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Optimal geotechnical site investigations for slope design
Discipline of Civil, Surveying & Environmental Engineering, Priority Research Centre for Geotechnical Science & Engineering, The University of Newcastle, Callaghan, Australia.
Discipline of Civil, Surveying & Environmental Engineering, Priority Research Centre for Geotechnical Science & Engineering, The University of Newcastle, Callaghan, Australia.
Department of Civil and Environmental Engineering, Colorado School of Mines, Golden, CO, USA.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
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2019 (English)In: Computers and geotechnics, ISSN 0266-352X, E-ISSN 1873-7633, Vol. 114, article id 103111Article in journal (Refereed) Published
Abstract [en]

Site investigation in combination with field and laboratory testing, plays a vital role in characterizing the soil profile for geotechnical design in order to reduce uncertainty. In spite of this, site investigations are often limited in scope due to high costs. In this paper, conditional random fields are used to examine the influence of soil strength mean, standard deviation and spatial correlation length on the risk of slope design failure for different levels of site investigation scope. An undrained slope example is used to illustrate how the proposed approach can be used to assess the risk reduction that can be obtained as the scope of a site investigation is increased. By combining the cost of site investigation with the cost of slope failure, the results indicate that there exists an optimal site investigation scope, beyond which the cost of additional boreholes does not justify the cost savings due to reduced slope failure risk.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 114, article id 103111
Keywords [en]
Geotechnical site investigation, Sampling strategy, Risk analysis, Conditional random field
National Category
Geotechnical Engineering
Research subject
Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-75134DOI: 10.1016/j.compgeo.2019.103111Scopus ID: 2-s2.0-85067178667OAI: oai:DiVA.org:ltu-75134DiVA, id: diva2:1332877
Note

Validerad;2019;Nivå 2;2019-06-28 (johcin)

Available from: 2019-06-28 Created: 2019-06-28 Last updated: 2019-06-28Bibliographically approved

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Meng, Jingjing

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