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  5. Use of a genetic algorithm to perform reliability analysis of unsaturated soil slopes
 
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Use of a genetic algorithm to perform reliability analysis of unsaturated soil slopes

Author(s)
Gavin, Kenneth  
Xue, Jianfeng  
Uri
http://hdl.handle.net/10197/3103
Date Issued
2009-08
Date Available
2011-08-26T13:43:42Z
Abstract
Rainfall induced landslides are a major cause of disturbance to transport networks in many parts of the world. In slopes where the water table is some depth below the ground surface, negative pore water pressure (suctions) develop in the near surface soils which contribute significantly to their overall stability. However, these suctions are transient and reduce as water percolates into the slope (and a wetting front develops) during periods of heavy or prolonged rainfall.

In this paper the development of a model for determining the reliability of a slope in which the soil properties are considered as random variables is presented. By transforming the variables into polar coordinates the complexities associated with defining the limit state function, which have affected many previous attempts at probabilistic analysis of slopes, can be overcome. The minimisation problem is solved in a powerful and efficient Genetic Algorithm environment.
Sponsorship
Other funder
Other Sponsorship
Iarnród Éireann
Type of Material
Journal Article
Publisher
Institution of Civil Engineers
Journal
Géotechnique
Volume
59
Issue
6
Start Page
545
End Page
549
Copyright (Published Version)
2009 Thomas Telford Publishing Ltd.
Subjects

Failure

Partial saturation

Slopes

Suction

Subject – LCSH
Slopes (Soil mechanics)--Stability
Soil mechanics
Genetic algorithms
DOI
10.1680/geot.8.T.004
Web versions
http://dx.doi.org/10.1680/geot.8.T.004
Language
English
Status of Item
Peer reviewed
ISSN
0016-8505
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
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Owning collection
Civil Engineering Research Collection
Mapped collections
Critical Infrastructure Group Research Collection•
Urban Institute Ireland Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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