Department of Mechanical Engineering
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Item Understanding casting behaviour of low carbon high manganese steel through detailed characterization of mould powder and mould top slag(Taylor and Francis, 2023-02-02) D. Paswan; J. K. Ansu; Adekunle Akanni Adeleke; Peter Pelumi Ikubanni; C. T. Christopher; T. K. Roy; P. Palai; M. MalathiThis study focused on multistage characterization techniques in developing an understanding of the abnormal casting behaviour of low carbon high manganese (LCHMn) steel. In addition to raw mould powder used for casting LCHMn steel, mould top slag samples were also collected for normal and abnormal casting conditions. Raw mould powder and top slag samples were characterized using XRF, XRD, and SEM-EDS to determine chemical composition, crystallinity and morphology. The chemical composition results revealed deviation of normal and abnormal behaviours from the mould powder due to the pickup of oxides of Al, Mn, and Ti. The SEM analyses of raw mould powder showed different granular particle sizes while pores and glassy/crystalline structure were seen for normal and abnormal behaviour at casting. CaF2, CaSiO3, and Na2CaSi3O9 were revealed as the mineralogical phases. There was a modified crystalline phase present in the abnormal behaviours at casting due to pickup of other oxides.Item Essential basics on biomass torrefaction, densification and utilization(Wiley, 2020-09-24) Adekunle Akanni Adeleke; Jamiu Kolawole Odusote; Peter Pelumi Ikubanni; Olumuyiwa A. Lasode; Madhurai Malathi; Dayanand PaswanTorrefaction and densification are crucial steps in upgrading biomass as feed-stock for energy generation and metallurgical applications. This paperattempts to discuss essential basics on biomass torrefaction and densification,which can propel developing nation to take full advantage of them. The mostpromising clean energy sources that have found applications in various areasare biomass materials, that is, both the lignocellulosic and non-lignocellulosi c.However, high moisture contents, low energy density, hydrophilic nature, poorstorage and handling properties are the major drawbacks limiting its useful-ness. Therefore, torrefaction as one of the major thermal pre-treatment pro-cesses to upgrade biomass in terms of improved energy density, hydrophobic,moisture content and grindability has been discussed. The influence of temper-ature, residence time, particle sizes and gas flow rates on the properties of tor-refied biomass has also been discussed. The advantages and disadvantages ofvarious torrefaction technologies have also been highlighted. The possibleareas of application of torrefied biomass especially densification into pelletsand briquettes alongside the equipment required for it have been reviewed inthis paper. The torrefied biomass can be deployed in the metallurgical indus-tries as reducing agent in the development of sponge iron from iron ores ofvarious grade including lean ones. The information gathered in this paperfrom peer-reviewed articles will reduce the burden of seeking to understandthe preliminaries of torrefaction process and its importanceItem Electrochemical Studies of the Corrosion Behavior of Al/SiC/PKSA Hybrid Composites in 3.5% NaCl Solution(MDPI, 2022-09-30) Peter Pelumi Ikubanni; Makanjuola Oki; Adekunle Akanni Adeleke; Olanrewaju Adesina; Peter Omoniyi; Esther AkinlabiThe corrosion behavior of metal matrix composites (MMCs) is accelerated by the inclusion of reinforcements. Hence, this study investigates the corrosion behavior of MMCs produced from Al 6063 matrix alloy with reinforcement particulates of silicon carbide (SiC) and palm kernel shell ash (PKSA) inclusion at different mix ratios. The MMCs were synthesized using the double stir casting technique. The corrosion behaviors of the composites in NaCl solutions were studied via gravimetric analysis and electrochemical measurements. The gravimetric analysis showed fluctuating dissolution rate of the samples in NaCl solution to indicate flawed film as well as corrosion product formation over the surface of the specimens. The observed corrosion mechanism of the samples was general and pitting corrosion. The presence of reinforcements within the Al6063 matrix acted as active sites for corrosion initiation. The range of values for Ecorr and Icorr obtained in 3.5% NaCl at 24 h was between −220.62 and −899.46 mV and between 5.45 and 40.87 µA/cm2, respectively, while at 72 h, the Ecorr values ranged from 255.88 to −887.28 mV, and the Icorr ranged from 7.19 to 16.85 µA/cm2. The Nyquist and Bode plots revealed the electrochemical corrosion behavior of the samples under investigation, with predominant reactions on the surface of the samples linked to charge transfer processes. The relative resistance to corrosion of the samples depends on the thin oxide film formed on the surface of the samples.Item DEVELOPMENT AND ASSESSMENT OF PARTICLE REINFORCED ABRASIVE GRINDING DISCS FROM LOCALLY SOURCED MATERIALS(Journal of Chemical Technology and Metallurgy, 2024-09-09) Jamiu Kolawole Odusote; Adekunle Akanni Adeleke; Peter Pelumi Ikubanni; Timothy Adekanye; Adeiza Avidime Samuel; Chinedum OjiManagement of waste materials is a serious concern to researchers and scientists. Waste materials cause health and environmental hazards. Hence, they should be properly managed. The aim of this study is to develop a grinding disc using agricultural wastes (palm kernel shell and snail shell), granite, aluminium oxide, and polyester resin. The particles of snail shell, palm kernel shell, aluminium oxide (abrasive) and granite (friction modifier) were measured in percentages varying between 8 - 29 wt. % and were mixed with 27 wt. % polyester resin (binder), 3 wt. % methyl ethyl ketone peroxide (hardener) and 3 wt. % cobalt naphthalene (accelerator) to produce a grinding disc. The micrograph, hardness, wear rate, and water absorption tests were carried out on the grinding disc samples. The result showed that the composition with the highest palm kernel shell particle content (29 wt. %) had the best values for hardness and wear resistance, making it the most suitable material for grinding discs. The environmentally-friendly palm kernel shell-based discs could be used for soft metals, wood grinding and finishing processes.Item Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model(Hindawi, 2023-02-06) Moses Oluwatobi Fajobi; Olumuyiwa A. Lasode; Adekunle Akanni Adeleke; Peter Pelumi Ikubanni; Ayokunle O. Balogun; Prabhu ParamasivamOne of the major challenges confronting researchers is how to predict biogas yield because it is a herculean task since research in the field of modeling and optimization of biogas yield is still limited, especially with the adaptive neuro-fuzzy inference system (ANFIS). This study used ANFIS to model and predict biogas yield from anaerobic codigestion of cow dung, mango pulp, and Chromolaena odorata. Asides from the controls, 13 experiments using various agglomerates of the selected substrates were carried out. Cumulatively (for 40 days), the agglomerate that comprised 50% cow dung, 25% mango pulp, and 25% Chromolaena odorata produced the highest volume of biogas, 4750 m3/kg, while the one with 50% cow dung, 12.5% mango pulp, and 37.5% Chromolaena odorata produced the lowest volume of biogas, 630 m3/kg. The data articulated for modeling were those of the optimum biogas yield. Data implemented for modeling comprised two inputs (temperature in Kelvin and pressure in kN/m2) and one output (biogas yield). The Gaussian membership function (Gauss-mf) was implemented for the fuzzification of input variables, while the hybrid algorithm was selected for the learning and mapping of the input-output dataset. The developed ANFIS architecture was simulated at varied membership functions, MFs, and epoch numbers to determine the minimum root mean square error, RMSE, and maximum R-squared R2 values. The one that fulfilled the conditions was considered to be the optimized model. The minimum RMSE and maximum R2 values recorded for the developed model are 14.37 and 0.99784, respectively. The implication is that the model was able to efficiently predict not less than 99.78% of the experimental data. These results prove that the ANFIS model is a reliable tool for modeling data and predicting biogas yield in the biomass anaerobic digestion process. Therefore, the use of the developed ANFIS model is recommended for biogas producers and other allies for predicting biogas yield adequately.Item Machine Learning Model for the Evaluation of Biomethane Potential Based on the Biochemical Composition of Biomass(BioEnergy Research, 2023-09-30) Adekunle Akanni Adeleke; Jude A. Okolie; Chukwuma C. Ogbaga; Peter Pelumi Ikubanni; Patrick U. Okoye; Olugbenga AkandeBiomethane potential (BMP) is often used to evaluate the biogas potential during anaerobic digestion (AD). However, BMP tests are complex and time-consuming. Therefore, the present study presents a hybrid model in machine learning (ML) for evaluating and predicting BMP based on biomass biochemical composition. Generative adversarial network (GAN) is combined with different ML models to model and predict BMP for different biomass materials. The models were trained on 64 experimental datasets (original datasets) and a combination of a GAN and the original datasets (augmented datasets). The gradient boost regression (GBR) model performed very well on the training set with both datasets compared to the support vector machine (SVM), Artificial neural network (ANN), and random forest (RF). RF and GBR models performed very well when trained with the combined GAN and original datasets, with RF slightly outperforming GBR on the test datasets (R2 score of 0.9106 vs. 0.9177). This indicates that the models benefit from the additional data generated by the GAN. The GBR model trained with the GAN and original datasets combined outperformed the RF model on the test set, with an R2 score of 0.9177 vs. 0.9106. A comparison between three different hyperparameter optimization methods (grid search, particle swarm optimization, and Bayesian optimization) showed that the grid search optimized model offers a balanced performance with an R2 score of 0.9994 and a marginal improvement on the test set with an R2 of 0.9213. Feature analysis results demonstrate that cellulose has the most influence on BMP.Item Mechanical properties and stress distribution in aluminium 6063 extrudates processed by equal channel angular extrusion technique(Taylor and Francis, 2023-08-08) T.M. Azeez; L. O. Mudashiru; Tesleem B. Asafa; Adekunle Akanni Adeleke; Adeyinka Sikiru Yusuff; Peter Pelumi IkubanniThis study investigated the effect of temperature and load on the mechanical properties and stress distribution in ECAE processed Al6063. Samples were extruded at temperatures of 350, 425 and 500 under applied loads of 1000, 1100 and 1200 kN and ram speed of 5 mm/s. Hardness and tensile strength of all the extrudates were measured with Rockwell hardness tester and universal testing machine, respectively. Stress distribution in the extrudates was simulated with qform software under different extended applied loads and temperatures. Experimental results showed that billet temperature influenced tensile strength and hardness more significantly than applied load. The grains in the extrudates also became more refined as billet temperature increased. Simulation results indicated that more uniform stress distribution with lower magnitude was observed in the extrudates with increased billet temperature. The hardness and tensile strength of the extrudates as revealed through the uniform stress distribution were enhanced.Item Green Corrosion Inhibition Practices(IEEE, 2023-11-01) Petrus Nzerem; Adekunle Akanni Adeleke; Ayuba Salihu; Esther Nneka Anosike-Francis; Adeiza Avidime Samuel; Adebayo Isaac Olosho; India Chiazokam Odezugo; Jachimike Agbo Samuel; Peter Pelumi IkubanniCorrosion poses significant challenges for industries worldwide, causing financial losses, safety risks, and environmental issues. To address these concerns, there has been a shift towards sustainable corrosion prevention techniques. This review presents a summary of corrosion, corrosion inhibitors, and specifically focuses on green corrosion inhibitors. It discusses relevant literature exploring various types of green inhibitors to mitigate corrosion. Additionally, it highlights recent progressions in the application of green corrosion inhibitors. The insights presented in this paper enable researchers, engineers, and business experts to adopt sustainable corrosion prevention solutions.Item A comprehensive review of hydrogen production and storage: A focus on the role of nanomaterials(The University of Edinburgh, 2022-05-20) Emmanuel I. Epelle; Kwaghtaver S. Desongu; Winifred Obande; Adekunle Akanni Adeleke; Peter Pelumi Ikubanni; Jude A. Okolie; Burcu GunesNanomaterials are beginning to play an essential role in addressing the challenges associated with hydrogen production and storage. The outstanding physicochemical properties of nanomaterials suggest their applications in almost all technological breakthroughs ranging from catalysis, metal-organic framework, complex hydrides, etc. This study outlines the applications of nanomaterials in hydrogen production (considering both thermochemical, biological, and water splitting methods) and storage. Recent advances in renewable hydrogen production methods are elucidated along with a comparison of different nanomaterials used to enhance renewable hydrogen production. Additionally, nanomaterials for solid-state hydrogen storage are reviewed. The characteristics of various nanomaterials for hydrogen storage are compared. Some nanomaterials discussed include carbon nanotubes, activated carbon, metal-doped carbon-based nanomaterials, metal-organic frameworks. Other materials such as complex hydrides and clathrates are outlined. Finally, future research perspectives related to the application of nanomaterials for hydrogen production and storage are discussed.Item CORROSION BEHAVIOR OF Al/SiC/PKSA HYBRID COMPOSITES IN 1.0 M H2SO4 ENVIRONMENT USING POTENTIODYNAMIC POLARIZATION TECHNIQUE(SCICELL, 2022-12-13) Peter Pelumi Ikubanni; Makanjuola Oki; Adekunle Akanni Adeleke; Emmanuel Ajisegiri; Moses FajobiThe potentiodynamic polarization of aluminium 6063 alloy reinforced with silicon carbide (SiC) and palm kernel shell ash (PKSA) particulates at various mixing ratios were investigated. Double stir casting method was adopted for the production of the hybrid reinforced composites. The existence of the reinforcements within the matrix alloy acted as active sites for corrosion initiation. Hence, pitting corrosion was observed. The range of values for Ecorr and Icorr obtained at 24 h in 1.0 M H2SO4 were between -627.74 and -644.46 mV, and between 423.81 and 860.23 µA/cm2, respectively. The Ecorr values ranged from -654 to -697.22 mV, and the Icorr ranged from 1075.65 to 3057.16 µA/cm2 at 72 h in 1.0 M H2SO4. The relative resistance to corrosion of the samples is dependent on the thin oxide film formed on the surface of the samples.