently used, relative error. The modified percentage relative error metric that is developed accounts for the known challenges associated with using the relative error on signals with a periodic nature around zero. The modified percentage relative error metric is compared to two other quantitative validation metrics that were identified from the literature study. It is concluded that the modified percentage relative error has certain limitations but that it is able to give an accurate and reliable account of the agreement/disagreement between two periodic signals around zero. The modified percentage relative error is used to obtain the accuracies of the two models and both give good results with the neural network being almost 3 times more computationally efficient. The elasto-plastic leaf spring model, for the multi-leaf spring, is then further extended to model the behaviour of a parabolic leaf spring. It was also combined with a method that is able to capture the effect of changes in the spring stiffness due to changes in the loaded length. Qualitative validation using experimental data shows that the elasto-plastic leaf spring model is able to predict the vertical behaviour of the parabolic leaf spring. Quantitative validation also shows that the method proposed for accounting for the change in stiffness due to changes in the loaded length is able to capture this characteristic of the physical leaf spring.
Following the systematic modelling approach the elasto-plastic multi-leaf spring model is incorporated into a model of a simplified version of the physical suspension system. The quantitative validation results from this model show that the model is able to accurately predict the forces that are transmitted from the suspension system to the chassis.
Supervisor: Prof PS Els
KeSheng Wang 2011 "Approaches to the improvement of order tracking techniques for vibration based diagnostics in rotating machines"
In order to perform effective and reliable simulations in the CAE process, accurate simulation models of the product and its associated systems, sub-systems and components are required. In the vehicle dynamics context simulation models of the tyres, suspension, springs, damper, etc, are needed. This study will look at creating validated models of leaf spring suspension systems used on commercial vehicles. The primary goal set for the models are to be able to predict the forces at the attachment points where the suspension system is attached to the vehicle chassis as the models are to be used in full vehicle durability simulations. The most important component in this suspension model is the leaf spring. Leaf springs have been used in vehicle suspensions for many years. Even though leaf springs are frequently used in practice they still hold great challenges in creating accurate mathematical models. It is needless to say that an accurate model of a leaf spring is needed if accurate full vehicle models are to be created.
Conventional rotating machine vibration monitoring techniques are based on the assumption that changes in the measured structural response are caused by deterioration in the condition of the rotating machine. However, due to variations of the rotational speed, the measured signal may be non-stationary and difficult to interpret. For this reason order tracking technique is often introduced. One of the main advantages of order tracking over traditional vibration monitoring lies in its ability to clearly identify non-stationary vibration data and to a large extent exclude the influences of varying rotational speed.
This work synthesizes different order tracking techniques. Through combination, exchange and reconciliation of ideas between these order tracking techniques, three improved order tracking techniques are developed for the purpose of enhancing order tracking analysis in condition monitoring. The techniques are Vold-Kalman filter and computed order tracking (VKC-OT), intrinsic mode function and Vold-Kalman filter order tracking (IVK-OT) and intrinsic cycle re-sampling (ICR). Indeed, these improved approaches contribute to current order tracking practice, by providing new order tracking methods with new capabilities for condition monitoring of systems which are intractable by traditional order tracking methods, or which enhances results obtained by these traditional methods.
Supervisor: Prof PS Heyns
Daniel Nicolas Wilke 2010 "Approaches to accommodate remeshing in shape optimization"
This study proposes novel optimization methodologies for the optimization of problems that reveal non-physical step discontinuities. More specifically, it is proposed to use gradient-only techniques that do not use any zero-th order information at all for step discontinuous problems. A step discontinuous problem of note is the shape optimization problem in the presence of remeshing strategies, since changes in mesh topologies may, and normally do, introduce non-physical step discontinuities. These discontinuities may in turn manifest themselves as non-physical local minima in which optimization algorithms may become trapped.
Conventional optimization approaches for step discontinuous problems include evolutionary strategies, and design of experiment (DoE) techniques. These conventional approaches typically rely on the exclusive use of zero-th order information to overcome the discontinuities, but are characterized by two important shortcomings: Firstly, the computational demands of zero order methods may be very high, since many function values are in general required. Secondly, the use of zero order information only does not necessarily guarantee that the algorithms will not terminate in highly unfit local minima. In contrast, the methodologies proposed herein use only first order information, rather than only zero-th order information. The motivation for this approach is that associated gradient information in the presence of remeshing remains accurately and uniquely computable, notwithstanding the presence of discontinuities. From a computational effort point of view, a gradient-only approach is of course comparable to conventional gradient based techniques. In addition, the step discontinuities do not manifest themselves as local minima.
Dr A Oberholster 2010 "The application of Eulerian laser Doppler vibrometry to the on-line condition monitoring of axial-flow turbomachinery blades.".
The on-line condition monitoring of turbomachinery blades is of utmost importance to ensure the long term health and availability of such machines and as such has been an area of study since the late 1960's. As a result a number of on-line blade vibration measurement techniques are available, each with its own associated advantages and shortcomings. In general, on-blade sensor measurement techniques suffer from sensor lifespan, whereas non-contact techniques usually have measurement bandwidth limitations. One non-contact measurement technique that yields improvements in the area of measurement bandwidth is laser Doppler vibrometry.
This thesis presents results and findings from utilizing laser Doppler vibrometry in an Eulerian fashion (i.e. a fixed reference frame) to measure on-line blade vibrations in axial-flow turbomachinery. With this measurement approach, the laser beam is focussed at a fixed point in space and measurements are available for the periods during which each blade sweeps through the beam. The characteristics of the measurement technique are studied analytically with an Euler-Bernoulli cantilever beam and experimental verification is performed. An approach for the numerical simulation of the measurement technique is then presented.
Associated with the presented measurement technique are the short periods during which each blade is exposed to the laser beam. This characteristic yields traditional frequency domain signal processing techniques unsuitable for providing useful blade health indicators. To obtain frequency domain information from such short signals, it is necessary to employ non-standard signal processing techniques such as non-harmonic Fourier analysis.
Results from experimental testing on a single-blade test rotor at a single rotor speed are presented in the form of phase angle trends obtained with non-harmonic Fourier analysis. Considering the maximum of absolute unwrapped phase angle trends around various reference frequencies, good indicators of blade health deterioration were obtained. These indicators were verified numerically.
To extend the application of this condition monitoring approach, measurements were repeated on a five-blade test rotor at four different rotor speeds. Various damage cases were considered as well as different ELDV measurement positions. Using statistical parameters of the abovementioned indicators as well as time domain parameters, it is shown that with this condition monitoring approach, blade damage can successfully be identified and quantified with the aid of artificial neural networks.
Supervisors: Prof P S Heyns
Dr J A Olivier 2009 "Single-phase heat transfer and pressure drop inside horizontal circular smooth and enhanced tubes with different inlet configurations for transitional flow".
It is common practice to design water chiller units and heat exchangers in such a way that
they do not operate within the transition region. This is mainly due to the perceived chaotic
behaviour as well as the paucity of information in this region. Due to design constraints or
change of operating conditions, however, exchangers are often forced to operate in this region.
This is even worse for enhanced tubes as much less information within this region is available.
It is also well known that the entrance has an influence on where transition occurs, adding to
the woes of available information.
The purpose of this study is thus to obtain heat transfer and friction factor data in the
transition region of fully developed and developing flows inside smooth and enhanced tubes,
using water as the working fluid, and to develop correlations from these results. The use of
different inlets, tube diameters and enhanced tubes was also investigated with regards to the
commencement of transition.
Heat transfer and pressure drop data were obtained from six different types of tubes with
diameters of 15.88 mm (5/8!!) and 19.02 mm (3/4!!). Low fin enhanced tubes with a fin height
to diameter ratio of 0.4 and helix angles of 18" and 27" were investigated. Heat transfer was
obtained by means of an in-tube heat exchanger with the cooling of water being used as the
test fluid. Reynolds numbers ranged between 1 000 and 20 000 while Prandtl numbers were
in the order of 4 to 6. Uncertainties in heat transfer coefficient and friction factors were on
average below 2.5% and 10% respectively.
Adiabatic friction factor results showed that the use of different inlets influenced the commencement
of transition. The smoother the inlet profile the more transition was delayed,
confirming previous work done. The effect of increasing tube diameters had a slight delay in
transition. Enhanced tubes caused transition to occur at lower Reynolds numbers which was
accounted for by the fin height and not the helix angle. Heat transfer results showed that
transition occurred at approximately the same Reynolds number for all the different inlets
and enhanced tubes. This was attributed to the secondary flow forces influencing the growing
hydrodynamic boundary layer. These secondary flow forces also influenced the laminar heat
transfer and diabatic friction factors with both these parameters being higher. Turbulent enhanced
tube heat transfer results were higher than those of the smooth tube, with the tube
with the greatest helix angle showing the greatest increase. Correlations were developed for all
the tubes and their inlets and predicted all the data on average to within 3%.
Supervisors: Prof J P Meyer and Prof L Liebenberg
Dr O S Motsamai 2009 "Optimisation Techniques For Combustor Design"
Dr J Wannenburg: 2007 "A study of fatigue loading on automotive and transport structures".
Defective structural designs are mostly caused by insufficient knowledge of input data, such as material properties or loading, rather than inadequate analysis or testing methods. In particular, loads associated with automotive and transport (trucks, trailers, containers, trains) structures are nontrivial to quantify. Such loads arise from stochastic and ill-defined processes such as driver/operator actions and structure-terrain interaction. The fundamental processes involved with the determination of input loading are measurements, surveys, simulation, estimation and calculation from field failures. These processes result in design criteria, code requirements and/or testing requirements. The present study deals with methods for the establishment of input loading for automotive and transport structures. It is attempted to generalize and unify new and existing techniques into a cohesive methodology. This is achieved by combining researched current theory and best practices, with lessons learnt during application on, as well as new techniques developed for, a number of complex case studies, involving road tanker vehicles, light commercial vehicles, industrial vehicles, as well as tank containers.
Supervisor: Prof P S Heyns
Co-supervisor: Dr A D Raath
(Full text of thesis can be found here)
Dr M Thoresson: 2007 "Efficient Gradient-Based Optimisation of Suspension Characteristics for an Off-Road Vehicle"
The efficient optimisation of vehicle suspension systems is of increasing interest to vehicle manufacturers. The main aim of this thesis is to develop a methodology for efficiently optimising an off-road vehicle's suspension for both ride comfort and handling, using gradient-based optimisation. Good ride comfort of a vehicle traditionally requires a soft suspension setup, while good handling requires a hard suspension setup. The suspension system being optimised is a semi-active suspension system that has the ability to switch between a ride comfort and a handling setting. This optimisation is performed using the gradient-based optimisation algorithm Dynamic-Q. In order to perform the optimisation, the vehicle had to be accurately modelled in a multi-body dynamics package. This model, although very accurate, exhibited a high degree of non-linearity, resulting in a computationally expensive model that exhibited severe numerical noise. In order to perform handling optimisation, a novel closed loop driver model was developed that made use of the Magic Formula to describe the gain parameter for the single point driver model's steering gain. This non-linear gain allowed the successful implementation of a single point preview driver model for the closed loop double lane change manoeuvre, close to the vehicle's handling limit.
Due to the high levels of numerical noise present in the simulation model's objective and constraint functions, the use of central finite differencing for the determination of gradient information was investigated, and found to improve the optimisation convergence history. The full simulation model, however, had to be used for the determination of this gradient information, making the optimisation process prohibitively expensive, when many design variables are considered. The use of carefully chosen, simplified, two-dimensional, non-linear models were investigated for the determination of this gradient information. It was found that this substantially reduced the total number of expensive full simulation evaluations required, thereby speeding up the optimisation time.
It was, however, found that as more design variables were considered, some variables exhibited a lower level of sensitivity than the other design variables, resulting in the optimisation algorithm terminating at sub-optimal points in the design space. A novel automatic scaling procedure is proposed for scaling the design variables when Dynamic-Q is used. This scaling methodology attempts to make the n-dimensional design space more spherical in nature, ensuring the better performance of Dynamic-Q, which makes spherical approximations of the optimisation problem at each iteration step. The results of this study indicate that gradient-based mathematical optimisation methods may indeed be successfully integrated with a multibody dynamics analysis computer programme for the optimisation of a vehicle's suspension system. Methods for avoiding the negative effects of numerical noise in the optimisation process have been proposed and successfully implemented, resulting in an improved methodology for gradient-based optimisation of vehicle suspension systems.
Supervisor: Dr P E Uys
Co-Supervisor: Dr P S Els
(Full text of thesis can be found here)
Dr PS Els: 2006 "The Ride Comfort vs. Handling Compromise for Off-Road Vehicles."
Schalk Els examines the classic ride comfort vs. handling compromise when designing a vehicle suspension system using mathematical modelling and field tests.
The full vehicle, non-linear mathematical model, built in MSC ADAMS software, is verified against test data, modified to incorporate hydropneumatic springs and used to obtain optimised spring and damper characteristics for ride comfort and handling respectively. It is found that these optimised results are at opposite corners of the design space, i.e. ride comfort requires a soft suspension while handling requires a stiff suspension. The ride comfort vs. handling compromise can only be eliminated by having a controllable suspension system that can switch between a soft and a stiff spring, as well as low and high damping. This switching must occur rapidly and automatically without driver intervention.
A prototype 4 State Semi-active Suspension System (4S4) is designed, manufactured, tested and modelled mathematically. This system enables switching between low and high damping, as well as between soft and stiff springs in less than 100 milliseconds.
A control strategy to switch the suspension system between the “ride” mode and the “handling” mode is proposed, implemented on a test vehicle and evaluated during vehicle tests over various on- and off-road terrains and for various handling manoeuvres. The control strategy is found to be simple and cost -effective to implement and works extremely well. Improvements in the order of 50% can be achieved for both ride comfort and handling.
Supervisor: Prof N J Theron
(Full text of thesis can be found here)
Dr NDL Burger: 2006 "Failure analysis of ultra high molecular weight polyethylene acetabular cups."
The main aim of this study was to determine the root cause of mechanical failure of acetabular cups and to determine the origin of the excessive amount of ultra-high molecular weight polyethylene (UHMWPE) wear debris floating in the joint resulting in osteolysis.
During the study various techniques were used to analyse acetabular cups retrieved during revision surgery as well as isolating and classifying wear debris generated in vivo. The defects found were also replicated in vitro to verify the findings.
The final conclusion of this study is that excessive amounts of wear debris are generated due to the localised overheating of the bearing couple as a result of insufficient lubrication. The localised heat build-up results in excessive amounts of wear debris being generated and deposited in the joint area, resulting in osteolysis.
Supervisor: Prof P L de Vaal and Prof J P Meyer
(Full text of thesis can be found here)
Dr D J de Kock: 2005 "Optimal Tundish Design Methodology Optimal Tundish Design Methodology in a Continuous Casting Process in a Continuous Casting Process"
The promovendus's principal contribution to the knowledge in this research field has been the development of a new methodology to design the tundish of a continuous steel casting process in an optimal way. The methodology consists of combining mathematical optimisation and computational fluid dynamics in order to arrive at optimised designs using a robust and systematic process. This new methodology was successfully applied to three tundishes being operated by steel companies in South Africa. In these case studies, it is demonstrated how the design of steelmaking tundishes can be optimised in a rigorous and methodical way using different design criteria.
Supervisor: Prof Ken Craig
(Full text of thesis can be found here)
Dr C J Stander: 2005 "Condition Monitoring of Gearboxes Operating Under Fluctuating Load Conditions."
Conventional gearbox vibration monitoring techniques are based on the assumption that changes in the measured structural response are caused by deterioration in the condition of the gears in the gearbox. However, this assumption is not valid under fluctuating load conditions, since the fluctuating load will amplitude modulate the measured vibration signal and cause the rotational speed of the system to change. General monitoring of machines subject to fluctuating load conditions is dealt with by considering the constant load conditions on gearboxes or during free rotational tests.
The need to monitor the condition of large gearboxes in mineral mining equipment has attracted greater interest in order to improve asset management. An inherent need for signal processing techniques, with the ability to indicate degradation in gear condition, under fluctuating load conditions, exists. Such techniques should enable the online monitoring of gearboxes that operate under fluctuating load conditions. A continued flow of up-to-date information should consequently be available for asset and production management.
With this research, a load demodulation normalisation procedure was developed to remove the modulation caused by fluctuating load conditions, which obscures the detection of incipient gear fault conditions.
A rotation domain averaging technique is implemented which combines the ability of computer order tracking and time domain averaging to suppress the spectral smearing effect caused by the fluctuation in speed, as well as to suppress the amplitude of the vibration which is not synchronous with the rotation of the gear shaft.
It is demonstrated that the instantaneous angular speed of a gearbox shaft can be utilised to monitor the condition of the gear on the shaft. The instantaneous angular speed response measurement is less susceptible to phase distortion introduced by the transmission path when compared to conventional gearbox casing vibration measurements. A phase domain-averaging approach was developed to overcome the phase distortion effect of the transmission path under fluctuating load conditions. The load demodulation normalisation and rotation domain-averaging signal processing procedures were applied to both the conventional gearbox casing vibration and instantaneous angular speed measurements prior to the calculation of a smoothed pseudo Wigner-Ville distribution of the data. Statistical parameters such as the energy ratio were calculated from the distribution. These parameters could be monotonically trended under different load conditions to indicate the degradation of gear conditions.
Supervisor: Prof P S Heyns
(Full text of thesis can be found here)
Dr N F du Plooy: 2004 "The development of amplified vibration-absorbing isolators for tonal time-varying excitation"
In his work the candidate focused on the broadening of the effective low stiffness bandwidth of isolators by adapting system characteristics. Two novel isolators were introduced and studied. These designs were then applied to a pneumatic rock drill in an effort to reduce the vibration transmitted to their operators. High vibration levels have been linked to debilitating diseases collectively known as hand arm vibration syndrome. By using the supply air pressure to feed the air spring the device could be made self-tuning, thereby greatly reducing cost. It was also found that the vibration levels could be decreased to below 10 m/s^2 in some cases, which allows such rock-drills to legislation when used for short periods of time.
Supervisor: Prof. P S Heyns
(Full text of thesis can be found here)
For gas turbines, the demand for high-performance, more efficient and longer-life turbine blades is increasing. This is especially so, now that there is a need for high-power and low-weight aircraft gas turbines. Thus, the search for improved design methodologies for the optimisation of combustor exit temperature profiles enjoys high priority. Traditional experimental methods are found to be too time-consuming and costly, and they do not always achieve near-optimal designs. In addition to the above deficiencies, methods based on semi-empirical correlations are found to be lacking in performing three dimensional analyses and these methods cannot be used for parametric design optimisation. Computational fluid dynamics has established itself as a viable alternative to reduce the amount of experimentation needed, resulting in a reduction in the time scales and costs of the design process. Furthermore, computational fluid dynamics provides more insight into the flow process, which is not available through experimentation only. However, the fact remains that, because of the trial-and-error nature of adjusting the parameters of the traditional optimisation techniques used in this iii field, the designs reached cannot be called “optimum”. The trial-and-error process depends a great deal on the skill and experience of the designer. Also, the above technologies inhibit the improvement of the gas turbine power output by limiting the highest exit temperature possible, putting more pressure on turbine blade cooling technologies. This limitation to technology can be overcome by implementing a search algorithm capable of finding optimal design parameters. Such an algorithm will perform an optimum search prior to computational fluid dynamics analysis and rig testing. In this thesis, an efficient methodology is proposed for the design optimisation of a gas turbine combustor exit temperature profile. The methodology involves the combination of computational fluid dynamics with a gradient-based mathematical optimiser, using successive objective and constraint function approximations (Dynamic-Q) to obtain the optimum design. The methodology is tested on three cases, namely:
- The first case involves the optimisation of the combustor exit temperature profile with two design variables related to the dilution holes, which is a common procedure. The combustor exit temperature profile was optimised, and the pattern factor improved, but pressure drop was very high.
- The second case involves the optimisation of the combustor exit temperature profile with four design variables, one equality constraint and one inequality constraint based on pressure loss. The combustor exit temperature profile was also optimised within the constraints of pressure. Both the combustor exit temperature profile and pattern factor were improved.
- The third case involves the optimisation of the combustor exit temperature profile with five design variables. The swirler angle and primary hole parameters were included in order to allow for the effect of the central toroidal recirculation zone on the combustor exit temperature profile. Pressure loss was also constrained to a certain maximum.
The three cases show that a relatively recent mathematical optimiser (Dynamic-Q), combined with computational fluid dynamics, can be considered a strong alternative to the iv design optimisation of a gas turbine combustor exit temperature profile. This is due to the fact that the proposed methodology provides designs that can be called near-optimal, when compared with that yielded by traditional methods and computational fluid dynamics alone.
Supervisor: Prof J P Meyer
Co-supervisor: Prof J A Snyman
(Full text of thesis can be found here)
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