Journal of Korean Tunnelling and Underground Space Association (한국터널지하공간학회 논문집)

Korean Tunnelling and Underground Space Association (한국터널지하공간학회)
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Development and implementation of a knowledge based TBM tunnel segment lining design program

지식기반형 TBM 터널 세그먼트 라이닝 설계 프로그램의 개발 및 적용

  • 정용준 (성균관대학교 글로벌건설엔지니어링학과) ;
  • 유충식 (성균관대학교 건설환경시스템공학과)
  • Received : 2014.05.10
  • Accepted : 2014.05.27
  • Published : 2014.05.31
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Abstract

This paper concerns the development of a knowledge-based tunnel design system within the framework of artifical neural networks(ANNs). The system is aimed at expediting a routine tunnel design works such as computation of segment lining body forces and stability analysis of selected cross section. A number of sub-modules for computation of segment lining body forces and stability analysis were developed and implemented to the system. It is shown that the ANNs trained with the results of 3D numerical analyses can be generalized with a reasonable accuracy, and that the ANN based tunnel design concept is a robust tool for tunnel design optimization. The details of the system architecture and the ANNs development are discussed in this paper.

본 논문에서는 인공신경망 기술을 이용한 TBM 터널 세그먼트 라이닝의 설계 시스템 개발에 관한 내용을 다루었다. 먼저 개발 시스템에 대한 개념 및 개발 과정과 시스템을 구성하는 각 요소기술 및 개별 모듈 개발에 관한 내용을 기술하였다. 본 시스템의 요소기술인 ANN-기반의 세그먼트 라이닝 부재력 예측 시스템에 대해 그 개념과 ANN 학습과정 및 검증과정을 기술하였다. ANN-기반의 세그먼트 라이닝 부재력 예측은 유한요소해석을 토대로 구축한 DB를 ANN을 통해 일반화 한 후 개발된 엔진을 세부 모듈에 접목시켜 별도의 해석 없이 유사 단면 혹은 현장에 적용이 가능하도록 하였다. 또한 해석 대상 단면에 대하여 상용 유한요소해석 프로그램과 연계하여 해석 Input파일의 자동생성이 가능하도록 하였으며 유한요소해석 결과를 통한 단면 검토가 가능하도록 하였다.

Keywords

References

  1. Bae, G.J., Shin, H.S., Kim, D.G., Chang, S.H., Lim, J.J., Lee, G.P., Choi, S.W., KICT (2005), "Development of technologies for minimizing and preventing the disaster on tunnel construction 2", KICT, pp. 73-87.
  2. KTA (2008), "3rd Mechanized tunnel construction tunnel design service technical conference", KTA, pp. 3-7, 393-399, 457-458.
  3. Yoo, C.S., Kim, J.M., Kim, S.B., Jung, H.Y. (2006), "Tunnel design/construction risk assessment based on GIS-ANN", Journal of the Korean Society of Civil Engineers, Vol. 26, No. 1C, pp. 63-72.
  4. Yoo, C.S., Kim, S.B., Yoo, K.H. (2008), "Development of IT-based tunnel design system", Journal of Korean Tunnelling and Underground Space Association, Vol. 10, No. 2, pp. 153-166.
  5. Yoo, C.S., Jeon, H.M. (2012), "A comparative study on methods for shield tunnel segment lining sectional forces", Journal of Korean Tunnelling and Underground Space Association, Vol. 14, No. 3, pp. 159-181. https://doi.org/10.9711/KTAJ.2012.14.3.159
  6. Yoo, C.S., Jeon, Y.W., Kim, J.H., Park, Y.J., Yoo, J.H. (2004), "Development and implementation of a GIS-based tunnelling risk management system", Journal of Korean Geotechnical Society, Vol. 20, No. 1, pp. 49-59.
  7. Chang, S.H., Lee, G.P., Choi, S.W., Bae, G.J. (2011), "State of the art of segment lining in shield tunnel and statistical analysis of its key design parameters", Journal of Korean Society of Rock Mechanics, Vol. 6, No. 6, pp. 427-438.
  8. Japan society of civil engineers (2007), Standard specifications for tunneling-2006 : Shield tunnels, Japan society of civil engineers.
  9. Kim, C.Y., Bae, G.J., Hong, S.W., Park, C.H., Moon, H.K., Shin, H.S. (2001), "Neural network based prediction of ground surface settlements due to tunneling", Computers and Geotechnics, Vol. 28, pp. 517-547. https://doi.org/10.1016/S0266-352X(01)00011-8
  10. Duddeck, H., Erdmann, J. (1985), "Structure design for tunnels", Tunnel82, Proceedings of the 3rd international symposium, Brighton, 7-11 June 1982, pp. 83-91.
  11. International Tunnelling Association Working Group No. 2. (2000), "Guidelines for the design of shield tunnel lining", Tunnelling and Underground Space Technology, Vol. 15, No. 3, pp. 303-331. https://doi.org/10.1016/S0886-7798(00)00058-4
  12. Muirwood, A.M. (1975), "The circular tunnel in elastic ground", Geotechnique, Vol. 25, No. 1, pp. 115-127. https://doi.org/10.1680/geot.1975.25.1.115
  13. Mark Hudson Beale, Martic T. Hagan, Howard B. Demuth (2013), Neural Network Toolbox User's Guide, Mathwork Inc.
  14. Jiao, Y., Hudson, J.A. (1995), "The fully-coupled model for rock engineering system", Rock Mechanics and Mining Sciences & Geomechanics, Vol. 32, Issue 5, pp. 491-512. https://doi.org/10.1016/0148-9062(95)00038-I
  15. Yang, Y., Zhang, Q. (1997), "A hierarchical analysis for rock engineering using artificial neural networks", Rock Mechanics and Rock Engineering, Vol. 30, Issue 4, pp. 207-222. https://doi.org/10.1007/BF01045717
  16. Yang, Y., Zhang, Q. (1998), "The application of neural networks to rock engineering system (RES)", Rock Mechanics and Mining Sciences, Vol. 35, Issue 6, pp. 727-745. https://doi.org/10.1016/S0148-9062(97)00339-2

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