Surrogate‐Based Multisource Sensitivity Analysis of TBM Driving System

Abstract

TBM cutterhead driving system is generally an extraordinarily large and complex machine containing lots of parameters; understanding and assessment of its dynamic characteristics are a great challenge as each of these parameters has uncertainty. In this work, a hierarchical modeling method for the dynamic model of the complex gear transmission system is proposed based on the generalized finite element modeling idea. On this basis, the whole machine dynamic model of cutterhead driving system is established; both the characteristics of vibration responses and the meshing force are revealed. Vibration responses under the action of simulated load are estimated and verified by comparing with the data measured on the tunneling field, where the error is about 18%∼50%. With the vibration response of the key nodes and the dynamic meshing force for the system dynamic characteristic evaluation index, considering the change of input parameters such as external loads, material parameters, meshing parameters, and coupling parameters, the global parameter sensitivity of system dynamic characteristics is analyzed based on the technology of surrogate model. Finally, variation of dynamic characteristics considering the interaction of polytypic parameters is obtained.

Sequential and Iterative Distributed Model Predictive Control of Multi-Motor Driving Cutterhead System for TBM

“…When the backlash of the ith gear pair i b = 0, we have ϕ i = 1 and β i = − e i (t) r i ; (ii) The period time-varying parameters k t,i , c t,i and e i are simplified with the average values, that are k t,i = k 0 , c t,i = c 0 , e i (t) = e 0 andė(t) = 0. It has been shown in [41] that the variation range of backlash parameter is only between [−0.2 0.2]µm, compared with the diameter of the driving motor (generally 30 centimeters), these nonlinearities are neglectable if we design robust controller for the cutterhead system.…”

A New Evaluation Method for the Uniaxial Compressive Strength ahead of the Tunnel Face Based on the Driving Data and Specification Parameters of TBM

“…Encouraged by the opening of Japan's Sei-kan tunnel (50.5 km in length) and the British-French submarine tunnel (53.9 km in length), a large number of larger scheme extralong tunnels have been planned in China and abroad, for example, the Japanese-Korean submarine tunnel between Fukuoka and Busan (250.0 km), Gotthard railway tunnel in Switzerland (56.9 km), and the Basis Brenner railway tunnel between Austria and Italy (55.0 km). Compared with traditional techniques such as drilling and blasting, the fullface rock tunnel boring machine (TBM) has gradually become the first choice for long and deep tunnel construction in recent years since it has many advantages, such as high quality, high efficiency, environmental protection, and small disturbance of surrounding rock [1,2]. As one of the most fundamental mechanical parameters, UCS has widely been applied in the process of TBM construction including assessment of rockmass rating (RMR) and Q TBM rockmass system, hazard assessment of rockburst classification or TBM jamming and assessment of the reasonable supporting design [3][4][5][6].…”

An Efficient Global Optimization Approach for Reliability Maximization of Friction‐Tuned Mass Damper‐Controlled Structures

“…In order to find a trade-off between computational cost and global optimization, this paper investigates the performance of efficient global optimization (EGO) for the probability of failure minimization in FTMD design. To balance exploration and exploitation, EGO uses information from kriging [10,11], which provides a prediction of the value of the original function as well as the stochastic error associated with such a value. e expected improvement infill criterion is employed to guide the EGO search, since it presented robust results in a series of optimization problems [12].…”