The process of ground motion selection and scaling is an integral part of hazardand risk-consistent seismic demand analysis of structures. Due to the lack of ground motion records that naturally possess high amplitude and intensity, the research community generally relies on scaling the records to match a target hazard intensity level. The scaling factors used are frequently as high as 10. Due to the criticism received in previous research studies, the extent of amplitude scaling and its process has become a matter of debate, and various constraints on the scaling factors have been proposed. The primary argument against unrestricted amplitude scaling is the unrealistic nature of the scaled records and the possible biases caused in the engineering demand parameters (EDPs) of structures. This study presents a framework to utilize machine-learning and statistical techniques for the assessment of ground motion amplitude scaling for nonlinear time-history analysis (NTHA) of structures. The framework utilizes Bayesian non-parametric Gaussian process regressions (GPRs) as surrogate models to obtain statistical estimates of EDPs for scaled and unscaled ground motions. The GPR surrogate models are developed based on a large-scale analysis of five steel moment frames (SMFs) using 200 unscaled as-recorded ground motions for ten spectral acceleration levels, (𝑆 𝑎 (𝑇 1 )) (ranging from 0 g to maximum considered earthquake, MCE) and 2500 scaled ground motions representing 50 scale factors (𝑆𝐹), and the 10 𝑆 𝑎 (𝑇 1 ) levels for each SMF. For each building, two types of EDPs are considered: i) peak inter-story drift ratio (PIDR) and ii) peak floor acceleration (PFA). To provide a better interpretation of the GPR surrogate models, the concept of explainable artificial intelligence (i.e., Shapley additive explanation, SHAP) is used to obtain insights into the decision-making process of the GPR models with respect to the 𝑆𝐹 and 𝑆 𝑎 (𝑇 1 ). Then, for the 10 𝑆 𝑎 (𝑇 1 ) levels, the GPRbased EDP estimates under scaled ground motions corresponding to 50 different SFs are compared with the EDP estimates of unscaled ground motions. TheThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
The design practice of Box-Girder Seat-Type (BGST) bridges in the Western U.S. is continuously evolving based on the results of advanced modeling and analysis techniques. This is mainly to help engineers and researchers to better understand the behavior of BGST bridges during seismic excitations. Within this backdrop, this study fills the gaps in the current knowledge of assessing the combined effect of strong motion duration and spectral shape on the response of bridges using a comprehensive set of numerical simulations and statistical analyses. Three-dimensional finite element models of two real BGST bridges are analyzed using a large set of ground motions obtained from crustal sources and subduction sources. By means of Step-wise regressionand other statistical proceduresthe sensitivity of bridge response parameters to various ground motion parameters including Arias Intensity (I a), RotD50 spectral acceleration at the bridge's first natural period (, Significant Duration (D 5-95), mid-frequency (f), the derivative of the mid-frequency (f') and time at 30% of cumulated Arias Intensity (t mid) are evaluated. Results indicate that in the case of ground motions arising from shallow crustal sources, I a and are the best predictors of the bridge response, and strong motion duration (D 5-95) has no statistically meaningful impact on the response of bridges. However, it is observed that the D 5-95 of the ground motions ascending from the subduction sources highly affects the bridge response; utilizing D 5-95 alongside , or I a , can significantly increase the accuracy of bridge response estimates. Hence, it is concluded that D 5-95 is not an important ground motion intensity measure for ground motion selection for bridges located in areas with crustal earthquakes. In contrast, D 5-95 is important in subduction zone ground motions and must be given proper consideration in the design and analysis of BGST bridges.
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