Department of Aeronautic Engineering

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Browsing Department of Aeronautic Engineering by Author "Anyaegbuna Elochukwu Benjamin"

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    Aerodynamic lift coefficient prediction of supercritical airfoils at transonic flow regime using convolutional neural networks (CNNs) and multi-layer perceptions (MLPs)
    (Al-Qadisiyah Journal for Engineering Sciences, 2023-05-18) Olayemi Adebayo Olalekan; Salako Isaac Oluwadolapo; Jinadu Abdulbaqi; Obalalu Martins Adebowale; Anyaegbuna Elochukwu Benjamin
    Designing an aircraft involves a lot of stages, however, airfoil selection remains one of the most crucial aspects of the design process. The type of airfoil chosen determines the lift on the aircraft wing and the drag on the aircraft fuselage. When a potential airfoil is identified, one of the first steps in deciding its optimality for the aircraft design requirements is to obtain its aerodynamic lift and drag coefficients. In the early stages of trying to select a candidate airfoil, which a whole part of the design process rests on, the conventional method for acquiring the aerodynamic coefficients is through Computational Fluid Dynamics Simulations (CFDs). However, CFD simulation is usually a computationally expensive, memory-demanding, and timeconsuming iterative process; to circumvent this challenge, a data-driven model is proposed for the prediction of the lift coefficient of an airfoil in a transonic flow regime. Convolutional Neural Networks (CNNs) and Multi-Layer Perceptrons (MLPs) were used to develop a suitable model which can learn a set of usable patterns from an aerodynamic data corpus for the prediction of the lift coefficients of airfoils. Findings from the training revealed that the models (MLPs and CNNs) were able to accurately predict the lift coefficients of the airfoil.
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    CFD Analysis of A 3-Bladed NACA 0018 Vertical Axis Wind Turbine for Deployment in Ilorin, Kwara State, Nigeria
    (FETiCON, 2023-06-05) Olayemi Adebayo Olalekan; Ajide Favour Tomisin; Ibitoye Emmanuel Segun; Obalalu Martins Adebowale; Jinadu Abdulbaqi; Anyaegbuna Elochukwu Benjamin
    During the last few years, vertical axis wind tubines have evolved as a suitable supplement to energy production worldwide. There has been a lot of interest in vertical axis wind turbines as a small-scale renewable power converter because they can be used in places where the wind speeds are turbulent or unsteady. When investigating the aerodynamic characteristics of vertical axis wind turbines, computational fluid dynamics has been shown to be one of the most effective methods. There is a need for better knowledge of the factors that influence the accuracy of computational fluid dynamics. The aim of this paper is to demonstrate the influence of these factors on the simulation of a low-speed turbine to guide the execution of accurate computational fluid dynamics simulations of vertical axis wind turbines at varying tip speed ratios and solidities. To simulate the turbulent, unstable fluid flow around the turbine, we used a 2D SIMPLE approach with the help of ANSYS FLUENT. In the study, it was found that when the tip speed ratio is low, the result is largely dependent on the azimuthal increment, and a fine azimuthal increment of 0.1 is usually better for low tip speed ratios