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Artificial neural networks approach for estimating the groutability of granular soils with cement-based grouts

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Abstract

A reliable estimation of the groutability of the target geomaterial is an essential part of any grouting project. An artificial neural network (ANN) model has been developed for the estimation of groutability of granular soils by cement-based grouts, using a database of 87 laboratory results. The proposed model used the water:cement ratio of the grout, relative density of the soil, grouting pressure, and diameter of the sieves through which 15% of the soil particles and 85% of the grout pass. A very good correlation was obtained between the ANN predictions and the laboratory experiments. Comparison of these results with those obtained using traditional methods for groutability prediction confirmed the viability of using ANN to estimate groutability.

Résumé

Une estimation fiable de l’injectabilité de géomatériaux constitue une question essentielle de tout projet d’injection. Dans ce contexte, un modèle de réseau de neurones artificiel (ANN) a été développé pour l’estimation de l’injectabilité de sols granulaires par des coulis à base de ciment, en utilisant une base de données établie à partir de 87 résultats d’essais en laboratoire. Le modèle proposé considère comme paramètres d’entrée: le rapport eau-ciment du coulis, la densité relative du sol, la pression d’injection, la taille de particule du sol correspondant au passant à 15% et la taille de particule du coulis correspondant au passant à 85%. Un très bon accord a été obtenu à partir de la comparaison des résultats de l’analyse ANN avec ceux obtenus à partir des expérimentations. La comparaison de ces résultats avec ceux obtenus avec les méthodes traditionnelles pour les prévisions d’injectabilité confirment la possibilité d’utiliser le modèle ANN pour les estimations d’injectabilité.

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Authors and Affiliations

  1. Department of Civil Engineering, Gazi University, Ankara, Turkey

    E. Tekin & S. O. Akbas

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  1. E. Tekin
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  2. S. O. Akbas
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Correspondence to S. O. Akbas.

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Tekin, E., Akbas, S.O. Artificial neural networks approach for estimating the groutability of granular soils with cement-based grouts. Bull Eng Geol Environ 70, 153–161 (2011). https://doi.org/10.1007/s10064-010-0295-x

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  • DOI: https://doi.org/10.1007/s10064-010-0295-x

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