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Bulletin of Engineering Geology and the Environment

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01.11.2010 | Original Paper

The use of artificial neural networks to predict the effect of sulphate attack on the strength of cemented paste backfill

verfasst von: L. Orejarena, Mamadou Fall

Erschienen in: Bulletin of Engineering Geology and the Environment | Ausgabe 4/2010

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Abstract

The growing use of cemented paste backfill (CPB) as a ground support method in mining and also as an environmentally friendly alternative for mine waste disposal demands a better understanding of the different processes that affect its strength. Due to its nature as cement based material, CPB is prone to the progressive loss of strength with sulphate attacks under certain conditions. The paper provides a background to sulphate attacks in CPB and artificial neural networks (ANN) and presents a model to predict the unconfined compressive strength of a CPB under sulphate attack, based on different water cement ratios, binder composition and binder content.

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Nächster Artikel Discussion of the paper by I. Sass and U. Burbaum entitled “A method for assessing adhesion of clays to tunneling machines” (doi:10.1007/s10064-008-0178-6)

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Titel: The use of artificial neural networks to predict the effect of sulphate attack on the strength of cemented paste backfill
verfasst von: L. Orejarena
Mamadou Fall
Publikationsdatum: 01.11.2010
Verlag: Springer-Verlag
Erschienen in: Bulletin of Engineering Geology and the Environment / Ausgabe 4/2010
Print ISSN: 1435-9529
Elektronische ISSN: 1435-9537
DOI: https://doi.org/10.1007/s10064-010-0326-7

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