A dice similarity measure for TBM penetrability classification in hard rock condition with the intuitionistic fuzzy information of rock mass properties. Issue 14 (6th December 2021)

• Record Type: Journal Article
• Authors: Yong, Rui; Ye, Jun; Du, Shi-Gui; Zhang, He; Gu, Leiyu; Lin, Hang
• Is Part Of: European journal of environmental and civil engineering. Volume 25:Issue 14(2021)
• Page Start: 2658
• Page End: 2673
• Publication Date: 2021-12-06
• Subjects: Intuitionistic fuzzy set -- penetrability classification -- similarity measure -- TBM; Sustainable engineering -- Periodicals; Civil engineering -- Environmental aspects -- Periodicals; Environmental engineering -- Periodicals; 628
• DOI: 10.1080/19648189.2019.1643789
• Languages: English
• ISSNs: 1964-8189

Abstract

Abstract: Penetration rate is a key parameter for the performance prediction of hard rock tunnel boring machines (TBM), which has a high correlation with rock mass properties. The purpose of this study is to find an appropriate method for estimation of penetrability classification of TBM. To achieve this aim, a similarity measure model and a classification method were proposed based on the similarity measures of intuitionistic fuzzy sets of rock properties. The relationships between actual measured TBM penetration rate and rock properties were discussed by statistical analysis on the published database obtained from Queens's tunnel project in New York. Then the rock mass parameters were classified into three categories and these normalized categories were transformed into intuitionistic fuzzy sets. According to the Dice similarity measures between the vectors of rock mass properties at each tunnel station, the TBM penetrability conditions in hard rocks can be predicted and described into Good, Medium, and Poor classes. Eventually, in comparison with the measured penetrability results, this suggested method was demonstrated to be effective for penetrability classification with accuracy of 77.5%.