Modeling asymmetric dependences among multivariate soil data for the geotechnical analysis

The asymmetric copula approach

authored by
Yi Zhang, António Topa Gomes, Michael Beer, Ingo Neumann, Udo Nackenhorst, Chul Woo Kim
Abstract

Multivariate information of soil parameters is quite important for the design and risk assessment of geotechnical engineering problems. It is necessary to have an accurate and realistic statistical multivariate model for representing the soil properties and thus evaluating the soil conditions. Thus, advanced multivariate modeling of soil parameters could help to improve the geotechnical engineering practice. In this paper, the asymmetric copulas are introduced to model the geotechnical soil data. Compared to extensive previous research on the use of symmetric copulas on the modeling of engineering data, this study is focusing on capturing asymmetric dependencies among the natural soil parameters, which are critical for engineering design. A copula-based multivariate probabilistic model is built based on a set of collected samples from a granite residual soil from Portugal. Several asymmetric copula functions, capable of capturing nonlinear asymmetric dependence structures, are tested and analyzed. The fundamental information on tail dependencies and measures of asymmetric dependencies are also exploited. To demonstrate the advantages of asymmetric copulas, its concept is compared with the traditional copula approaches for modeling site soil data. The performance of these asymmetric copulas is discussed and compared based on data fitting and extreme value characterizations.

Organisation(s)
Institute for Risk and Reliability
Geodetic Institute
Institute of Mechanics and Computational Mechanics
External Organisation(s)
Tsinghua University
Universidade do Porto
Kyoto University
Type
Article
Journal
Soils and foundations
Volume
59
Pages
1960-1979
No. of pages
20
ISSN
0038-0806
Publication date
12.2019
Publication status
Published
Peer reviewed
Yes
ASJC Scopus subject areas
Civil and Structural Engineering, Geotechnical Engineering and Engineering Geology
Electronic version(s)
https://doi.org/10.1016/j.sandf.2019.09.001 (Access: Open)
 

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