초록

본 논문에서는 역해석 방법 중 직접법의 성능에 큰 영향을 미치는 최적화 과정을 인공지능의 한 기법인 유전자알고리즘을 이용하여 역해석 프로그램을 구성하였다. 유전자 알고리즘 및 역해석 기법의 효용성을 검증하기 위하여 과거 역해석 연구 사례 중의 하나인 Gens et al(1987)과 동일한 암반조건을 가진 모델에 대한 역해석을 실시하여 그 결과를 비교${\cdot}$검토하였다. 경부고속철도 터널 현장의 내공변위 및 천단침하에 대한 계측자료로부터 최종 내공변위의 예측함수를 결정하는 방법으로 터널의 총 변위를 분석하였다. 이를 역해석에 필요한 입력자료로 활용하여 역해석을 실시하고 터널 주변 암반의 거동을 반영할 수 있는 지반의 특성치를 구하였다. 각 현장 시험에서 얻어진 지반의 특성치와 비교한 결과 본 연구에서 적용된 유전자 알고리즘을 이용한 역해석 방법이 유의한 수준의 결과를 도출하고 있다는 사실을 확인하였다.

Abstract

In this study, the back analysis program was developed by applying the genetic algorithm, one of artificial intelligence fields, to the direct method. The optimization process which has influence on the efficiency of the direct method was modulated with genetic algorithm. On conditions that the displacement computed by forward analysis for a certain rock mass model was the same as the displacement measured at the tunnel section, back analysis was executed to verify the validity of the program. Usefulness of the program was confirmed by comparing relative errors calculated by back analysis, which is carried out under the same rock mass conditions as analysis model of Gens et at (1987), one of back analysis case in the past. We estimated the total displacement occurring by tunnelling with the crown settlement and convergence measured at the working faces in three tunnel sites of Kyungbu Express railway. Those data measured at the working face are used for back analysis as the input data after confidence test. As the results of the back analysis, we comprehended the tendency of tunnel behaviors with comparing the respective deformation characteristics obtained by the measurement at the working face and by back analysis. Also the usefulness and applicability of the back analysis program developed in this study were verified.

주제어

#Back analysis   #Field measurements   #Genetic algorithms  

저자의 다른 논문

참고문헌 (22)

1. Chamber, L. (1995), Practical Handbook of Genetic Algorithms, Vol.1, CRC Press, Inc., pp.436-440 
2. Gens, A., Ledesma, A. and Alonso, E. E. (1987), 'Maximum Likelihood Parameter and Variance Estimation in Geotechnical Back Analysis', Proc. 5th Int, Conf. Applications of Statistics and Prob. in soil and Struct. Eng., pp.613-621 
3. Hanafy, E. A and J. J. Emery (1980), 'Advancing face simulation of tunnel excavation and lining placement', 13th Canadian Rock Mechanics Symp., CIMM, Montreal, pp.119-125 
4. Hoek E. and E. T. Brown (1997), 'Practical estimates of rock mass strength', Int, J. Rock Mech. Min. Sci. & Geomech. Abstr., Vol.34, No.8, pp.1165-1186 
5. Otsuka, M. and T. Kondoh (1981), 'On the displacement fore-casting methods and their application to tunnelling by NATM', Int. Symp. on Weak Rock, Tokyo, pp.945-950 
6. Serafim, L. J. and P. J. Pereira (1983), 'Consideration on the geomechanical classification of Bieniawski', Proc. of the Int. Symp. on Engineering Geology and Underground Construction, Vol.2, pp.33-42 
7. Srinivas, L.M. Patnaik (1994), 'Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms', IEEE Trans on SMC, Vol.24, No.2, pp.656-667 
8. Aydan, O., Ulusay, R, Kawamoto, T. (1997), 'Assessment of rock mass strength for underground excavation', Proceddings of the 1997 36th US Rock Mechanics ISRM International Symposium International Journal of Rock Mechanics and Mining Sciences, Vol.34, No.3, pp.705 
9. Hoek, E. and E. T. Brown (1980), Underground Excavations in Rock, Institution of Mining and Metallurgy, pp.493511 
10. Mohammad, N., D. J. Reddish and L. R. Stace (1997), 'The Relation between In Situ and Laboratory Rock Properties used in Numerical Modelling', Technical Note, Int. J. Rock Mech. Min. Sci. & Geomech. Abstr., Vol.34, No.2, pp.289-297 
11. Nicholson, G. A. and Z. T. Bieniawski (1990), 'A nonlinear deformation modulus based on rock mass classification', Int. J. Min. & Geological Engng., 8, pp.181-202 
12. Holland, J. H. (1975), Adaptation in Natural and Artificial Systems, Univ. Michigan, Ann Arbor, MI. 
13. Sakurai, S. and Takeuchi, K. (1983), 'Back Analysis of Measured Displacements of Tunnels', Rock Mech. Rock Eng. 16, 1983, pp.173-180 
14. Goldberg, D. E (1989), 'Genetic Algorithm in Search', Optimization & Machine earning, Addison-Wesley 
15. Vassilev, V. H. and T. N. Hrisstov (1988), 'Influence of the heading face and a two dimensional calculation model of tunnel linings', 6th Int. Conf. on Numer. Methods in Geomech., lnnsbruck, Vol.3, pp.279-289 
16. Mitri, H. S., R. Edrissi and J. Henning (1994), 'Finite element modelling of cable-bolted stopes in hard rock underground mines', SME Annual Meeting, Paper No.94-116 
17. Sulem J., Panet M. and Guenot A. (1987a), 'Closure analysis in deep tunnels', Int. J. Rock Mech. Min. Sci. & Geomech. Abstr., Vol.24, No.3, pp.145-154 
18. Bieniawski, Z. T. (1978), 'Determination of rock mass defor-mability : Experience from case histories', Int. J. Rock Mech. Min. Sci. & Geomech. Abstr., 15, pp.237-247 
19. Ledesma A., Gens A. and Alonso E. E. (1996), 'Estimation of Parameters in Geotechnical Back analysis - I. Maximum Likelihood Approach', Computers and Geomechanics, Vol.8, No.1, pp.1-27 
20. Panet, M., and A Guenot (1982), 'Analysis of convergence behind the face of tunnel', Tunnelling 82, IMM, Brighton, pp.197-204 
21. Goldberg, D. E, and Deb, K. (1991), 'A Comparative Analysis of Selection Schemes used in Genetic Algorithms', Foundations of Genetic Algorithms, Morgan Kaufmann. pp.69-93 
22. Cividiai, A, Jurina, L. and Gioda, G. (1981), 'Some Aspects of Characterization Problems in Geomechanics', Int. J. Rock Mech. Min. Sci. and Geomech. Abstr. 18 pp.487-503 

이 논문을 인용한 문헌 (0)

1. 이 논문을 인용한 문헌 없음