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Triaxial compression behavior of sand and tire wastes using neural networks

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Abstract

Tire waste additions to sand enhance the shear strength of sand for embankments. Granular and fiber shape tire wastes and their mixture with sand under drained and undrained conditions were tested in triaxial compression apparatus and modeled using neural networks (NN). In the experimental study, tire crumb and tire buffings inclusions were used at varying contents as soil reinforcement. Both quick tests and consolidated drained (CD) triaxial tests were performed to analyze the effects of tire content, tire shape, and tire aspect ratio on the shear strength of sand. Then, this extensive experimental database obtained in laboratory was used in training, testing, and prediction phases of three neural network-based soil models. The input variables in the developed NN models are tire wastes content, tire wastes type, test type, effective stress, and axial strain, and the output is the deviatoric stress. The accuracy of proposed models seems to be satisfactory. Furthermore, the proposed models are also presented as simple explicit mathematical functions for further use by researchers.

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Authors and Affiliations

  1. Department of Earthquake Engineering, Bogazici University, Istanbul, Turkey

    Ayse Edincliler

  2. Department of Civil Engineering, University of Gaziantep, Gaziantep, Turkey

    Ali Firat Cabalar & Abdulkadir Cevik

  3. Department of Civil Engineering, Bogazici University, Istanbul, Turkey

    Ahmet Cagatay

Authors
  1. Ayse Edincliler
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  2. Ali Firat Cabalar
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  3. Ahmet Cagatay
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  4. Abdulkadir Cevik
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Correspondence to Ali Firat Cabalar.

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Edincliler, A., Cabalar, A.F., Cagatay, A. et al. Triaxial compression behavior of sand and tire wastes using neural networks. Neural Comput & Applic 21, 441–452 (2012). https://doi.org/10.1007/s00521-010-0430-4

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  • DOI: https://doi.org/10.1007/s00521-010-0430-4

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