Research Articles in Mechanical Engineering

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

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Design and Fabrication of an Ablative Pyrolyzer for Production of Bio- lubricants and chemicals in Oil Well Drilling Application
(IOP Publishing, 2021-03-24) Samuel Oluwafikayo Adegoke; Adekunle Akanni Adeleke; Peter Pelumi Ikubanni; A. O. Falode; A. J. Alawode; O.O. Agboola; Adeolu Adesoji Adediran
In this study, an ablative pyrolyser having 27.1 cm inner diameter, 41.2 cm outer diameter, the full chamber height of 74.7 cm and chamber volume of 40 litres was designed and fabricated. 150KW heater was wounded around the reactor chamber made of stainless steel to provide a higher temperature of up to 1400 The -40 to 105 capacity heat resistance wires were used to conduct the heater into the electrical panel which has several components such as the contactor, temperature controller, thermocouple wire and so on to give a particular desired working temperature. This pyrolyser applies technology of thermal energy in the heated walls of the pyrolyser being transferred to the biomass by conduction in the absence of oxygen for onward disintegration into gas, bio-oil, and biochar. After fabrication, 12 kg each of Tectona grandis and Rhopalosiphum maidis was fed into the reactor and pyrolyzed at 500, the bio-oil product for both samples were mixed together and distilled at 120 and the bio-oil distillate was characterized for density, kinematic viscosity, pH, acid value and free fatty acid content. The bio-oil distillate shows a density of 0.960 g/cc, pH of 7.2, kinematic viscosity of 84 cst and acid value of 42.20 compared to the bio oil crude which showed higher values. This pyrolyser has been found on average to melt 12 kg each of Tectona grandis and Rhopalosiphum maidis to 5353 and 3493 g crude bio-oil respectively for a period of at least 3 h. The mass of bio-char for tectona grandis and Rhopalosiphum maidis were 3325 and 2614 g respectively while the reactor requires 8 h to cool before discharging the bio-char from the reactor. This research work can provide a basic designing formula for effective and workable ablative pyrolyzer fabrication for Nigerian wastes having high energy content.
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.
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.