4.7 Article

Modeling spatial variability in offshore geotechnical properties for reliability-based foundation design

期刊

STRUCTURAL SAFETY
卷 49, 期 -, 页码 18-26

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.strusafe.2013.07.008

关键词

Spatial variability; Random field models; Reliability-based design; Maximum likelihood estimators; Value of information; Offshore foundations; Deep foundations; Undrained shear strength

资金

  1. oil industry

向作者/读者索取更多资源

Design of foundations for offshore energy production typically requires soil characterization over large areas. Often, in uniform geological settings, it is neither practical nor economical to acquire geotechnical data at every foundation location. Additionally, the zone of interest for the foundation may extend deeper than the available geotechnical data. This paper describes a model of spatial variability in geotechnical properties for foundation design in deep water Gulf of Mexico. The geology consists of normally to slightly over-consolidated marine clays. Data are available for about 100 locations with soil borings, jumbo piston cores and cone penetration tests. A random field model that describes spatial variations in the design undrained shear strength is formulated and calibrated. This model is incorporated into a reliability-based framework to account for uncertainty due to spatial variability in foundation design. In this setting, depth-averaged values of design undrained shear strength are correlated over longer distances than point values due to stratigraphic features. There is less variation and greater spatial correlation in the design undrained shear strength for deeper versus shallower deposits and along the continental shelf versus off from the shelf. The increased conservatism required in foundation design due to spatial variability when site-specific strength data are not available is generally small. (C) 2013 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据