Scaling, Matching, and Variability: Effects of Time Series Selection in Performance of Code‐Compliant Bridges

The modification of time series for the analysis of structures remains a topic of continuous debate. While amplitude scaling is widely accepted, codes often penalize spectral matching. Recent advancements in spectral matching address prior concerns about tight spectral matching by preserving component‐to‐component variability. This study explores and compares the improved spectral matching method with amplitude scaling in estimating the means and distributions of bridge response parameters. Two highway bridges in California were analyzed using suites of scaled and spectrally matched motions. Site and structure specific benchmarks were established by developing hazard curves for engineering demand parameters using the conditional scenario spectra, providing a more objective basis for comparison. Results demonstrate that spectral matching consistently yields lower bias and variability in engineering demand parameter predictions between time series suites compared to amplitude scaling for both bridge models and sites, indicating that spectral matching offers more reproducible and reliable EDP estimates across users and highlighting its strengths for use in bridge design.