Seismic retrofit of a soft first-story building using viscoelastic dampers considering inherent uncertainties. (15th April 2022)

• Record Type: Journal Article
• Authors: Nasab, Mohammad Seddiq Eskandari; Guo, Ying-Qing; Kim, Jinkoo
• Is Part Of: Journal of building engineering. Volume 47(2022)
• Publication Date: 2022-04-15
• Subjects: Viscoelastic material -- Fuzzy random analysis -- Kriging model -- Storage modulus -- Loss modulus; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2021.103866
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: The mechanical properties of viscoelastic dampers (VED) generally vary depending on the loading conditions such as input frequency, amplitude, and temperature, which makes the conventional modeling approach of using constant material properties highly inaccurate. This study develops the kriging model, which is a powerful tool when there is a limited number of experimental data available, for VED made of high energy dissipation acrylate and nitrile butadiene rubber-based viscoelastic materials. The coefficients of determination (R 2 ) of the storage and loss moduli predicted by the kriging model turns out to be 0.9805 and 0.9868, respectively, which proves that the model predictions for the test data are quite accurate. Fuzzy random analysis of a soft first-story building is carried out to investigate the effectiveness of the damper in uncertain conditions. The results show that when the informal uncertainty is minimum, the maximum inter-story drift ratio of the example structure is reduced from 1.6% to 1.0% after installation of the dampers; when the informal uncertainty is maximum, the maximum inter-story drift ratio of the building is reduced from 5.0% to 2.6% after the retrofit. Highlights: This study develops a kriging model of rubber-based viscoelastic materials. Fuzzy analysis is carried out to investigate the effectiveness of the damper. The VEDs are effective in improving the seismic performance of the model structure in uncertain situations. The kriging model can adequately simulate the test results with acceptable accuracy.