Shear-Wave Velocity-Based Probabilistic and Deterministic Assessment of Seismic Soil Liquefaction Potential

被引:281
|
作者
Kayen, R. [1 ,2 ]
Moss, R. E. S. [3 ]
Thompson, E. M. [4 ]
Seed, R. B. [5 ]
Cetin, K. O. [6 ]
Kiureghian, A. Der [5 ]
Tanaka, Y. [7 ]
Tokimatsu, K. [8 ]
机构
[1] US Geol Survey, Menlo Pk, CA 94025 USA
[2] Univ Calif Los Angeles, Dept Civil & Environm Engn, Los Angeles, CA 90025 USA
[3] Calif Polytech State Univ San Luis Obispo, San Luis Obispo, CA 93407 USA
[4] Tufts Univ, Medford, MA 02155 USA
[5] Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USA
[6] Middle Eastern Tech Univ, Ankara, Turkey
[7] UTAR, Dept Civil Engn, Kuala Lumpur 53300, Malaysia
[8] Tokyo Inst Technol, Dept Architechture & Bldg Engn, Tokyo 1528550, Japan
关键词
Earthquakes; Liquefaction; Shear waves; Velocity; Sand; Seismic hazard; Correlation; Databases; PENETRATION TEST; RESISTANCE; EARTHQUAKE; STRESS; SITES;
D O I
10.1061/(ASCE)GT.1943-5606.0000743
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
Shear-wave velocity (V-s) offers a means to determine the seismic resistance of soil to liquefaction by a fundamental soil property. This paper presents the results of an 11-year international project to gather new V-s site data and develop probabilistic correlations for seismic soil liquefaction occurrence. Toward that objective, shear-wave velocity test sites were identified, and measurements made for 301 new liquefaction field case histories in China, Japan, Taiwan, Greece, and the United States over a decade. The majority of these new case histories reoccupy those previously investigated by penetration testing. These new data are combined with previously published case histories to build a global catalog of 422 case histories of V-s liquefaction performance. Bayesian regression and structural reliability methods facilitate a probabilistic treatment of the V-s catalog for performance-based engineering applications. Where possible, uncertainties of the variables comprising both the seismic demand and the soil capacity were estimated and included in the analysis, resulting in greatly reduced overall model uncertainty relative to previous studies. The presented data set and probabilistic analysis also help resolve the ancillary issues of adjustment for soil fines content and magnitude scaling factors. DOI: 10.1061/(ASCE)GT.1943-5606.0000743. (C) 2013 American Society of Civil Engineers.
引用
收藏
页码:407 / 419
页数:13
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