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The accelerated creep plays an important role in the disasters of soft-rock tunnels under high stress. However, most of previous studies only involved attenuation creep and uniform creep. Large deformation disasters of soft rock occurred during the tunneling process in the Qianzhou–Sanyangchuan Tunnel, Gusu Province, China. In the paper, we developed the nonlinear generalized Nishihara rheological model with non-stationary parameter creep (NGNRM) to simulate the accelerated creep behaviors of soft rocks under high stress, and implemented it in ABAQUS, to reveal the mechanism of large deformation of soft rock. We proposed the multi-objective back analysis method of surrounding rock mechanical parameters based on the eXtreme Gradient Boosting and the non-dominated sorting genetic algorithm-II. In addition, the orthogonal test design method was used to determine the main parameters affecting the displacement of the tunnel. Using the proposed method, we can evaluate the large deformation mechanism of deep soft rock tunnels, and scientifically determine when to reinforce to prevent a large deformation disaster of the tunnel.

Active prosthetic knees (APKs) are widely used in the past decades. However, it is still challenging to make them more natural and controllable because: (1) most existing APKs that use rigid actuators have difficulty obtaining more natural walking; and (2) traditional finite-state impedance control has difficulty adjusting parameters for different motions and users. In this paper, a flexible APK with a compact variable stiffness actuator (VSA) is designed for obtaining more flexible bionic characteristics. The VSA joint is implemented by two motors of different sizes, which connect the knee angle and the joint stiffness. Considering the complexity of prothetic lower limb control due to unknown APK dynamics, as well as strong coupling between biological joints and prosthetic joints, an adaptive robust force/position control method is designed for generating a desired gait trajectory of the prosthesis. It can operate without the explicit model of the system dynamics and multiple tuning parameters of different gaits. The proposed model-free scheme utilizes the time-delay estimation technique, sliding mode control, and fuzzy neural network to realize finite-time convergence and gait trajectory tracking. The virtual prototype of APK was established in ADAMS as a testing platform and compared with two traditional time-delay control schemes. Some demonstrations are illustrated, which show that the proposed method has superior tracking characteristics and stronger robustness under uncertain disturbances within the trajectory error in ± 0 . 5 degrees. The VSA joint can reduce energy consumption by adjusting stiffness appropriately. Furthermore, the feasibility of this method was verified in a human–machine hybrid control model.