Performance of inherent damping models in inelastic seismic analysis for tall building subject to simultaneous horizontal and vertical seismic motion

In recent seismic analyses, it is considered that the structural damping ratio should be treated as independent of frequency, for safety side estimation. Therefore, frequency-insensitive damping is required for realistic seismic simulations. This paper investigates the performance of various sparse matrix damping models (extended Raleigh, capped viscous and uniform damping) in the inelastic seismic analysis of a 35-story moment-frame steel building. These sparse matrix damping models were compared with Rayleigh, tangent Rayleigh, and Wilson-Penzien (modal) damping models to provide insight into damping models suitable for large-scale inelastic response history analysis (RHA). First, the necessity of frequency-insensitive damping in large-scale analysis is illustrated via numerical simulations. Then, the vibration characteristics with simultaneous inputs of horizontal and vertical ground motion are analyzed using the abovementioned damping schemes, and their results are compared. The comparisons are analyzed by focusing on horizontal displacement/acceleration, story drift angle, beam-end ductility factor, the amplitude due to beam vibration, and the associated vertical acceleration. Finally, the computation speeds are compared. As a result, it is shown that although these sparse matrix damping models are practically useful, they are not yet sufficient and present challenges.

Automated summary

This paper investigates the performance of various sparse matrix damping models in the inelastic seismic analysis of a 35-story moment-frame steel building. The necessity of frequency-insensitive damping in large-scale analysis is illustrated through numerical simulations. The vibration characteristics with simultaneous inputs of horizontal and vertical ground motion are analyzed using different damping schemes, and their results are compared. The comparisons focus on various parameters and the computation speeds are also compared, showing the limitations and challenges of these sparse matrix damping models in practical applications.