Search results for: Oluwagbenga B. Fatile
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3

Search results for: Oluwagbenga B. Fatile

3 Fabrication Characteristics and Mechanical Behaviour of Fly Ash-Alumina Reinforced Zn-27Al Alloy Matrix Hybrid Composite Using Stir-Casting Technique

Authors: Oluwagbenga B. Fatile, Felix U. Idu, Olajide T. Sanya

Abstract:

This paper reports the viability of developing Zn-27Al alloy matrix hybrid composites reinforced with alumina, graphite and fly ash (a solid waste byproduct of coal in thermal power plants). This research work was aimed at developing low cost-high performance Zn-27Al matrix composite with low density. Alumina particulates (Al2O3), graphite added with 0, 2, 3, 4, and 5 wt% fly ash were utilized to prepare 10wt% reinforcing phase with Zn-27Al alloy as matrix using two-step stir casting method. Density measurement estimated percentage porosity, tensile testing, micro hardness measurement, and optical microscopy were used to assess the performance of the composites produced. The results show that the hardness, ultimate tensile strength, and percent elongation of the hybrid composites decrease with increase in fly ash content. The maximum decrease in hardness and ultimate tensile strength of 13.72% and 15.25% respectively were observed for composite grade containing 5wt% fly ash. The percentage elongation of composite sample without fly ash is 8.9% which is comparable with that of the sample containing 2wt% fly ash with percentage elongation of 8.8%. The fracture toughness of the fly ash containing composites was, however, superior to those of composites without fly ash with 5wt% fly ash containing composite exhibiting the highest fracture toughness. The results show that fly ash can be utilized as complementary reinforcement in ZA-27 alloy matrix composite to reduce cost.

Keywords: fly ash, hybrid composite, mechanical behaviour, stir-cast

Procedia PDF Downloads 334
2 Land Suitability Analysis for Rice Production in a Typical Watershed of Southwestern Nigeria: A Sustainability Pathway

Authors: Oluwagbenga O. Isaac Orimoogunje, Omolola Helen Oshosanya

Abstract:

The study examined land management in a typical watershed in southwestern Nigeria with a view to ascertaining its impact on land suitability analysis for rice cultivation and production. The study applied the analytical hierarchy process (AHP), weighted overlay analysis (WOA), multi-criteria decision-making techniques, and suitability map calculations within a Geographic Information System environment. Five main criteria were used, and these include climate, topography, soil fertility, macronutrients, and micronutrients. A consistency ratio (CR) of 0.067 was obtained for rice cultivation. The results showed that 95% of the land area is suitable for rice cultivation, with pH units ranging between 4.6 and 6.0, organic matter of 1.4–2.5 g kg-1 and base saturation of more than 80%. The study concluded that the Ofiki watershed is a potential site for large-scale rice cultivation in a sustainable capacity.

Keywords: land management, land characteristics, land suitability, rice production, watershed

Procedia PDF Downloads 75
1 Statistical Time-Series and Neural Architecture of Malaria Patients Records in Lagos, Nigeria

Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

Abstract:

Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

Procedia PDF Downloads 74