Research Articles in Mechanical Engineering

Permanent URI for this collectionhttps://repository.nileuniversity.edu.ng/handle/123456789/130

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Subject: search.filters.subject.Engineering (General). Civil engineering (General)

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    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 Paramasivam
    One 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.
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    Energy from biomass and plastics recycling: a review
    (Taylor and Francis, 2021-01-01) Samuel Oluwafikayo Adegoke; Adekunle Akanni Adeleke; Peter Pelumi Ikubanni; Chiebuka Timothy Nnodim; Ayokunle Olubusayo Balogun; Olugbenga Adebanjo Falode; Seun Olawumi Adetona
    The sustainability of fossil fuel is not guaranteed as it is gradually depleting. Alternative ways to this challenge are to generate biofuel from biomass and plastic solid wastes. Many studies have been done on the actualization of these alternatives. Hence, this study accumulates research from multidiscipline for the purpose of advancing biofuel production for sustainable energy. The necessary information needed by scientists having interest in biofuel production, including government policy, biomass selection, different conversion techniques and different ASTM standards for biodiesel properties are entrenched in this study. For vast biofuel production, there is a need for a collaborative work among fields from microbiologist, biochemist to engineering for the development of innovations, growth of cells, understanding of genetic engineering of algae strains and optimization of biofuel production. Also, a review on the recovery and recycling process of plastic solid waste was done. This is to ensure that the use of plastic solid waste to support energy sustenance will lead to no energy is wasted. Various ASTM standards for investigating the different properties of bio-oil were reviewed. The numerous plastic wastes that have not been utilized in the production of biofuel can be investigated to reduce the environmental pollution.
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    Electrochemical investigation of the corrosion susceptibility of hybrid reinforced Al6063 with SiC and PKSA in 1.0 M sulfuric acid environment
    (Wiley, 2023-07-24) Peter Pelumi Ikubanni; Makanjuola Oki; Adekunle Akanni Adeleke; Akintunde Sunday Onaolapo; Prabhu Paramasivam
    The recycling of agro-waste as complementary reinforcements has received significant recognition in the development of aluminium matrix composites. Hence, this study examines the corrosion behavior of Al6063 reinforced with hybrid SiC/PKSA (palm kernel shell ash) particles. Through various ratios of SiC and PKSA particles in Al6063 alloy, composites were fabricated by double stir casting. Samples were cut and metallographically prepared for 1 M H 2 SO 4 solution corrosion experiments. Gravimetric, potentiodynamic polarization and electrochemical impedance spectroscopic analyses were employed. The composites corroded initially at relatively high rates, gradually declining during long immersion times in the acidic solution. The intersection of reinforcements at the general surfaces of the composites where flawed oxide skins predominate acted as active sites for corrosion initiation. From potentiodynamic polarization studies, the corrosion currents increased with time for all specimens, with A9 being 1075.65 μA/cm 2 at 72 h as against 857.99 μA/cm 2 at 24 h of measurement. The corrosion potentials for all the specimens hovered around −654.00 to −647.22 mV. Bode plots revealed similar electrochemical reactions over all the substrates’ surfaces. The relative corrosion resistance by the specimen depends on the oxide films’ nature as the cathodic interfacial reinforcements dropped off into the acidic environment.
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    Tumbling strength and reactivity characteristics of hybrid fuel briquette of coal and biomass wastes blends
    (Elsevier, 2021-04-04) Adekunle Akanni Adeleke; J.K. Odusote; Peter Pelumi Ikubanni; O.O. Agboola; A.O. Balogun; O.A. Lasode
    This paper presents an assessment of the tumbling strength and reactivity behaviour of hybrid fuel briquette (HFB) produced from coal and torrefied woody biomass wastes. Briquettes were produced using 97% coal and 3% torrefied biomass with the blend of pitch and molasses in different ratios as a binder. The briquettes were treated in an inert environment at 200–300 °C for a residence time of 60 and 120 min in a tubular furnace. Fourier Transform Infrared Spectrophotometer (FTIR) was used to obtain the functional groups in the raw materials and the HFB. HFB were exposed to tumbling test (TSI+3mm) after curing and high temperature (1200 °C) exposure. Reactivity test (RI) of the HFB was carried out based on ASTM D5341M-14 standard. The FTIR spectra of the HFB show the presence of aromatic CC bonds and phenolic OH group. The TSI+3mm of the HFB samples drastically reduced from 95.5–98.3% for the treated to 57.4–77.4% for the samples exposed to 1200 °C. The reactivity indices of the HFB were in the range of 48–56%, which indicated that the HFB were highly reactive. Based on the TSI+3mm and RI, the HFB are suitable carbonaceous material in direct reduced iron making through rotary kiln.
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    Physico-chemical characterization, thermal decomposition and kinetic modeling of Digitaria sanguinalis under nitrogen and air environments
    (Elsevier, 2021-06-12) Ayokunle O. Balogun; Adekunle Akanni Adeleke ; Samuel Oluwafikayo Adegoke; Armando G. McDonald; Peter Pelumi Ikubanni; Abdulbaset M. Alayat
    The study undertook the thermal degradation of a tropical grass species, Digitaria sanguinalis, in nitrogen (pyrolysis) and air (combustion) atmospheres through thermogravimetric analysis as well as comparative kinetic investigation. The differential (Friedman) and integral (Flynn-Wall-Ozawa and Straink) isoconversional methods in conjunction with the Coats-Redfern method were utilized. This was to obtain the kinetic parameters and also predict the probable reaction mechanisms involved in the decomposition process. Before the thermal and kinetic investigations, the grass was analyzed for its physical, chemical, and structural properties utilizing diverse wet-chemistry and spectroscopic techniques. This research attempt is part of a larger project designed to investigate a couple of local grass species, which are invasive by nature, as potential energy crops for pyrolytic and combustion applications. The grass had a fixed carbon content of 17.85% and a calorific value of 13.7 MJ kg−1. The fatty acids detected were from C12 (lauric acid) to C24 (lignoceric acid), with the three most abundant being palmitic (94 mg/g extract), linoleic (27 mg/g extract), and oleic (19 mg/g extract) acids. The average residual weight in air (25.3%) was relatively less than in nitrogen (38.7%), affirming the higher rate of reaction in an oxidative process (combustion). The activation energy profiles in both atmospheres were markedly different, as shown by the Flynn-Wall-Ozawa technique for a conversion ratio of 0.1–0.2 (nitrogen, 149 kJ/mol; air, 177 kJ/mol) and 0.65–0.8 (nitrogen, 366 kJ/mol; air, 170 kJ/mol). Of all the models tested, the model-fitting technique indicates that the chemical reaction and diffusional models play predominant roles in the thermal decomposition of the grass under investigation. The thermal degradation of Digitaria sanguinalis proceeded mainly as complex multi-step reaction mechanisms. Aside from the potential suitability of the grass species for bioenergy applications and biofuels production, it also demonstrated huge capability for biochemical extraction. Future work will incorporate the kinetic data for the associated thermochemical processes development, and the design and optimization of reactors/combustors.