Browsing by Author "Isafiade, Adeniyi"

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    Open Access
    A systemic study of mining accident causality: an analysis of 100 accidents from a copper mining company in Zambia
    (2021) Mabeti, Daniel; Isafiade, Adeniyi
    The mining industry has remained Zambia's dominant industry for almost a century. According to the report by International Council for Mines and Minerals (ICMM) for 2013, Zambia is highly dependent on copper mining as the core productive industry. Mining contributes to direct employment (approximately at 1.7%), foreign direct investment (approximately at 86%), gross domestic product (more than 12%) and government revenue (more than 25%). Regardless of these economical enactments, the accident frequency across the mines is very significant. In general, the mining industry is perceived to be a high-risk industry. The increase in the number of mining accidents is extremely costly, whether measured in terms of medical expenses and disability compensation, loss of production and wages or damage to plant and equipment. The human cost, in terms of death and suffering, is beyond calculation. In recent years, there has been some innovations in terms of technology regarding mining methods, and this has resulted in decreased accident occurrence in the mines. The human factors involved in the mine accidents need to be addressed further to reduce these rates. Therefore, the best approach is first to understand mine accident causality, and then this will be a foremost step in a pursuit to diminish the high rate of accidents. Effective remedies and measures can be designed if only accident process is properly understood. The understanding and interpretation of causes of accidents at workplaces can only be achieved by accident modelling techniques. The effective way of analysing industrial accidents has been proven by the Swiss Cheese Model, which is also applicable to this study. The Swiss Cheese Model describes an accident as an event which happen within organization due to the combination of different unsafe acts which may include latent conditions and front-line operators. The purpose of this study was to determine how systemic factors contribute to accidents at a copper mining company in Zambia. The analysed results were compared with those of other local mines as well as mines from developed and developing countries. The approach in this study involves using the existing framework developed by Bonsu (2013). The framework had used the concepts from the Mark III of the Swiss Cheese Model, Incident Cause Analysis, safety management principles and the Nertney Wheel. The sections involved in the existing framework of Bonsu (2013) are metadata, accident barrier analysis and causal analysis. The accident causality section is designed and described in the same way as the Mark III version of the SCM. This section is used for analysis of accident causality and is categorized into proximal, work place and systemic factors. The metadata section offers explanations on different factors that influence the happening of accidents at this copper mining company in Zambia. Metadata section captures the information on accidents analysed under the barriers and causing agency section of the framework. The variables under the metadata are time and date of accident, place of the accident, accident type, activity involved which resulted in the accidents, task schedule of the accidents, age of the victim, experience of the victim, job status, etc. The last section of the existing framework is the agency and barrier analysis and was designed by Bonsu (2013) to capture data on the safety barriers which were breached and accident causing agents in the accident report. The accident reports collected from the copper mining company in Zambia were used in the existing framework and the analysed results were presented as unsafe acts, workplace and systemic factors with linkages to each other. The most prominent type of unsafe acts recognized were routine violation (recognized in 38% of all the accident analysed), closely followed by slips and lapses (identified in 30%) and then mistakes (21%). Exceptional violation and non-human cause were the lowest at 9% and 2% respectively. Systemic and workplace factors were involved in 78.2% of the accident reports that were analysed. The most prominent workplace factor recognized was behavioural environment (25.8% of all cases analysed), closely followed by physical environment (23.4% of all cases analysed), then unsafe work practices (18.8% of the accidents analysed), then fit-for purpose equipment (16.4% of the accidents analysed) and finally competent people (15.6% of the accidents analysed). In general, under the category of accident analysis on workplace factors, all the five factors were significantly contributing to the causes of accidents at the mine site that was investigated as demonstrated by the closeness in percentages. In the case of systemic factors, inadequate supervision or leadership was the most prominent factor identified (22.6% in all accidents analysed). It was also found that physical environment (23.4% of all cases considered) was the second most dominant workplace factor recognized. The results obtained also revealed that some systemic factors were associated with specific workplace factors more than others. For instance, the result of behavioural environment (workplace factor) was usually due to poor leadership problem (systemic factor), problems seen in housekeeping (systemic factor), hazard identification (systemic factor), risk management (systemic factor), and designs (systemic factor), these were also the causes of poor physical environment. In the unsafe work practices (workplace factor), hazard identification was the most common systemic factor that was recognized whereas in fit for purpose equipment (workplace factor) the most common associated systemic factors were risk management, leadership, hazard identification and design. The results obtained in this study were compared to those obtained in the study of Mwansa (2021), which also applied the framework used in this study to the analysis of accident reports from another mine site of the same mining company in Zambia as used in this study. Similarities and differences were obtained under the accident characterization and causation sections. The operations in both studies are different in terms of mining methods and metallurgical processing plants. This may be responsible for some of the differences in the results obtained in both studies. For instance, in Mwansa's (2021) study, the most dominant unsafe act recognized was also routine violation (36% of all cases considered) whereas the most prominent workplace factors recognized were physical environment (36% of all cases considered) and unsafe work practices (27% of all cases considered). In Mwansa's (2021) study, the most prominent systemic factors recognized as contributing to physical environment were hazard identification, work schedule, risk management, maintenance management, leadership, housekeeping, and contractor management. The results obtained in this study were also compared with previous studies from different commodities across the globe. This was done to have broader picture when dealing with mine accidents. The causes of accidents identified in this study are of significance to the safety of the industry. Overall, based on the analysis carried out in this study for the copper mining site investigated, it can be concluded that systemic factors are the main causes of accidents rather than human error and violations.
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    Open Access
    Integrated renewable energy polygeneration networks: a multi-objective optimisation and game theoretic approach
    (2025) Chitsiga, Takudzwa Brian; Isafiade, Adeniyi
    Renewable energy integration and process optimisation have been employed to address the ever-increasing concerns regarding energy security and pollutant emissions worldwide. Mathematical modelling, paired with game theory principles, can optimize decision-making among stakeholders, enhancing resource allocation and strategic planning. Furthermore, the necessity of industrial symbiosis becomes evident, as it promotes the efficient exchange of resources between different processes, reducing waste and enhancing sustainability. The modelling of these approaches facilitates detailed experimentation without the associated costs and risks of setting up real-life prototypes. In line with this approach, this dissertation presents an integrated resource network model that includes a bioenergy supply chain and a polygeneration hub. The objective is to optimally allocate renewable fuel, and a fossil fuel backup, to the polygeneration hub while optimally distributing the utilities produced to supply industrial and residential demand. The method used involves a 3-layer superstructure. The first layer consists of a supply chain network that includes seasonally available renewable and non-renewable energy sources, linked to the second layer through a transport system made up of railways, roads, and pipelines. The second layer, the polygeneration hub, contains a boiler for generating high-pressure steam, steam turbines for power production, a multi-effect evaporation system for desalinating seawater, and an absorption refrigeration system to produce chilled water. This layer also includes the option of connecting the boiler to a solar-thermal and heat storage subnetwork for preheating boiler feedwater. Piping and electrical cables connect the polygeneration hub to the third layer, which meets industrial heat demand through a heat exchanger network and electrical power demand. The generated model, which is a mixed-integer non-linear program, is applied to two case studies. The first case study provides valuable insights into the impact of weighting factors on cost and emissions, highlighting the model's decision-making process under varying renewable fuel availability and objective preferences. The second case study extends the model's applicability by incorporating cooperative game theory, showcasing its potential to enhance industrial symbiosis and achieve significant cost savings through strategic collaboration. In the first case, a multi-objective function with an equal weighting between total annual cost and CO2 emissions is used. A total annual cost of 40.2 ×106 $/y and emissions of 73.7 × 106 t/y CO2 is obtained. Furthermore, a sensitivity analysis is conducted to determine the effect of changes in biomass availability and weighting factors in the multi-objective function on the solution. The solution reveals that the model prefers to exhaust the supply capacity of the cheapest biomass with lowest carbon composition, before moving on to the next. As a last resort, the model uses fossil fuel to meet the set energy demand. A change in weighting factors in the multi-objective function in favour of economics results in lower total annual cost values, achieved by using cheaper fuel and transport, and reducing number of units in the heat exchanger network and multi-effect evaporation system. When the weighting factor is changed to favour of emission reduction, lower CO2 emission values are obtained by the incorporation of solar thermal energy and increasing the number of units in the heat exchanger network and multi-effect evaporation system. In the second case study, the subnetworks in the superstructure from the first case are treated as individual participants within an industrial symbiosis network, with the potential to engage in a cooperative game. The objective function for this scenario aims to minimise the sum of the marginal contributions of each participant, assigning equal weighting to each, toward the coalition's total annual cost. The results indicate a preference for forming a coalition among the combined heat and power, multi-effect evaporation, and the heat exchanger network. This had the highest cost savings of 465.5 ×105 $/y.
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    Open Access
    Synthesis of integrated solar thermal networks for domestic and industrial utilization
    (2021) Abikoye, Semilore Ben Olaoluwa; Isafiade, Adeniyi; Čuček, Lidija
    This study involves the development of generic multi-period Mixed Integer Non-Linear Programming (MINLP) based design and optimization methods for integrating solar thermal with domestic and industrial heat networks over multiple time frames based on discrete time intervals/periods. The study also presents a new simultaneous multi-period modelling and design framework for increasing thermal output of an integrated solar thermal-heat pump system. Detailed MINLP superstructure based design and optimization technique is used for the proposed designs while the synthesis of the heat networks was implemented and solved simultaneously in General Algebraic Modelling Systems (GAMS) using SBB solver. The first aspect of the thesis deals with the development of design and optimization model for direct and indirect integration of feasibly attainable solar thermal with industrial heat network. In the model, periodic changes in demand and supply sides of the industrial heat network superstructure, including periodic changes in the amount of heat stored in thermal storage tank, are accounted for using discretized time periods. The developed model was then applied to three kinds of integration scenario for industrial heating which includes pre-heating of single cold stream, targeting of a definite cold stream among multiple industrial cold streams, and pre-heating of multiple cold streams within the heat network. The second part of the study introduces the developed design and optimization model for integrating solar thermal with the heat network of residential buildings. The residential heat network includes water and space heating, periodic heat storage and backup utility, while other essential attributes of the design are incorporated and accounted for periodically in the proposed model. The case study considered involves solar thermal integration with heat supply network of a cluster of buildings considering heat storage and the varying heat requirement profiles of each building in the network. In the case study, two heat storage design alternatives incorporating combined water and space heating networks for three different types of building designs in Slovenia were investigated for the proposed residential integration of solar thermal network. The third aspect of the study presents a multi-period mathematical programming approach for simultaneous design and optimization of a solar thermal source multi-stage heat pump cycle for low/medium temperature heat production. The proposed model accounts for the intermittent changes in solar irradiation and ambient temperatures, as well as their effects on heat output from the system, while the dynamic operating conditions and thermodynamic features of the integrated system are also accounted for according to diverse ambient temperatures. The conceptual framework for the combined solar thermal-heat pump design rests on the idea that the thermal output of solar heat network designs, such as those described in the first two parts of the thesis, could be further enhanced by incorporating heat pump technology with the solar thermal network. The results obtained from the studies indicate good prospect for solar thermal integration with domestic and industrial heat networks; it also offers opportunities for enhanced solar heat output through systematic combination of solar thermal with heat pump cycle. For the case of industrial cold stream pre-heating, the results obtained show that the average attainable solar heat increases (i.e. by 80.9 W/m2 ) up to collector area of about 6,500 m2 , beyond which the average solar heat attainable increase dropped to 16.7 W per additional m2 of collector area up to 10,000 m2 . However, for the selected case study of a dairy plant, an average solar heat output of about 75 W/m2 of collector is obtained with linear increase in the average attainable heat load up to certain collector area (on case- by-case basis), after which it is observed that further increase in collector area does not result in much increase in the obtained heat load. For the first design alternative in the integrated residential solar thermal with heat storage network study, the results show that about 7.4 % of the total heat required by the buildings (for water and space heating) in winter months could be satisfied by solar thermal while the total heat demand for water heating in summer months could be fully satisfied by solar. Whereas the result obtained from the second design with a single heat storage tank shows that for collector area of about 18.8 m2 , only 25% of the energy required in the buildings could be satisfied by solar while for a collector area of 601.2 m2 , up to 92% of heat demand could be satisfied by solar. The results for the integrated solar thermal and heat pump systems show relative operational stability in the heat output regardless of season with 4,904.9 kW and 4,714.8 kW of heat harvested from the system in March and August respectively at an average coefficient of performance of 1.68. The models developed in this thesis are generic in that the model equations are formulated independent of the data. Hence, they can be applied to any integrated solar heating network in any location with known geographical coordinates and meteorological information.