HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Full Text (PDF) Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via ISI Web of Science (1) Citing Articles via Google Scholar Google Scholar Articles by Jeon, S.-S. Articles by O’Rourke, T. D. Search for Related Content GeoRef GeoRef Citation

Northridge Earthquake Effects on Pipelines and Residential Buildings

¹ Geotechnical Research Division
Highway & Transportation Technology Institute
Korea Highway Corporation
San 50-5, Sanchuk-Ri, Dongtan-Myeon
Hwaseong City, Kyeonggi-Do
South Korea 445-812
 (S.-S.J.)

² School of Civil & Environmental Engineering
Cornell University
Ithaca, New York 14853-3501
 (T.D.O.)

This article is focused on the spatial variability of earthquake strong motion and its relationship with the performance of water-distribution pipelines provided by Los Angeles Department of Water and Power (LADWP) and residential buildings. Analyses of strong-motion characteristics and their correlations with pipeline and building damage were conducted with an immense geographical information system (GIS) database for the 1994 Northridge earthquake, which was collected, digitized, and organized by researchers at Cornell. There are statistically significant correlations among pipeline repair rate (repairs/km) and peak ground velocity (PGV) for cast iron, ductile iron, asbestos cement, and steel pipe. Statistically significant regressions have been developed between damage ratio, DR (percent of existing structures with damage equal to or exceeding a particular damage factor, DF [percent of building replacement cost]) and the magnitudes of seismic parameters, such as PGV and spectrum intensity (SI). Regressions developed between DR and scaled seismic parameters (seismic parameters normalized with respect to DF) resulted in predictive equations having a very high degree of statistical significance. Algorithms to visualize damage patterns for buildings were developed and validated to choose optimal GIS mesh dimensions and contour intervals. Ordinary kriging was used to develop regressions of pipeline repair rate and residential building DR associated with 90% confidence PGV and spectrum intensity (weighted average pseudovelocity). Such regressions provide an explicit means of characterizing the uncertainty embodied in the strong-motion data.