Abstract
This paper presents an analysis of the optimal design of transmission shafts by adopting the approach of a novel continuous genetic algorithm. The optimization case study is formulated as a single-objective optimization problem whose objective function is the minimization of the total weight that results from the sum of all the sections in the shaft.Additionally, mechanical stresses and constructive characteristics are considered constraints in this case.The proposed optimization model corresponds to a nonlinear non-convex optimization problem which is numerically solved with a continuous variant of genetic algorithms. SKYCIV®and Autodesk Inventor®were used to verify the quality and robustness of the numerical results in this paper by means of simulation tools and analysis. The results obtained demonstrates that the methodology proposed reduce the complexity and improving the results obtained in comparison to conventional mechanical design.
Highlights
The drive shafts of industrial machinery are responsible for transmitting power, generally from the engine to the mechanism, which makes the equipment operate [1]
This work implemented an optimization Genetic algorithms (GA) to solve the model that enables to calculate the diameters of the cross sections of a shaft under the conditions studied in this article
In this paper a new approach for the continuous genetic algorithm is proposed for mechanical design of transmission shaft
Summary
The drive shafts of industrial machinery are responsible for transmitting power, generally from the engine to the mechanism, which makes the equipment operate [1]. In 2016, Reddy and Nagaraju studied the minimization of the weight of a drive shaft of an automobile [4] To achieve their goal, they created a mathematical model considering the constructive and physical parameters that must be respected for a correct operation. They created a mathematical model considering the constructive and physical parameters that must be respected for a correct operation They carried out a validation with Finite Element Analysis (FEA) software to guarantee compliance with the characteristics mentioned above. Due to the time and economic resources required by traditional design techniques, optimization algorithms have been introduced They explore a search space under given parameters and a set of constraints in order to provide an optimal solution to the mathematical model of the problem [6] in a quick and accurate manner. They add the value of safety because, if the mathematical model is analyzed with specialized computer programs, the human
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