Super learner implementation in corrosion rate prediction

This thesis proposes a new machine learning model for predicting the corrosion rate of 3C steel in seawater. The corrosion rate of a material depends not just on the nature of the material but also on the material\u27s environmental conditions. The proposed machine learning model comes with a selection framework based on the hyperparameter optimization method and a performance evaluation metric to determine the models that qualify for further implementation in the proposed models’ ensembles architecture. The major aim of the selection framework is to select the least number of models that will fit efficiently (while already hyperparameter-optimized) into the architecture of the proposed model. Subsequently, the proposed predictive model is fitted on some portion of a dataset generated from an experiment on corrosion rate in five different seawater conditions. The remaining portion of this dataset is implemented in estimating the corrosion rate. Furthermore, the performance of the proposed models’ predictions was evaluated using three major performance evaluation metrics. These metrics were also used to evaluate the performance of two hyperparameter-optimized models (Smart Firefly Algorithm and Least Squares Support Vector Regression (SFA-LSSVR) and Support Vector Regression integrating Leave Out One Cross-Validation (SVR-LOOCV)) to facilitate their comparison with the proposed predictive model and its constituent models. The test results show that the proposed model performs slightly below the SFA-LSSVR model and above the SVR-LOOCV model by an RMSE score difference of 0.305 and RMSE score of 0.792. Despite its poor performance against the SFA-LSSVR model, the super learner model outperforms both hyperparameter-optimized models in the utilization of memory and computation time (graphically presented in this thesis)

Design and Simulation of Single Phase Intelligent Prepaid Energy Meter

In this paper, the design and simulation of Intelligent Prepaid Energy Meter (IPEM) has been presented. The objectives of this work  are :( i) to model an IPEM,( ii) to show its reliability on  load measurement ; and (iii) to show graphical behavior of energy consumption pattern of different loads connected to power supply.  The design methodology is Artificial Intelligent (AI) based-using “ knowledge-based” and “cognitive simulation” approach.  The intelligentce properties and expected results of the proposed digital meter was modeled into the system; and was simulated using Matlab /Simulation tool. Results obtained were very satisfactory. If  fully implemented, on one hand, the estimated bills or irregular billing imposed by Power Holding Company of Nigeria(PHCN) on her customers will stop; and on the other hand ,revenue loss through unpaid bills suffered by PHCN will greatly reduce. This will have an overall effects on the nation’s economy as revenue collection will increase. Keyword:Artificial Intelligence, Prepaid Energy Meter, Model, Simulation, Matlab/Simulin

Actualization of Nigeria’s Vision 20:2020 Through Entrepreneurial Development Culture

A worldwide consensus on the critical role of competitive markets and entrepreneurs in economic development has emerged in the last decade. In developing countries, the primary barriers to economic growth is often not so much a scarcity of capital, labour orland, as it is a scarcity of both the dynamic entrepreneurs that bring these together and the markets and mechanisms that can facilitate them in this task. The purpose of this paper is to describe the essential features of an entrepreneurial development culture in Nigeria, asit relates to vision 20:2020 and provides a sense of direction for Nigerian vision 20:2020 planners, makers of policies and government – for them to quickly realize and capitalize on entrepreneurial development culture, since it is a tool for any economy development– thus, it implies that entrepreneurial development culture is indispensable if Nigeria must actualize vision 20:2020. Conclusively, the attainment of the Nigeria’s vision 20 – 2020 and other development milieu such as Seven – Point Agenda, National EconomicEmpowerment and Development Strategy (NEEDS) and Millennium Development Goals (MDGS) etc can hardly be achieved without a very strong backing of entrepreneurial development culture. We therefore argue that entrepreneurial development culture that is based on “indigenous entrepreneur” should stand as the basis for our development as a nation

Computer aided modelling of low density polyethylene pyrolysis to produce synthetic fuels

The pyrolysis of waste low-density polyethylene (LDPE) is an excellent method of converting waste materials into useful products. Aspen HYSYS 2006 was used to develop a computational steady-state model to simulate the pyrolysis of LDPE. The Peng-Robinson fluid package was used for the simulation. A continuous stirred tank reactor with an Arrhenius kinetic expression was used to predict reaction extent and product yield. At a pyrolysis temperature of 4500C and atmospheric pressure, 92.88% liquid yield was obtained. From the given feedstock, the char obtained was composed of only elemental carbon. The synthesis gas was composed mainly Hydrogen and C1-C4 hydrocarbons with traces of n-C5 and n-C6. The Pyrolysis oil was composed of higher hydrocarbon fractions (C8-C24). The conversion temperature relationships from the simulation are in good agreement with experimental results. This proved that pyrolysis of waste LDPE can give an excellent yield of liquid product and is a viable recycling technique.Keywords: Pyrolysis, Simulation, LDPE, Synthetic fuels, Aspen HYSY

Optimisation of microchannels and micropin-fin heat sinks with computational fluid dynamics in combination with a mathematical optimisation algorithm

In recent times, high power density trends and temperature constraints in integrated circuits have led to conventional cooling techniques not being sufficient to meet the thermal requirements. The ever-increasing desire to overcome this problem has led to worldwide interest in micro heat sink design of electronic components. It has been found that geometric configurations of micro heat sinks play a vital role in heat transfer performance. Therefore, an effective means of optimally designing these heat sinks is required. Experimentation has extensively been used in the past to understand the behaviour of these heat extraction devices. Computational fluid dynamics (CFD) has more recently provided a more cost-effective and less time-consuming means of achieving the same objective. However, in order to achieve optimal designs of micro heat sinks using CFD, the designer has to be well experienced and carry out a number of trial-and-error simulations. Unfortunately, this will still not always guarantee an accurate optimal design. In this dissertation, a design methodology which combines CFD with a mathematical optimisation algorithm (a leapfrog optimisation program and DYNAMIC-Q algorithm) is proposed. This automated process is applied to three design cases. In the first design case, the peak wall temperature of a microchannel embedded in a highly conductive solid is minimised. The second case involves the optimisation of a double row micropin-fin heat sink. In this case, the objective is to maximise the total rate of heat transfer with the effect of the thermal conductivity also being investigated. The third case extends the micropin-fin optimisation to a heat sink with three rows. In all three cases, fixed volume constraint and manufacturing restraints are enforced to ensure industrial applicability. Lastly, the trends of the three cases are compared. It is concluded that optimal design can be achieved with a combination of CFD and mathematical optimisation.Dissertation (MEng)--University of Pretoria, 2011.Mechanical and Aeronautical EngineeringUnrestricte

Mushroom-mediated delignification of agricultural wastes for bio-ethanol production

Biological pretreatment is a cost-effective method of delignifying lignocellulosic biomass, making it less recalcitrant to hydrolysis into fermentable sugars. In this study, selected agricultural wastes were pretreated with mushrooms (Lentinus squarrosulus and Pleurotus ostreatus) to delignify them for bioethanol production. The substrates were supplemented with 0.2 % CaCO3, inoculated with 12 % (w/w) L. squarrosulus and Pleurotus ostreatus spawns and incubated at 25 oC for 21 days. The highest lignin removal and highest bioethanol yield of 77.45 % and 13.98 % were obtained from bean husks pretreated with L. squarrosulus. Similarly, 64.29 % and 60.92 % lignin were removed from the Pleurotus ostreatus-pretreated banana leaves and sawdust, respectively, while 12.08 % and 13.05 % bio-ethanol yields were recorded, respectively. These findings demonstrate that affordable and straightforward mushroom delignification of abundant and cheap biomass can improve hydrolysis outcomes, thus easing bioethanol production

MATHEMATICAL OPTIMIZATION: APPLICATION TO THE DESIGN OF OPTIMAL MICRO-CHANNEL HEAT SINKS

This paper documents the geometrical optimization of a micro-channel heatsink embedded inside a highly conductive solid, with the intent of developing optimal solutions for thermal management in microelectronic devices. The objective is to minimize the peak wall temperature of the heat sink subject to various constraints such as manufacturing restraints, fixed pressure drop and total fixed volume. A gradient based multi-variable optimization algorithm is used as it adequately handles the numerical objective function obtained from the computational fluid dynamics simulation. Optimal geometric parameters defining the micro-channel were obtained for a pressure drop ranging from 10 kPa to 60 kPa corresponding to a dimensionless pressure drop of 6.5 × 107 to 4 × 108 for fixed volumes ranging from 0.7 mm3 of 0.9 mm3. The effect of pressure drop on the aspect ratio, solid volume fraction, channel hydraulic diameter and the minimized peak temperature are reported. Results also show that as the dimensionless pressure drop increases the maximised dimensionless global thermal conductance also increases. These results are in agreement with previous work found in literature

Modelling the Office Rental Market in Selected Districts of Abuja, Nigeria

This study examined the drivers of office rents in selected districts of Abuja, Nigeria. These districts are Asokoro, Maitama and Utako. Primary and secondary data were utilized for the study. Primary data obtained for the study include office rental levels and office space data in the study area for the period, 2001-2012. Secondary data for the study were obtained from the National Bureau of Statistics (NBS) and the Central Bank of Nigeria (CBN) and are mainly macroeconomic variables in Nigeria for the period, 2001-2012. Using single - equation regression analysis, the office rent model developed accounted for 76%, 72% and 75% of the variation in office property rents in the commercial property market in Asokoro, Maitama and Utako districts respectively. The study also revealed that real GDP growth and vacancy rate are the major determinants of rental growth in the office property market in Asokoro and Maitama districts while real GDP growth is the major driver of office rents in Utako district. Also, Rental index for office properties in the study areas using 2001 as the base year indicates progressive upward movement in rental values of office properties in these districts within the study period. Keywords: Office Rental Determinants; Office Property Market; Office Rent Model; Nigeria

Development of high-performance self compacting concrete using eggshell powder and blast furnace slag as partial cement replacement

This study aimed to examine the properties of self-compacting concrete (SCC) developed using eggshell powder (ESP) and granulated ground blast furnace slag (GGBFS) as partial cement replacement. The coarse aggregate impact value was 21.6% and the water absorption of the fine aggregates was 24 wt%. 10 wt% partial replacement was optimal for flow-ability and workability. SCC with 20 wt% partial replacements had the highest compressive strength at 41.34 kN/mm2 and 42.4 kN/mm2 for ESP and GGBFS respectively after 28 days of curing. SCC with 20 wt% partial replacements had the highest flexural strength at 3.2 kN/mm2 for both ESP and GGBFS after 28 days of curing. From the microstructural analysis, partial replacement with mineral admixtures improved the interfacial interactions between constituents of the concrete and GGBFS SCC gave a better interfacial interaction between the concrete constituents than ESP SCC. In summary, GGBFS had better fresh, hard and microstructural properties than ESP