Predicting penetration rate of hard rock tunnel boring machine using fuzzy logic

Ebrahim Ghasemi, Saffet Yagiz, Mohammad Ataei

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

Predicting the penetration rate of a tunnel boring machine (TBM) plays an important role in the economic and time planning of tunneling projects. In the past years, various empirical methods have been developed for the prediction of TBM penetration rates using traditional statistical analysis techniques. Soft computing techniques are now being used as an alternative statistical tool. In this study, a fuzzy logic model was developed to predict the penetration rate based on collected data from one hard rock TBM tunnel (the Queens Water Tunnel # 3, Stage 2) in New York City, USA. The model predicts the penetration rate of the TBM using rock properties such as uniaxial compressive strength, rock brittleness, distance between planes of weakness and the orientation of discontinuities in the rock mass. The results indicated that the fuzzy model can be used as a reliable predictor of TBM penetration rate for the studied tunneling project. The determination coefficient (R2), the variance account for and the root mean square error indices of the proposed fuzzy model are 0.8930, 89.06 and 0.13, respectively.

Original languageEnglish
Pages (from-to)23-35
Number of pages13
JournalBulletin of Engineering Geology and the Environment
Volume73
Issue number1
DOIs
Publication statusPublished - Feb 1 2014
Externally publishedYes

Fingerprint

TBM
fuzzy mathematics
hard rock
Fuzzy logic
Tunnels
penetration
Rocks
tunnel
rock property
compressive strength
rock
Soft computing
discontinuity
statistical analysis
Brittleness
rate
Mean square error
Compressive strength
Statistical methods
prediction

Keywords

  • Fuzzy logic
  • Rate of penetration (ROP)
  • Rock properties
  • Tunnel boring machine (TBM)

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geology

Cite this

Predicting penetration rate of hard rock tunnel boring machine using fuzzy logic. / Ghasemi, Ebrahim; Yagiz, Saffet; Ataei, Mohammad.

In: Bulletin of Engineering Geology and the Environment, Vol. 73, No. 1, 01.02.2014, p. 23-35.

Research output: Contribution to journalArticle

@article{7fd399bf9c524c34bc24fcb71b1843a9,
title = "Predicting penetration rate of hard rock tunnel boring machine using fuzzy logic",
abstract = "Predicting the penetration rate of a tunnel boring machine (TBM) plays an important role in the economic and time planning of tunneling projects. In the past years, various empirical methods have been developed for the prediction of TBM penetration rates using traditional statistical analysis techniques. Soft computing techniques are now being used as an alternative statistical tool. In this study, a fuzzy logic model was developed to predict the penetration rate based on collected data from one hard rock TBM tunnel (the Queens Water Tunnel # 3, Stage 2) in New York City, USA. The model predicts the penetration rate of the TBM using rock properties such as uniaxial compressive strength, rock brittleness, distance between planes of weakness and the orientation of discontinuities in the rock mass. The results indicated that the fuzzy model can be used as a reliable predictor of TBM penetration rate for the studied tunneling project. The determination coefficient (R2), the variance account for and the root mean square error indices of the proposed fuzzy model are 0.8930, 89.06 and 0.13, respectively.",
keywords = "Fuzzy logic, Rate of penetration (ROP), Rock properties, Tunnel boring machine (TBM)",
author = "Ebrahim Ghasemi and Saffet Yagiz and Mohammad Ataei",
year = "2014",
month = "2",
day = "1",
doi = "10.1007/s10064-013-0497-0",
language = "English",
volume = "73",
pages = "23--35",
journal = "Bulletin of the International Association of Engineering Geology - Bulletin de l'Association Internationale de G{\'e}ologie de l'Ing{\'e}nieur",
issn = "0074-1612",
publisher = "Springer Verlag",
number = "1",

}

TY - JOUR

T1 - Predicting penetration rate of hard rock tunnel boring machine using fuzzy logic

AU - Ghasemi, Ebrahim

AU - Yagiz, Saffet

AU - Ataei, Mohammad

PY - 2014/2/1

Y1 - 2014/2/1

N2 - Predicting the penetration rate of a tunnel boring machine (TBM) plays an important role in the economic and time planning of tunneling projects. In the past years, various empirical methods have been developed for the prediction of TBM penetration rates using traditional statistical analysis techniques. Soft computing techniques are now being used as an alternative statistical tool. In this study, a fuzzy logic model was developed to predict the penetration rate based on collected data from one hard rock TBM tunnel (the Queens Water Tunnel # 3, Stage 2) in New York City, USA. The model predicts the penetration rate of the TBM using rock properties such as uniaxial compressive strength, rock brittleness, distance between planes of weakness and the orientation of discontinuities in the rock mass. The results indicated that the fuzzy model can be used as a reliable predictor of TBM penetration rate for the studied tunneling project. The determination coefficient (R2), the variance account for and the root mean square error indices of the proposed fuzzy model are 0.8930, 89.06 and 0.13, respectively.

AB - Predicting the penetration rate of a tunnel boring machine (TBM) plays an important role in the economic and time planning of tunneling projects. In the past years, various empirical methods have been developed for the prediction of TBM penetration rates using traditional statistical analysis techniques. Soft computing techniques are now being used as an alternative statistical tool. In this study, a fuzzy logic model was developed to predict the penetration rate based on collected data from one hard rock TBM tunnel (the Queens Water Tunnel # 3, Stage 2) in New York City, USA. The model predicts the penetration rate of the TBM using rock properties such as uniaxial compressive strength, rock brittleness, distance between planes of weakness and the orientation of discontinuities in the rock mass. The results indicated that the fuzzy model can be used as a reliable predictor of TBM penetration rate for the studied tunneling project. The determination coefficient (R2), the variance account for and the root mean square error indices of the proposed fuzzy model are 0.8930, 89.06 and 0.13, respectively.

KW - Fuzzy logic

KW - Rate of penetration (ROP)

KW - Rock properties

KW - Tunnel boring machine (TBM)

UR - http://www.scopus.com/inward/record.url?scp=84930182131&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84930182131&partnerID=8YFLogxK

U2 - 10.1007/s10064-013-0497-0

DO - 10.1007/s10064-013-0497-0

M3 - Article

VL - 73

SP - 23

EP - 35

JO - Bulletin of the International Association of Engineering Geology - Bulletin de l'Association Internationale de Géologie de l'Ingénieur

JF - Bulletin of the International Association of Engineering Geology - Bulletin de l'Association Internationale de Géologie de l'Ingénieur

SN - 0074-1612

IS - 1

ER -