Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
An Extended Multifactorial Fuzzy Prediction of Hard Rock TBM Penetrability
Abstract This paper presents an extended multifactorial fuzzy evaluation of hard rock tunnel boring machine performance. Several modifications have been applied to an earlier work of the authors team in 2009 to capture better prediction capabilities of TBM penetrability modeling. In this new work, five linguistic categories, ranging from “Very Poor” to “Very Good”, have been considered to represent penetrability classes which are described by Sigmoidal fuzzy membership functions to consider the relationship between machine’s rate of penetration and the ground characteristics including intact rock and rock mass properties. A comprehensive database of a total of 151 tunnel sections was employed for this purpose. Also, several experts from different fields of tunneling have been asked to evaluate the criteria using fuzzy Delphi analytical hierarchy process technique instead of relying upon the authors’ knowledge and expertise. The results have been verified by comparisons to the actual field penetration data as well as the results of other predictive models from the literature, showing a very good conformity between measurements and predictions of this research compared to all the previous models. It proves not only the superiority of the utilized methodology, but also its field applicability in future tunneling projects in similar geological conditions.
An Extended Multifactorial Fuzzy Prediction of Hard Rock TBM Penetrability
Abstract This paper presents an extended multifactorial fuzzy evaluation of hard rock tunnel boring machine performance. Several modifications have been applied to an earlier work of the authors team in 2009 to capture better prediction capabilities of TBM penetrability modeling. In this new work, five linguistic categories, ranging from “Very Poor” to “Very Good”, have been considered to represent penetrability classes which are described by Sigmoidal fuzzy membership functions to consider the relationship between machine’s rate of penetration and the ground characteristics including intact rock and rock mass properties. A comprehensive database of a total of 151 tunnel sections was employed for this purpose. Also, several experts from different fields of tunneling have been asked to evaluate the criteria using fuzzy Delphi analytical hierarchy process technique instead of relying upon the authors’ knowledge and expertise. The results have been verified by comparisons to the actual field penetration data as well as the results of other predictive models from the literature, showing a very good conformity between measurements and predictions of this research compared to all the previous models. It proves not only the superiority of the utilized methodology, but also its field applicability in future tunneling projects in similar geological conditions.
An Extended Multifactorial Fuzzy Prediction of Hard Rock TBM Penetrability
Mikaeil, Reza (Autor:in) / Zare Naghadehi, Masoud (Autor:in) / Ghadernejad, Saleh (Autor:in)
2017
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
BKL:
57.00$jBergbau: Allgemeines
/
38.58
Geomechanik
/
57.00
Bergbau: Allgemeines
/
56.20
Ingenieurgeologie, Bodenmechanik
/
38.58$jGeomechanik
/
56.20$jIngenieurgeologie$jBodenmechanik
An Extended Multifactorial Fuzzy Prediction of Hard Rock TBM Penetrability
| Online Contents | 2017
Multifactorial fuzzy approach to the penetrability classification of TBM in hard rock conditions
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Multifactorial fuzzy approach to the penetrability classification of TBM in hard rock conditions
| Online Contents | 2009
Multifactorial fuzzy approach to the penetrability classification of TBM in hard rock conditions
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| Springer Verlag | 2022