Browsing by Author "Nyaanga, Daudi"
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Publication Effect of Process Techniques on Three Feedstocks Mix on Briquette Performance Properties(2022) Okwara, Wilberforce; Nyaanga, Daudi; Kabok, Peter; Nyaanga, JaneEnergy availability at domestic level is a challenge across the world and especially in Africa. Firewood is the major source of energy for cooking for households in Kenya and there is need for a friendly sustainable environmental fuel. Carbonized biomass materials (briquettes) are considered a substitute. This study thus evaluated effect of selected briquetting techniques on briquettes’ performance properties. Milled charcoal dusts mixed in a ratio of 1:1:1 (Rice husk, maize cob, and sugarcane bagasse) with molasses binder in the ratio of 6:1 was hence ready for densification and agglomeration. The Water Boiling Test was used in determination of the briquette’s performance characteristics for various parameters. High (screw press); and low (drum agglomerator and hand making) pressure briquetting techniques were distinctly different in ignition time (minutes), time to boil (minutes) burning rate (g/min), specific fuel consumption (g/ml) and power output (kW) values as (4, 3, 3; 14, 12, 11: 0.8, 1.1, 1.3; 0.11, 0.13, 0.15; and 1.8, 1.4, 0.75). Diversified briquetting techniques, number and type of feedstocks are thus factors that influence performance characteristics of briquettes in converting the agricultural and or other wastes for useful energy application. This knowledge should enable users to make choices on techniques for optimum efficiency towards realization of Sustainable Development Goal Number #7 on affordable and clean energy.Publication Investigating the Effect of Selected Parameters on Moisture Removal Rate of an Experimental Forced Convection Solar Grain Dryer(Scientific & Academic Publishing, 2018) Osodo, Booker; Nyaanga, DaudiAlthough forced convection solar grain dryers achieve greater drying rates than natural convection dryers, optimum air velocity, grain layer thickness and drying air temperatures are necessary for improved performance. Number of trays used also affects performance. This study investigated the moisture removal rate (ratio of mass of moisture removed to mass of wet grain per hour) of a solar grain under different drying conditions. The effect of air velocity, layer thickness, number of trays and temperature on moisture removal rate (MRR) was investigated. MRR increased with increase in both drying air velocity and temperature at constant layer thickness. For 0.02 m thickness, MRR increased from 0.048 to 0.061 kg moisture / (kg wet grain. hour). However this increase was only significant at lower temperatures (below 45°C). Changing from 40 to 45°C caused a significant increase, but increasing temperature above 45°C did not. Also, MRR decreased with increase in layer thickness at constant air velocity. At 0.408 m/s air velocity, as layer thickness increased from 0.02 to 0.08 m, MRR decreased from 0.061 to 0.022 kg moisture / (kg wet grain. hour). Finally, when drying a given layer thickness, use of two trays did not significantly improve MRR.Publication Selection and Verification of a Drying Model for Maize (Zea mays L.) in Forced Convection Solar Grain Dryer(science and education publishing, 2017) Osodo, Booker; Nyaanga, Daudi; Muguthu, JosephVarious researchers have fitted experimental drying curves for various products to existing drying models. In this study, an experimental forced convection solar grain dryer was used to select the best fitting drying model for shelled maize. 0.04 m thick grain layer of shelled maize was dried an air velocity of 0.408 m/s and a 40°C drying air temperature. Using Root Mean Square Error (RMSE), Coefficient of Determination (R2) and Chi Square (𝜒𝜒2) the selected drying model was the one by Midilli et al. (2002), with R2, 𝜒𝜒2 and RMSE values of 0.9487, 0.4278 and 0.1723 respectively. The model coefficients were determined for drying air temperatures of 40, 45, 50 and 55°C. It was found that the predicted and experimental data agreed satisfactorily with R2 and RMSE values of 0.9225-0.9786 and 0.0325-0.0750 respectively. A computer simulation model was developed to predict moisture ratio at a given drying time.