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Erschienen in: Soft Computing 7/2022

31.10.2021 | Application of soft computing

A framework to predict the load-settlement behavior of shallow foundations in a range of soils from silty clays to sands using CPT records

verfasst von: Hossein MolaAbasi, Aghileh Khajeh, Reza Jamshidi Chenari, Meghdad Payan

Erschienen in: Soft Computing | Ausgabe 7/2022

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Abstract

Using a set of cone penetration test (CPT) records, the current paper develops a general framework based on regression analyses to model the load-settlement (q-s) behavior of shallow foundations resting on a variety of soils ranging from silty clays to sands. A three-parameter hyperbolic function is employed to rigorously examine the obtained q-s curves and to determine the model parameters. Also, the results of some CPT soundings, including the corrected cone tip resistance (qt) and the skin friction (Rf), are adopted to predict the results of plate load tests (PLT). The findings corroborate the high accuracy of the proposed model, the reasonable performance of the hyperbolic function and the use of the Volterra series to predict the q-s curves. Moreover, the obtained curves from the newly developed model are compared to those from other methods in the literature which cross-confirms the efficacy of the current model. A sensitivity analysis is also conducted, and the exclusive effects of all the contributing parameters are assessed among which Rf is shown to be the most influential. Ultimately, simple solutions are adopted to determine various key geotechnical parameters, like the ultimate bearing capacity (qult), the allowable bearing capacity (qa) and the modulus of subgrade reaction (ks).

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Metadaten
Titel
A framework to predict the load-settlement behavior of shallow foundations in a range of soils from silty clays to sands using CPT records
verfasst von
Hossein MolaAbasi
Aghileh Khajeh
Reza Jamshidi Chenari
Meghdad Payan
Publikationsdatum
31.10.2021
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 7/2022
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-021-06485-8

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