Optimal design of the rotating disk structure of a turbine engine utilizing modern optimization methods
This paper presents the initial structural analysis and geometric optimization of a rotating disk used in an aircraft turbine engine. The disk is homogeneous and subject to mechanical and thermal loads. The governing equations for the thermoelastic analysis of the assumed disk were derived under the assumption of plane stress conditions and subsequently analyzed using the MATLAB computational software. Three different optimization methods were implemented for the geometric optimization of the rotating disk: The Counting Sort Algorithm (CSA), the non-gradient Genetic Algorithm (GA), and the Artificial Bee Colony algorithm (ABC). The optimization methods resulted in a reduction of the disk mass by 36.49%, 39.51%, and 36.43%, respectively. Also, the approximate time required to reach the optimization results was 3,500, 120, and 100 minutes, respectively. The results show that the non-gradient genetic algorithm (GA) method has the greatest improvement in results. The convergence speed of the non-gradient GA and ABC methods is also about 30 to 35 times faster than the CSA method. As a result, the importance of non-gradient methods in saving time and computational costs has become more evident, due to the time-consuming nature of gradientbased analyses. Based on the results, the use of the GA method has been proposed as an accurate and efficient method for the optimization of rotating problems under thermoelastic loading.