Technical Papers
Sep 14, 2022

Modeling Microtunnel Boring Machine Penetration Rate Using a Mechanistic Approach

Publication: Journal of Construction Engineering and Management
Volume 148, Issue 11

Abstract

Predicting the productivity of microtunneling construction projects is challenging, due to the complexities of this trenchless excavation method. One of these complexities is estimating the microtunnel boring machine (MTBM) penetration rate due to the complex nature of the interactions between the MTBM and the ground. In the present study, a novel mechanistic approach based on the theory of contact mechanics is proposed to determine the underlying mechanics of the MTBM penetration rate. Using the proposed mechanistic approach, an analytical model of the MTBM penetration rate is developed, and a mechanistic relationship between the MTBM penetration rate and its influential factors, namely soil properties, operational loads, and cutterhead characteristics, is established. The proposed approach is expected to provide substantial mechanistic insight with respect to MTBM penetration rates by (1) modeling penetration rates of MTBMs into soils, (2) identifying the factors that influence penetration rates based on a fundamental theoretical approach, and (3) providing a useful tool for evaluating MTBM penetration rates based on the combined influences of ground properties, operational loads, and cutterhead characteristics.

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Data Availability Statement

All models generated or used during the study are available from the corresponding author upon reasonable request. Case study data used in this research were provided by a third party. Direct requests for these materials may be made to the provider indicated in the Acknowledgements.

Acknowledgments

This project was supported by a Collaborative Research and Development Grant (CRDPJ 532148) from the Natural Sciences and Engineering Council of Canada. The authors would like to thank the Shanghai Construction Group Canada Corp. for their continued support and for providing case study data.

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Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 148Issue 11November 2022

History

Received: Jan 27, 2022
Accepted: Jul 11, 2022
Published online: Sep 14, 2022
Published in print: Nov 1, 2022
Discussion open until: Feb 14, 2023

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Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Alberta, 9105 116 St., 5-080 NREF, Edmonton, AB, Canada T6G 2W2. ORCID: https://orcid.org/0000-0003-4942-0703. Email: [email protected]
Alireza Bayat, Ph.D., M.ASCE [email protected]
P.Eng.
Professor, Dept. of Civil and Environmental Engineering, Univ. of Alberta, 9211-116 St., 7-243 D-ICE, Edmonton, AB, Canada T6G 2W2. Email: [email protected]
P.Eng.
Professor, Dept. of Civil and Environmental Engineering, Univ. of Alberta, 9105 116 St., 5-080 NREF, Edmonton, AB, Canada T6G 2W2 (corresponding author). ORCID: https://orcid.org/0000-0002-4788-9121. Email: [email protected]

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