THEORETICAL EVALUATION AND EXPERIMENTAL VALIDATION OF AN INNOVATIVE DYNAMIC ANALYSIS METHOD FOR COMBINED STRUCTURES WITH TUNED MASS DAMPERS

Abstract

Tuned Mass Dampers (TMDs) is an effective way for mitigating vibrations and sways in engi neering structures under lateral actions, such as strong winds. Thus, TMDs can enhance safe ty and reduce design structural demands. The design approach for systems with TMDs is crucial for both the accuracy and efficiency of their design. However, the current design ap proaches have either some practicality disadvantages, or cannot provide accurate and effec tive solutions in all cases. To this end, Bellos et al. [2] recently proposed a robust and versatile hybrid analytical-numerical design method that can address these shortcomings. The method accounts for distributed parameters and non-proportional damping, and can ap ply to non-conservative systems under all types of external actions. Yet, this method has not experimentally been validated. The main objectives of this work are to experimentally validate the aforementioned method, demonstrate its extended applicability, and provide a handy and accurate means for engineers to design systems with TMDs accurately and efficiently. The latter is realized by providing design charts, in lieu of using heavy numerical simulations, or other impractical and oversimplified methods. To achieve its objectives, the work utilizes a scaled down, two-storey building experimental setup with and without a TMD at its top. Par ametric analyses are then performed for varying values of characteristic design parameters of the investigated system. The experiments show a good agreement with the theoretical results, thus validating the accuracy of the method. The results demonstrate the effectiveness of the method in reducing critical performance indices of the structure under winds by up to about 90% for realistic values of the TMB design properties. The work lays the foundation for im plementing the method in complex structures with multiples TMDs in random positions.