The country or region where energy production is based on imported coal or oil will become more self-sufficient by using alternatives such as wind power. Electricity produced by the wind produces no CO2 emissions and therefore does not contribute to the greenhouse effect. Wind energy is relatively labour intensive and thus creates many jobs. Wind energy is the major alternative of conventional energy resources. A wind turbine transforms the kinetic energy in the wind to mechanical energy in a shaft and finally into electrical energy in a generator. The turbine blade is the most important component of any wind turbine. In this article is considered the single airfoil National Advisory Committee for Aeronautics (NACA) 0018 and a computational fluid dynamics (CFD) analysis is done at different blade angles 0º, 10º, 15º, and 30º with a wind velocity of 4 m/s. The analysis results show that a blade angle of 10º gives the best possible power and pressure and velocity distributions are plotted for every case.
We construct a new biparametric three-point method with memory to highly improve the computational efficiency of its original partner, without adding functional evaluations. In this way, through different estimations of self-accelerating parameters, we have modified an existing seventh-order method. The parameters have been defined by Hermite interpolating polynomial that allows the accelerating effect. In particular, the R-order of the proposed iterative method with memory is increased from seven to ten. A real multidimensional analysis of the stability of this method with memory is made, in order to study its dependence on the initial estimations. Taking into account that usually iterative methods with memory are more stable than their derivative-free partners and the obtained results in this study, the behavior of this scheme shows to be excellent, but for a small domain. Numerical examples and comparison are also provided, confirming the theoretical results.
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