# Performance Analysis of Tunnel Boring Machines for
## 2 Data Collection for Performing Statistical Analysis  
The purpose of the experimental analysis was to identify and evaluate the correlations between the mechanical parameters of the TBMs and any links between them and the speed of advancement, also according to the geological characteristics of the rock mass. For this purpose, a robust database was built to perform statistical analyses [12; 15; 16; 18; 20; 21; 22; 23; 24; 25; 26; 31; 32; 37; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57]; it includes information from 302 tunnels excavated by TBM (open, single shield, and double shield), with a total length of 2200 km. It was structured by assigning to each tunnel the following information: name of the project; country where the project was carried out; contract of the work; purpose; geological context; overburden material; Rock Mass Rating (RMR) and UCS; excavation diameter; length; construction period; feed rate; machine manufacturer and type of machine; number of tools on the excavation head; tools diameter; installed power; thrust; cutterhead rotation speed; and torque. It is pointed out that, for many tunnels, only a few data were available. As for the geological characteristics of the rock mass encountered, only qualitative descriptions were found, and almost no parameters characterizing the rock mass from a geomechanical point of view were found; this partially limited the work. In addition, the average advancement rate was found only in very few cases since, most of the time, TBM manufacturers only provide the peak speeds recorded during the excavation. In this regard, since the utilization coefficient was not available, the feed rate was tentatively calculated as the ratio between the tunnel length and the construction time. Obviously, the data contain all the downtimes related to possible machine stoppages due to the replacement of the tools and to different organizations of the work shifts. Because of this, the results of the processing are not provided in this work, as the information obtained was too scattered and unreliable. Once the database was completed, the statistical analysis was carried out. First, based on the type of machine examined (open, single shield, double shield TBM) the following correlations were analyzed: diameter--power; diameter--thrust; diameter--torque; diameter--cutterhead rotation speed; thrust--torque; power--torque; power--thrust.  
For each of the pairs of parameters, different regression functions were evaluated, and the one that returned the highest value of R\({}^{2}\) (coefficient of determination) was chosen as a statistical measure of how close the data are to the fitted regression line. Admissible values of R\({}^{2}\) range between 1 and 0 but only high R\({}^{2}\) values indicated that the model explains all the variability of the response data around its mean. So, the higher the R\({}^{2}\), the better the model fits the data.  
Correlation equations that took into account the geological aspect were sought, albeit not in detail, due to the lack of geomechanical parameters. In this context, a series of filterswas applied, and the behavior in five different rock types was examined for each type of machine. The statistical analysis was carried out in the same way as in the previous cases, considering only the correlations where the number of available data was greater than 10. Finally, in the last phase of the study, links were sought between the machine parameters and the forward speed, according to the type of rock and machine.