중대단면 TBM 설계 사양 예측을 위한 DB분석

Database Analysis for Estimating Design Parameters of Medium to Large-Diameter TBM

Abstract

TBM은 사전에 예측하지 못한 지반조건의 변화에 대한 대응력이 재래식 공법과 비교할 때 상대적으로 낮기 때문에, 설계단계에서 TBM의 사전 성능예측과 공사기간 산정을 위한 굴진율 예측이 매우 중요하다. 기존 연구에서 구축된 211개의 TBM 데이터베이스에 신규 데이터를 추가하여 TBM의 핵심 제작 사양인 최대 추력, 커터헤드 최대 토크 및 회전속도, 커터헤드 구동력 사이의 상관관계를 지반조건에 따라 분석하였다. 기존 연구들에서와 같이 TBM의 최대추력, 최대토크, 구동력과 같은 기본 제작사양을 추정하는 데 있어 TBM 외경은 매우 중요한 정보임을 확인할 수 있었다. 국외의 TBM 데이터베이스로부터 도출된 회귀식과 본 연구로부터 얻어진 회귀식을 비교한 결과, 최대추력의 경우는 유사한 경향을 보였으나, 대단면 TBM에서 본 연구의 회귀식에서 추정된 최대토크가 국외의 회귀식보다 더 높게 추정하는 경향이 나타났다.

The Tunnel Boring Machine(TBM) is relatively insufficient to cope with unpredicted changes in ground conditions as compared with Conventional Tunnelling Methods. Therefore, it is very important to predict the TBM performance at the design stage and estimate the advance rate for the calculation of the construction period. In this study, we added data to 211 TBM databases constructed in the previous study and analyzed the correlation between TBM outer diameter, maximum thrust, maximum cutterhead torque, cutterhead driving power and RPM, which are the main design and manufacturing specifications of TBM. As a result of the analysis from results obtained in the previous studies, it was confirmed that TBM outer diameter is very effective and important in estimating maximum thrust, maximum cutterhead torque, and cutterhead driving power of the TBM. As a result of comparing the regression equations derived from other TBM databases outside the country and the regression equation obtained from the present study results, the maximum thrust showed a similar tendency to each other, but the maximum torque estimated from the regression equation of this study was higher than that of other countries in the case of the large scale TBM.

Fig. 1. Regional analysis on TBM database

Fig. 2. Basic analysis on TBM use and diameter

Fig. 3. Basic analysis on TBM type and ground condition

Fig. 4. Schematic diagram for main TBM design parameters

Fig. 5. Correlations between TBM diameter and design parameters of TBM

Fig. 6. Analysis of correlation between each design parameter of TBM

Fig. 7. Basic analysis on ground condition of EPB TBM data

Fig. 8. Correlations between EPB TBM diameter and design parameters of EPB TBM

Fig. 8. Correlations between EPB TBM diameter and design parameters of EPB TBM (Continued.)

Fig. 9. Correlations between each design parameters of EPB TBM

Fig. 10. Comparison between Ates. et al. (2014) and this study

Table 1. TBM database information

Table 2. Summary of regression functions from correlation between TBM diameter and design parameters

Table 3. Summary of regression functions obtained from correlation between design parameters of TBM

Table 4. Summary of regression functions obtained from correlation between EPB TBM diameter and design parameters of EPB TBM

Table 5. Summary of R² value of regression functions obtained from correlation between TBM diameter and four design parameters

Table 6. Summary of regression functions obtained from correlation between each design parameter of EPB TBM

Table 7. Summary of regression functions obtained from correlations for comparison between Ates et al. (2014) and this study