Average spectral acceleration (AvgSa) for high-confidence probabilistic seismic demand modeling of urban highway bridge portfolios: What period range and damping ratio shall we use?

Engineering Structures(2024)

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摘要
The average spectral acceleration (AvgSa), i.e., the geometric mean of spectral accelerations over a period range, has attracted widespread recognition as one of the most promising intensity measures (IMs) for probabilistic seismic demand modeling of structures. As AvgSa is a structure-related spectral IM, a pivotal step in calculating AvgSa is to determine an appropriate period range and damping ratio. Whilst optimal AvgSa has been well documented for buildings, consensus on the period range and damping ratio of AvgSa for urban highway bridges is yet to be reached. To this end, a pool of AvgSa candidates with different combinations of lower and upper period bounds and damping ratios are assessed to identify the optimum combination(s) for straight and curved urban highway bridge portfolios against bidirectional seismic excitations, in terms of peak pier drift ratio, peak bearing displacement, and residual pier drift ratio. Results indicate that for the peak demand parameters, optimal AvgSa is characterized by a damping ratio of 0.2 and a period range of [Tf, 1.5Tf], where Tf is the structural fundamental period, for bridges with relatively short piers; and the optimal period range becomes [Tf, 2Tf] for medium to tall-pier bridges. Besides, the optimal period range for the conventional 5%-damped AvgSa is also detected, where [0.5Tf, 1.5Tf] is the optimal range for bridges with relatively short piers, while [0.5Tf, 2Tf] is recommended for medium to tall-pier bridges. Regarding the residual pier drift ratio, averaging spectral accelerations over any examined period ranges does not outperform traditional spectral accelerations at specific periods.
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关键词
Average spectral acceleration,Probabilistic seismic demand modeling,Urban highway bridges,Seismic incidence angle,Optimal period range,Optimal damping ratio
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