Dynamic classification method for TBM cutting face rock mass boreability based on tunneling characteristics and multi-criteria decision analysis

• A rock mass boreability evaluation method for TBM tunnel construction is proposed. • Wave velocity is used to enrich the rock characteristics of the unexcavated surface. • Evaluating boreability using multiple excavation characteristics reduces randomness. • This method achieves peak prediction accuracy of 93 % in boreability classification. Current rock mass classification methods are primarily suitable for drill-and-blast tunnels. To meet the demand for rapid perception of geological changes in TBM-constructed tunnels, a dynamic classification method for rock mass boreability at the TBM cutting face is proposed, based on tunneling characteristics and multi-criteria decision analysis (MCDA). First, massive TBM tunneling data undergoes batch real-time processing to extract key feature data. Second, four parameters—FPI, TPI, PR, and P—are selected as comprehensive boreability evaluation indices. Concurrently, UCS, BTS, J S , and V P are chosen as classification criteria parameters. A boreability classification method for rock masses ahead of the TBM cutting face is established using the VIKOR algorithm. The incorporation of P-wave velocity compensates for the lack of characteristic information in unexcavated surrounding rock. Based on field data from multiple TBM projects, the rock mass boreability is classified into five levels (from level 1 to level 5, with drillability becoming worse gradually). Furthermore, a prediction model for real-time boreability classification of the near face rock mass is developed, using real-time tunneling parameters as inputs. The model achieves average and peak prediction accuracies of 86 % and 93 %, respectively.