Optimizing of Turbine blade spar using Ansys program

The current work involved optimizing the spars of wind turbine blades while taking into account the wind speed quantities that affected the blade structure. The objective was to determine the optimal dimensions of turbine blade spar configurations using the finite element method under the influence of the maximum pressure associated with the first mode shape while maintaining the Von Misses stresses within the assumed safety factor (1.5). (200-230 MPa). The blade was stiffened with a main box spar and two auxillary spars on each side. Appropriate spar locations were specified for poisons with a high natural frequency first mode. The blade parts' dimensions were discretized to allow for greater flexibility and precision in dimension assignment. By utilizing the ANSYS program, the optimization process required a certain number of iterations to modify the blade structure's dimensions. Optimized iteration was considered in order to increase the thickness in areas of high stress and decrease the thickness in areas of low stress. Additionally, a comparison between a blade structure with optimal dimensions and one with non-optimal dimensions was included .


Introduction:
The Optimization is a strategy for determining the optimal design. By "optimal design," we mean one that satisfies all specified requirements while incurring the fewest possible costs in terms of weight, surface area, volume, stress, and cost. In other words, 303 the optimal design is typically the most effective. The ANSYS program includes a variety of optimization methods that may be used to solve a wide variety of optimization problems. These approaches can be applied quickly to the majority of engineering problems. One of these ways is the first order method, which is more suitable for issues requiring high accuracy because it is based on design sensitivity. While attempting to achieve the optimal design, the ANSYS optimization procedures make use of three distinct types of variables to represent the design process: design variables, state variables, and the objective function.THEORY The independent variables in an optimization analysis are the design variables. State variables are also known as dependent variables since they vary in relation to the vector x of design variables [3]. Equations (3) through (6) denote a constrained minimization problem whose objective is to minimize the objective function f while adhering to the limitations imposed by Equations (2), (4), (5), and (6).

FEASIBLE VERSUS INFEASIBLE DESIGN SETS
The term "feasible designs" refers to design configurations that satisfy all constraints [4].
Infeasible configurations are those that have one or more violations. Each state variable limit is given a tolerance when determining the feasible design space. Therefore, if x* is a specified design set defined as: The design is deemed feasible only if

THE BEST DESIGN SET
Due to the fact that tools generate design sets and an objective function is given, the better design set is computed and its number is stored. The optimal set is determined in one of the following circumstances. If there are multiple viable sets, the optimal design set is the one with the lowest objective function value. In other words, it is the set that conforms most closely to the mathematical objectives represented in Equations (3) through (8). If all design sets are infeasible, the best design set is the one that is the closest to being feasible, regardless of the value of the objective function [7].

RESULTS AND DISSCUSSION
The optimization technique requires a certain number of iterations to alter the blade structure's dimension. Optimize iteration was explored in order to raise the thickness in areas of high stress and decrease the thickness in areas of low stress. Tables (1) and (2) show the final optimized dimensions of the blade thicknesses in each section (2).     It was observed the same thing in the left and right spars and the results of weight and thickness reduction were indicated in Table (4).

CONCLUSION
The stress distribution along optimized blade structures was shown to be more stable at high stress levels until it reached the threshold area, after which the stress continued to fall until it reached the blade's tip. In non-optimized structures, stress is noted to be greatest at the blade's root and gradually decreases until it reaches the blade's tip. The total weight of the non-optimized blade was (8348.3 N), which was reduced to (3545.5 N) for the improved blade (57.53 percent). Additionally, the natural frequency in the first mode was (0.675 Hz) for the non-optimized structure and became (0.97 Hz) for the improved structure. This demonstrates that the optimized blade was stiffer than the nonoptimized blade, where the natural frequency is proportional to the root of the blade's stiffness and inversely proportional to the root of the blade's mass.