Skip to main content
SpringerLink
Log in

Optimal disc cutters plane layout design of the full-face rock tunnel boring machine (tbm) based on a multi-objective genetic algorithm

  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

Improving of the quality of the disc cutters’ plane layout design of the full-face rock tunnel boring machine (TBM) is the most effective way to improve the global performance of a TBM. The plane layout design of disc cutters contains multiple complex engineering technical requirements and belongs to a multi-objective optimization problem with multiple nonlinear constraints. Based on analysis of the technical requirements of the plane layout problem, an optimizing mathematical model was built. To obtain a set of design schemes for engineers to choose from, a multi-objective genetic algorithm (MOGA) was applied to carry out the optimization of the mathematical model. A constraint-domination principle was utilized to handle the constraints, and a nondominated sorting method was adopted to obtain Pareto solutions. Simulation results showed that the proposed method was efficient and accurate in obtaining the Pareto layout solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. R. Gertsch, L. Gertsch and J. Rostami, Disc cutting tests in Colorado Red Granite: implications for TBM performance prediction, International Journal of Rock Mechanics and Mining Sciences, 44 (2007) 238–246.

    Article  Google Scholar 

  2. J. Rostami, Development of a force estimation model for rock fragmentation with disc cutters through theoretical modeling and physical measurement of crushed zone pressure [Doctor Dissertation], Golden, Colorado, USA: Dept of Mining Engineering. Colorado School of Mines, (1997).

    Google Scholar 

  3. J. Rostami, L. Ozdemir and B. Nilson, Comparison between CSM and NTH hard rock TBM performance prediction models, Proc. of Institute of Shaft Drilling Technology (ISDT) annual Technical Conference’96, Las Vegas (1996) 11.

  4. J. Rostami and L. Ozdemir, Computer modeling of mechanical excavators cutterhead, Proc. of the World Rock Boring Association Conference, Ontario (1996).

  5. Q. M. Gong, J. Zhao and A. M. Hefny, Numerical Simulation of Rock Fragmentation Process Induced by Two TBM Cutters and Cutter Spacing Optimization, AITES-ITA 2006 congress, Seoul, South Korea (2006) 263–270.

  6. Q. M. Gong, Y. Y. Jiao and J. Zhao, Numerical modeling of the effects of joint orientation on rock fragmentation by TBM cutters, Tunnelling and Underground Spacing Technology, 20(1) (2005) 183–191.

    Article  Google Scholar 

  7. Q. M. Gong, Y. Y. Jiao and J. Zhao, Numerical modeling of the effects of joint spacing on rock fragmentation by TBM cutters. Tunnelling and Underground Spacing Technology, 21(1) (2006) 46–55.

    Article  Google Scholar 

  8. L. Ozdemir and F. D. Wang, Mechanical tunnel boring prediction and machine design. Washington, USA, (1979).

  9. R. A. Snowdon, M. D. Ryley and J. Temporal, A study of disc cutting in selected British rocks, Journal of Rock Mechanics and Mining Sciences and Geomechanics Abstracts, 19 (1982) 107–121.

    Article  Google Scholar 

  10. CSM, computer model for TBM performance prediction. www.mines.edu.emipaperscomputer_modeling_for_mechani cal_excavatorstbm_performance_prediction.pdf, (2003).

  11. J. Rostami, Hard Rock TBM Cutterhead Modeling for Design and Performance Prediction, DOI:10.1002/geot. 200800002, (2008).

  12. Z. H. Zhang, An Investigation in the Cutter Arrangement Rules for Tunneler Disk, Construction Machinery and Equipment, 7 (1996) 24–25.

    Google Scholar 

  13. S. S. Qiao, C. J. Mao and C. Liu, Full-face Rock Tunnel Boring Machine. Petroleum industry press, Beijing, China, (2005).

    Google Scholar 

  14. C. M. Fonseca and P. J. Fleming, An overview of evolutionary algorithms in multiobjective optimization,. Evolutionary Computation, 3(1) (1995) 1–16.

    Article  Google Scholar 

  15. N. Srinivas and K. Deb, Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms,. Evolutionary Computation, 3(2) (1994) 221–248.

    Article  Google Scholar 

  16. T. Lan, S. R. Liu and X. S. Gu, Multi-objective Optimization Approaches Based on the Evolutionary Algorithms, Control and Decision Making, 21(6) (2006) 601–605.

    MATH  Google Scholar 

  17. K. Deb, A. Pratap and S. Agarwal, A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6(2) (2002) 182–197.

    Article  Google Scholar 

  18. C. A. Coello, A Comprehensive Survey of Evolutionary Based Multi-objective Optimization Techniques, Knowledge and Information Systems, 1(3) (1999) 269–308.

    Google Scholar 

  19. W. Jakob, Application of Genetic Algorithms to Task Planning and Learning, Parallel Problem solving from Nature. 2nd workshop, lecture notes in computer science, Amsterdam, North-Holland Publishing Company, In: Manner R and Manderick B, (1992) 291–300.

    Google Scholar 

  20. P. B. Wienke, Multicriteria Target Optimization of Analytical Procedures Using a Genetic Algorithm, Analytical Chimica Acta, 265(2) (1992) 211–225.

    Article  Google Scholar 

  21. K. Deb, A. Pratap and T. Meyarivan, Constrained Test Problems for Multi-objective Evolutionary Optimization. Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization (EMO-2001), (2001) 284–298.

  22. D. A. G. Vieira, R. L. S. Adriano and J. A. Vasconcelos, Treating Constraints as Objectives in Multiobjective Optimization Problems Using Niched Pareto Genetic Algorithm, IEEE Transaction on Magnetics, 40(2) (2004) 1188–1191.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Dalian University of Technology, Dalian, 116024, P.R. China

    Junzhou Huo & Wei Sun

  2. School of Naval Architecture Engineering, Dalian University of Technology, Dalian, 116024, P.R. China

    Jing Chen

  3. Northern Heavy Shenyang Heavy Machinery Group Co., Ltd., Shenyang, 110025, P.R. China

    Pengcheng Su & Liying Deng

Authors
  1. Junzhou Huo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wei Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jing Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pengcheng Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Liying Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wei Sun.

Additional information

This paper was recommended for publication in revised form by Associate Editor Yong Tae Kim

Jun-Zhou Huo received his B.S. in Mechanical Engineering from Henan University of Science and Technology, China, in 2001. He then received his M.S. and Ph.D. degrees from Dalian University of Technology in 2003 and 2007, respectively. Dr. Huo is currently a postdoctor at the School of Mechanical Engineering at Dalian University of Technology in Dalian, China. His research interests include layout optimization and TBM cutter head design.

Wei Sun received his B.S. in Mechanical Engineering from Dalian University of Technology, China, in 1988. He then received his M.S. and Ph.D. degrees from Dalian University of Technology in 1993 and 2000, respectively. Dr. Sun is currently a professor & doctoral supervisor at the School of Mechanical Engineering at Dalian University of Technology in Dalian, China. His research interests include knowledge-based product digital design, design and optimization of complex mechanical equipment.

Jing Chen received her B.S. in Mechanical Engineering from Henan University of Science and Technology, China, in 2000. She then received her M.S. degree from Dalian University of Technology in 2006. Chen is currently a PHD candidate at the School of Naval Architecture Engineering at Dalian University of Technology in Dalian, China. Her research interests include optimization design and CAD.

Peng-Cheng Su received his B.S. degree from Dalian University of Technology, China, in 1982. He then received his M.S. degree from Shenyang University of Technology in 1988. Su is currently a chief engineer of Nhi Group Tunnel Broing Machine Company in Shenyang, China. His research interests include TBM design, large bucket-wheel excavator design and MW-class wind turbine design.

Li-Ying Deng received his B.S. degree from Shengyang Institute of Technology, China, in 1998. He then received his M.S. degree from Northeastern University in 2006. Deng is currently an engineer of Nhi Group Tunnel Broing Machine Company in Shenyang, China. His research interests include TBM design.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Huo, J., Sun, W., Chen, J. et al. Optimal disc cutters plane layout design of the full-face rock tunnel boring machine (tbm) based on a multi-objective genetic algorithm. J Mech Sci Technol 24, 521–528 (2010). https://doi.org/10.1007/s12206-009-1220-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-009-1220-8

Keywords

Search

Navigation