In the heart of China, researchers at Southwest Jiaotong University are revolutionizing the way we approach tunneling and rock-breaking, with significant implications for the energy sector. Youlin Qin, a leading expert from the School of Civil Engineering and the State Key Laboratory of Intelligent Geotechnics and Tunnelling, has been spearheading a study that could dramatically improve the efficiency of tunnel boring machines (TBMs) and reduce costs in underground construction.
The research, published in the journal “Underground Space” (which translates to “Underground Space” in English), focuses on the intricate relationship between rock brittleness and the optimal spacing of TBM cutters. This might sound like a niche topic, but the implications are vast, particularly for the energy sector where underground construction is a critical component of infrastructure development.
Qin and his team have discovered that as the rock brittleness index (BI) increases, the way rocks fracture changes significantly. “We found that with higher BI, the number, depth, and width of tensile cracks increase, and the cracks shift from horizontal to oblique orientations,” Qin explains. This understanding is crucial because it directly impacts the efficiency of rock-breaking and, consequently, the overall performance of TBMs.
One of the most compelling findings is that moderate cutter spacing—around 90 to 110 millimeters—is optimal for generating these tensile cracks. This is a game-changer because it means TBMs can be fine-tuned to work more efficiently, reducing the time and cost of tunneling projects. For instance, the study found that the rock-breaking force increases significantly with higher BI. At 80 millimeters spacing, the maximum force for rock with a BI of 13.134 was 5.51 times that for rock with a BI of 4.731. This insight could lead to more precise and cost-effective tunneling strategies.
The team also developed four intelligent hybrid models to optimize cutter spacing, with the particle swarm optimization and extreme gradient boosting (PSO-XGBoost) model standing out for its high performance. This model achieved an R2 of 0.994, VAF of 99.418%, RMSE of 0.987, and MAPE of 5.217% on the test datasets. “The PSO-XGBoost model demonstrates the highest performance, providing a robust tool for optimizing cutter spacing,” Qin notes.
The practical applications of this research are immense. For the energy sector, which often involves complex underground construction projects, this could mean faster, more efficient, and cost-effective tunneling. This could be particularly impactful for projects involving geothermal energy, hydroelectric power, and underground storage facilities.
Looking ahead, this research could shape the future of tunneling and underground construction. By understanding the nuances of rock brittleness and optimizing cutter spacing, engineers can design more efficient TBMs and reduce the environmental impact of tunneling projects. It’s a step towards smarter, more sustainable underground construction, and it’s all thanks to the groundbreaking work being done at Southwest Jiaotong University.
As the energy sector continues to evolve, the need for efficient and cost-effective underground construction will only grow. This research provides a crucial piece of the puzzle, offering a pathway to more intelligent and optimized tunneling practices. It’s a testament to the power of scientific inquiry and its potential to transform industries.