Abstract This study presents an innovative optimization approach that integrates the Pattern Search (PS) algorithm with the Transfer Matrix Method (TMM) to enhance rotor dynamics in gas turbine systems. A multi-objective framework has been developed to optimize rotor geometry, aiming to increase natural frequency while reducing deflections and bearing forces. The PS algorithm, known for its robust convergence capabilities, is employed for the iterative adjustment of design parameters, while TMM provides fast and highly accurate dynamic analysis. Experimental validation was conducted through modal tests performed on a dedicated test rig. The results indicate an increase in natural frequency by up to 15 %, a reduction in disk deflections by 10–20 %, and a decrease in bearing forces by 8–15 %. When compared with TMM and analytical methods, the error rate for the optimized first natural frequency remained below 2.86 %. Comparisons with the unoptimized configuration demonstrate that the PS-TMM approach offers significant advantages, particularly in natural frequency enhancement and deflection reduction. The synergy of PS and TMM in multi-objective optimization provides an effective and practical solution for high-speed rotors, offering substantial contributions to the fields of aerospace and energy.
Niş et al. (Tue,) studied this question.
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