Record Selection for Nonlinear Seismic Analysis of Structures

Author:

Iervolino Iunio12,Cornell C. Allin2

Affiliation:

1. Dept. of Structural Analysis and Design, University of Naples Federico II, 21 via Claudio, Naples 80125, Italy

2. Dept. of Civil and Environmental Engineering, Terman Engineering Center, Stanford University, CA 94305

Abstract

This study addresses the question of selection and amplitude scaling of accelerograms for predicting the nonlinear seismic response of structures. Despite the current practices of record selection according to a specific magnitude-distance scenario and scaling to a common level, neither aspect of this process has received significant research attention to ascertain the benefits or effects of these practices on the conclusions. This paper hypothesizes that neither these usual principal seismological characteristics nor scaling of records matters to the nonlinear response of structures. It then investigates under what conditions this hypothesis may not be sustainable. Two classes of records sets are compared in several case studies: one class is carefully chosen to represent a specific magnitude and distance scenario, the other is chosen randomly from a large catalog. Results of time-history analyses are formally compared by a simple statistical hypothesis test to assess the difference, if any, between nonlinear demands of the two classes of records. The effect of the degree of scaling (by first-mode spectral acceleration level) is investigated in the same way. Results here show (1) little evidence to support the need for a careful site-specific process of record selection by magnitude and distance, and (2) that concern over scenario-to-scenario record scaling, at least within the limits tested, may not be justified.

Publisher

SAGE Publications

Subject

Geophysics,Geotechnical Engineering and Engineering Geology

Reference20 articles.

1. Empirical Response Spectral Attenuation Relations for Shallow Crustal Earthquakes

2. Benjamin, J.R., and Cornell, C.A., 1970.Probability, Statistics and Decision for Civil Engineers, McGraw-Hill, London.

3. Carballo Arévalo, J.E., 2000. Probabilistic Seismic Demand Analysis: Spectrum Matching and Design, Ph.D. thesis, Dept. of Civil and Environmental Engineering, Stanford University, Stanford, CA. (http://www.stanford.edu/group/rms/)

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