Browsing by Author "Isafiade, Adeniyi Jide"

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    Open Access
    Assessment of pre-treatment technologies for bio-ethanol production using multi-objective optimisation
    (2015) Crimes, Joanne; Isafiade, Adeniyi Jide; Fraser, Duncan
    South Africa’s liquid fuels have a large carbon footprint due to coal- to -liquid fuels however, this could be reduced by blending bio-ethanol in the fuel. It is estimated that 3.3 Mt/year of sugarcane bagasse, a non-food biomass, could be available for biofuel production in South Africa if steam generation from bagasse at the sugarcane mills was more efficient (Lynd et al., 2003). Bagasse comprises lignocellulose which does not contain free sugars, but requires pre-treatment so as to promote access to polysaccharides for hydrolys is to sugars prior to fermentation to ethanol. Lignin present in bagasse prevents access to cellulose, thus lignin is often solubilised in a basic solution prior to hydrolysis. A variety of methods exist for pre-treating bagasse which require different raw materials and have different operating conditions, and thus have different costs and environmental impacts associated with them. In order to determine an optimal pre-treatment network of sugarcane bagasse for the production of bio-ethanol, a systematic procedure which considers economics and environmental impact as objectives should be employed. This thesis uses a systematic approach to develop mixed integer non-linear programs (MINLPs) of pre- treatment options for sugarcane bagasse. The superstructure of pre-treatment options is aimed at embedding the key pre-treatment alternatives, and the optimisation of each of these alternatives is performed using GAMS (General Algebraic Modelling System). The superstructure incorporates the following pre-treatment options: acid pre-treatment and steam explosion (acid-catalysed and un- catalysed), and both acid and enzymatic hydrolysis. The use of delignification using sodium hydroxide prior to hydrolysis was investigated. The benefits of producing methane from the xylose-rich liquid leaving the pre-treatment unit were also included. The superstructure, which embeds the aforementioned pre-treatment options, was developed using insights obtained from detailed modelling and simulation of some key aspects of individual unit operations involved in possible pre-treatment flowsheets. The acid pre-treatment unit was developed in Matlab using reaction kinetic data to generate 13 sets of black box data at differing acid weight percentages and temperatures. The two steam explosion methods and the enzymatic hydrolysis unit, used black box data obtained from Aspen Plus simulations from CTBE (Brazilian Bio-ethanol Science and Technology Laboratory ) (Bonomi, Dayan, Jesus, Cunha, & Mantelatto, 2011). Kinetic equations describing the acid hydrolysis of cellulose were included directly in the GAMS model for acid hydrolysis. Linear relationships describing the solubilisation of solid components with sodium hydroxide weight percentage during delignification were used in the delignification model. The superstructure was decomposed into fixed flowsheets, which involved all possible combinations of these models. The optimal pre-treatment flowsheet was s then chosen based on both economic and environmental objectives by evaluating the solution space. It was found that recycling of sodium hydroxide is needed for profitability in the delignification flowsheets. A recycle cost of 25% of the total annual sodium hydroxide cost with no recycling was used in the flowsheets although the recovery process could possibly be more efficient. However, adding delignification reduced the profitability of all flowsheets except steam explosion with enzymatic hydrolysis. Acid-catalysed steam explosion with acid hydrolysis was one of the most profitable flowsheets and had the lowest environmental impact, however the glucose flowrate produced by this flowsheet was low. Acid-catalysed steam explosion followed by enzymatic hydrolysis produces more glucose and was more profitable however, the environmental impact of this method may be very large due to the use of enzymes. Enzymes (excluding transportation) can contribute significantly to environmental impact if the production method is energy intensive and the e energy production method is carbon-intensive method . More research into the environmental impact of enzymes should be conducted to determine which hydrolysis method should be chosen.
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    Interval based MINLP superstructure synthesis of heat and mass exchange networks
    (2007) Isafiade, Adeniyi Jide; Fraser, Duncan McKenzie
    This study presents a new technique for synthesizing heat and mass exchange networks. The method involves generating superstructures using the temperature/composition interval concept from the physical insight approach. The superstructures are partitioned into temperature/composition intervals using the supply and target temperatures/compositions of either the hot/rich or cold/lean set of streams. The opposite kind of streams are made to participate (float) in all the intervals defined. Their ability to exchange heat/mass in these intervals is however subject to thermodynamic feasibility. The resulting superstructure is optimised as a mixed integer non linear programming (MINLP) model. The superstructure is hot/rich streams based if hot/rich streams are used to define the intervals otherwise it is cold/lean stream based.
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    Open Access
    Optimisation of South Africa's biomass to bio-ethanol supply chain network
    (2016) Mutenure, Mildred; Isafiade, Adeniyi Jide; Fraser, Duncan
    This study is about the optimisation of bio-ethanol supply chains for economic and environmental objectives, using a mathematical programming approach. A superstructure presented as a Mixed Integer Linear Programme (MILP) model that adequately captures the key variables in South Africa's bio-ethanol supply chain network is developed. The MILP model accounts for food demand, geographical distribution of biomass cultivation areas and biomass diversity, feedstock, product and by-product distribution, product demand and tax subsidies. The study focuses on the use of sugarcane, bagasse and crop waste from maize, wheat, barley and sorghum in the production of bio-ethanol. In the supply chain, one processing technology for ethanol production is considered and one mode of transportation for both feedstock and products is considered. A detailed profitability analysis of the optimised MILP model is also provided. To account for the environmental impact of the supply chain, the model is integrated with life cycle analysis through multi-objective optimisation. The ε- constraint method is used to solve the multi-objective optimisation problem and Pareto analysis is done to check the trade-offs between the economic and environmental objectives, which is measured mainly by greenhouse gas emissions. In addition to greenhouse gas emissions, other impact categories namely eutrophication, human toxicity, acidification and global warming potential were also considered. Bio-ethanol production has been a subject of many studies. It is a renewable and potentially environment-friendly product, which after blending with petrol can be used as a fuel in the transport sector. The use of bio-fuels has the potential to relieve pressure on fossil-based fuels, and achieve a reduction in the emissions of greenhouse gases. The use of bio-fuel results in net savings in carbon dioxide gas emissions as plants absorb the carbon dioxide released during bio-fuel production during biomass cultivation. The bio-fuel industry worldwide, however, faces many challenges, which compromises its economic viability and commercialisation, especially where lignocellulosic biomass is to be used in bio-fuel production. These challenges include the uncertainty or discontinuous availability of biomass, fluctuations in market prices, high logistics and high maintenance costs of the processing equipment. The high logistics costs arise from the low density of the feedstock and from distribution of the feedstock, which is usually scattered over a wide area thereby making the process energy intensive. To overcome these challenges, an optimised supply chain network is required.
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    Synthesis of optimal heat and mass exchange networks using a two-step hybrid approach including detailed unit designs
    (2017) Short, Michael; Isafiade, Adeniyi Jide
    This PhD thesis develops a methodology for the synthesis of optimal heat and mass exchanger networks through a novel hybrid method. The two-step procedure makes use of simplified exchanger models in a network optimisation step, followed by a detailed design where the exchangers found in the network synthesis step are modelled in detail. Subsequent iterations of the network design step are then updated with information from the detailed network designs. The algorithm has certain advantages over previous methods in that the network optimisation is based on more realistic representations of the actual units therein and also that the method increases the likelihood of attaining a globally optimal solution through the generation and assessment of multiple candidate networks throughout the algorithm. The method can be used in a variety of applications and is demonstrated to be effective for large problems and multi-period scenarios. The thesis also shows that the method can be used in conjunction with multiple individual unit optimisation techniques including heuristics and fully explicit optimisation methods.
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    A sytemic study of mining accident causality : an analysis of 91 mining accidents from a platinum mine in South Africa
    (2013) Bonsu, Jude; Isafiade, Adeniyi Jide
    The mining industry is a very important sector of the South African national economy. A major factor threatening the sustainability of this industry is the worrying effect of mining accidents. These accidents usually lead to the destruction of property, injury/death of mine workers, and pollution of the environment. Although mining is generally seen as a hazardous operation worldwide, the accident rates in South African mines are still unacceptably high. Another worrying phenomenon is the fact that since 2003 reduction in fatalities and injuries has been 20– 25% short of annual targets set by stake holders. These factors make the safety of the industry a very important subject. The understanding of accident causality is a major step in the quest to reduce accidents. It is only with a good understanding of the accident process that effective remedies can be designed. Accident modelling techniques provide the necessary platform for the interpretation and understanding of accidents at workplaces. The Swiss Cheese Model of accidents has proven to be a very efficient way of analysing industrial accidents. In this model, an accident is seen as a combination of unsafe acts by front line operators and latent conditions in the organization. The model helps to identify factors in an organizational structure that influence human behaviour/performance at workplaces. This study is aimed at demonstrating how a systemic approach can be applied to the analysis of the causes of accidents in South African mines. In this study, an accident analysis framework has been developed from the Swiss Cheese Model, combining the Mark III version of the Swiss Cheese Model, the Nertney Wheel and safety management principles. The main section of the framework is made up of three layers of accident causality: proximal causes, workplace factors and systemic factors. The second section (metadata) of the framework incorporates contextual data pertaining to each accident such as age, experience, task being performed, and time of accident. These data enhance the understanding of accident causality. The third and final section of the framework incorporates information about accident causing agencies and the nature of barriers breached in the accident process.