Improving Tunnel Boring Machine Tunneling Performance by Investigating the Particle Size Distribution of Rock Chips and Cutter Consumption
Abstract
:1. Introduction
2. Project Background
3. Rock Chip Sieving and Laboratory Tests
3.1. On-Site Rock Chip Sieving Test
3.2. Preparation of Rock Samples
3.3. Cerchar Abrasivity Test
4. Correlations among CI, SE, and Tunneling Parameters
4.1. Specific Energy (SE)
4.2. Coarseness Index (CI)
4.3. Correlation between CI and SE
4.4. Correlation between Rock-Breaking Efficiency and Tunneling Parameters
5. Influence of Dry and Saturated Conditions on TBM Tunneling Efficiency and Optimization of Tunneling Parameters
5.1. Optimization of Tunneling Parameters Based on CI
5.2. Optimization of Tunneling Parameters Based on Cutter Consumption
5.3. Optimal Tunneling Parameters Considering CI and Cutter Consumption
6. Conclusions
- Both SE and the CI exhibit strong quadratic relationships with the Smax/P ratio. The fitting coefficients for the CI under both soft and hard rock conditions are 4.2% and 10.4% higher than those of the SE, respectively.
- Regardless of if conditions are dry or saturated, TBM cutter consumption increases exponentially with the CAI. In different lithologies under saturated conditions, cutter consumption is 15.07% to 57.06% lower compared to dry conditions.
- In both dry and saturated conditions, the CI initially increases and then decreases with an increase in the Smax/P ratio, while TBM cutter consumption decreases initially and then increases with a rise in the Smax/P ratio. There exists an optimal Smax/P value that maximizes TBM rock-breaking efficiency and minimizes TBM cutter consumption.
- Considering both TBM rock-breaking efficiency and cutter consumption, the optimal Smax/P ranges for dry conditions are 10.972–12.169, 8.495–9.457, and 16.5–17.5 for medium-hard, soft, and hard rocks, respectively. In saturated conditions, the optimal Smax/P ranges are 8.606–8.931, 7.055–8.319, and 13.50–14.00 for the same rock types. To enhance TBM construction guidance, optimal tunneling parameter ranges are suggested for various dry and saturated surrounding rock tunneling conditions.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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TBM Design Parameters | Water Conveyance Tunnel | |
---|---|---|
TBM1 | TBM2 | |
TBM type | double shield | |
Tunneling diameter | 5460 mm | 5460 mm |
Number of disc cutters | 37 | 30 |
Center disc cutter/diameter | 6/432 mm | 4/432 mm |
Inner cutter/diameter | 21/483 mm | 17/483 mm |
Gauge cuter/diameter | 10/483 mm | 9/483 mm |
Maximum cutter spacing | 86 mm | 83 mm |
Cutter head speed | 0~10.3 r·min−1 | 0~8.7 r·min−1 |
Cutter head power | 1800 kW | 2100 kW |
Maximum cutter head thrust | 22,160 kN | 11,900 kN |
Rating torque | 3458 kN·m | 4210 kN·m |
Breakaway torque | 5878 kN·m | 6940 kN·m |
Maximum tunneling speed | 120 mm·min−1 | 120 mm·min−1 |
Rock Lithology | Code Name | Sample Number | CAIdry | Average CAIdry | Code Name | CAIsat | Average CAIsat |
---|---|---|---|---|---|---|---|
Metamorphic andesite | A | A1 | 2.435 | 2.530 | A5 | 1.846 | 2.006 |
A2 | 2.358 | A6 | 1.553 | ||||
A3 | 2.746 | A7 | 2.439 | ||||
A4 | 2.581 | A8 | 2.184 | ||||
Sandstone | S | S1 | 0.751 | 0.846 | SH5 | 0.564 | 0.747 |
S2 | 0.978 | SH6 | 0.939 | ||||
S3 | 0.835 | SH7 | 0.741 | ||||
S4 | 0.821 | SH8 | 0.743 | ||||
Granite | H | H1 | 2.933 | 3.523 | H5 | 2.581 | 2.905 |
H2 | 3.751 | H6 | 2.943 | ||||
H3 | 3.323 | H7 | 3.261 | ||||
H4 | 4.085 | H8 | 2.834 | ||||
Quartz schist | Y | Y1 | 4.169 | 3.488 | SP5 | 3.041 | 3.024 |
Y2 | 3.323 | SP6 | 2.822 | ||||
Y3 | 3.647 | SP7 | 3.254 | ||||
Y4 | 2.813 | SP8 | 2.978 | ||||
Quartz diorite | SY | SY1 | 3.539 | 3.167 | SY5 | 3.219 | 3.102 |
SY2 | 2.959 | SY6 | 3.411 | ||||
SY3 | 2.953 | SY7 | 3.042 | ||||
SY4 | 3.215 | SY8 | 2.734 |
Group Number | Surrounding Rock Grade | Sieve Quality (kg) | Smax/P | SE (kJ/m3) | CI |
---|---|---|---|---|---|
1 | IV | 178.81 | 6.38 | 30,024.92 | 312.13 |
2 | IV | 108.20 | 5.2 | 31,784.36 | 279.29 |
3 | III | 215.17 | 9.8 | 19,939.43 | 347.60 |
4 | III | 164.30 | 5.4 | 29,866.75 | 326.74 |
5 | III | 119.80 | 9.5 | 17,356.68 | 366.00 |
6 | III | 104.61 | 7.22 | 27,396.53 | 328.00 |
7 | III | 194.37 | 9 | 19,616.44 | 350.66 |
Group Number | Surrounding Rock Grade | Sieve Quality (kg) | Smax/P | SE (kJ/m3) | CI |
---|---|---|---|---|---|
1 | II | 180.50 | 22.25 | 78,505.88 | 377.28 |
2 | II | 171.15 | 23.25 | 68,820.04 | 350.74 |
3 | II | 263.17 | 20.11 | 51,575.24 | 430.81 |
4 | II | 212.74 | 12.29 | 32,221.89 | 448.88 |
5 | II | 175.07 | 12.6 | 29,259.62 | 454.06 |
6 | II | 239.25 | 17.2 | 38,060.04 | 457.58 |
7 | II | 214.14 | 20.5 | 46,150.56 | 429.67 |
Rock Lithology | Dry | Saturated | ||
---|---|---|---|---|
CAIdry | Cutter Consumption 10−3 Piece m−3 | CAIsat | Cutter Consumption (10−3 Piece∙m−3) | |
Metamorphic andesite | 2.530 | 2.568 | 2.006 | 1.204 |
Sandy stone | 0.846 | 0.669 | 0.747 | 0.642 |
Granite | 3.523 | 5.640 | 2.905 | 2.422 |
Quartz schist | 3.488 | 6.070 | 3.024 | 2.741 |
Quartz diorite | 3.167 | 5.066 | 3.102 | 2.942 |
Rock Lithology | Soft Rock | Medium-Hard Rock | Hard Rock | |
---|---|---|---|---|
The optimal Smax/P range determined based on CI | Dry | 7.976~9.457 | 10.414~12.169 | 17.465~19.369 |
Sat | 6.502~8.769 | 8.606~11.656 | 14.514~16.193 | |
The optimal Smax/P range determined based on cutter consumption | Dry | 8.495–9.749 | 10.972–12.246 | 14.511–16.640 |
Sat | 7.055~8.319 | 7.187~8.641 | 10.945~13.163 | |
The optimal Smax/P range recommendation | Dry | 8.495~9.457 | 10.972~12.169 | 16.5~17.5 |
Sat | 7.055~8.319 | 8.606~8.931 | 13.50~14.00 |
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Wang, W.; Yan, C.; Guo, J.; Zhao, H.; Li, G.; Yao, W.; Ren, T. Improving Tunnel Boring Machine Tunneling Performance by Investigating the Particle Size Distribution of Rock Chips and Cutter Consumption. Buildings 2024, 14, 1124. https://doi.org/10.3390/buildings14041124
Wang W, Yan C, Guo J, Zhao H, Li G, Yao W, Ren T. Improving Tunnel Boring Machine Tunneling Performance by Investigating the Particle Size Distribution of Rock Chips and Cutter Consumption. Buildings. 2024; 14(4):1124. https://doi.org/10.3390/buildings14041124
Chicago/Turabian StyleWang, Wei, Changbin Yan, Jing Guo, Hailei Zhao, Gaoliu Li, Wenmin Yao, and Taozhe Ren. 2024. "Improving Tunnel Boring Machine Tunneling Performance by Investigating the Particle Size Distribution of Rock Chips and Cutter Consumption" Buildings 14, no. 4: 1124. https://doi.org/10.3390/buildings14041124