Refinement of tuned mass damper parameters on machine support structure using dynamic cuckoo search algorithm

Abstract. A classical Tuned Mass Damper (TMD) consists of a mass, spring, and viscous damper, typically optimized in the frequency domain to minimize the steady-state displacement amplitude of a primary structure under harmonic force excitation with varying frequency. This study proposes the use of a dynamic Cuckoo Search (CS) algorithm, a nature-inspired optimization method, to enhance the accuracy of TMD parameters when external factors, such as excitation frequency or structural properties, change. The research aims to optimize key TMD parameters (mass ratio, damping ratio, and frequency ratio) using the dynamic CS algorithm. The performance of this algorithm will be evaluated by comparing it to the computed values in literature, especially from the Den Hartog formula. In the dynamic CS algorithm, the value for discovery probability (pa) and the step size factor (a) are changed dynamically which changes the convergence speed to the solution. The descend rate to the final solution is a combination of exploration mode (bigger search area) and exploitation mode (more specific area). Key outcomes in the research continuation from this paper will include a parameter study that can enhance the TMD's design accuracy in mitigating harmonic vibrations. The intent is to formulate an algorithm capable of adapting to fluctuations in excitation frequencies and the structural modal parameters. These findings are hoped to contribute to the design of more robust TMDs, with broader applicability for vibration control in civil engineering structures.