The Nishihara creep model is an extremely effective method in the field of sandstone creep model research. However, the Nishihara creep model curve for sandstone under the marine environment (the coupled effect of chemical corrosion and temperature) does not fit the actual creep test data well. Based on the Nishihara creep model, we discovered that, on the one hand, the viscoelastic elements in the Nishihara model are replaced by the viscoelastic elements containing temperature and pH factors, which can accurately describe the influence of temperature and pH on rock creep characteristics; on the other hand, the viscoplastic elements in the Nishihara model are replaced by nonlinear viscoplastic elements, which can accurately describe the accelerated creep stage of the rock mass. After modifying Nishihara’s creep model twice, a new temperature–pH damage nonlinear creep model is established. The creep curve of the temperature–pH damage nonlinear creep model is compared with the creep test data of sandstone. The comparison results indicate that the creep curve of the nonlinear creep model has a high degree of fit with the creep test data of sandstone (accuracy > 92%). This validates the correctness of the newly established temperature–pH damage nonlinear creep model presented in this paper, demonstrating that the new model can effectively reflect the influence of temperature and pH on the creep characteristics of sandstone.

This study aimed to investigate the feasibility of using a model based on particle swarm optimization (PSO) and support vector machine (SVM) to predict the unconfined compressive strength (UCS) of cemented paste backfill (CTB). The dataset was built based on the experimental UCS values. Results revealed that the categorized randomly segmentation was a suitable approach to establish the training set. The PSO performed well in the SVM hyperparameters tuning; the optimal hyperparameters for the SVM to predict the UCS of CTB in this study were C = 71.923, ε = 0.0625, and γ = 0.195. The established model showed a high accuracy and efficiency on the prediction work. The R² value was 0.97 and the MSE value was 0.0044. It was concluded that the model was feasible to predict the UCS of CTB with high accuracy and efficiency. In the future, the accuracy and robustness of the prediction model will be further improved as the size of the dataset continues to grow.

The antiknock capability and thermal protection performance of rescue capsules mainly depend on the structural design of the cabin. By designing a new type of cabin structure, it can resist the impact of explosion shock waves and thermal shocks. In this paper, a new honeycomb-like cabin is proposed; the model has a novel thermal insulation layer design. Then, the antiknock capabilities and thermal protection analysis are carried out by using computer software. The “Autodyn” analysis module in ANSYS Workbench 17.0 has been used to simulate the explosion of TNT with a certain quality in a single room. The pressure map over time and the pressure variation curve at different locations for a single room are obtained. Through the analysis module “Transient Structural,” the stress and deformation of the honeycomb-like cabin under the blast load are simulated. The “Transient Thermal” analysis module in the finite element software is used to conduct a transient thermal analysis on the cabin structure. The temperature map and the temperature rise curve of each layer of the cabin cases are obtained. The analysis results indicate that the honeycomb-like cabin design has a good antiknock capability and thermal protection performance, and it can meet the usage requirements of the rescue capsule under dangerous conditions.

Due to the complexity of occlusal contact, force and trajectory tracking is a crucial problem for the chewing robots. A position-based impedance control is proposed to realize hybrid control of chewing force and chewing trajectory in this paper. To eliminate the steady-state error of the single impedance control in uncertain environment, a novel adaptive impedance control is proposed for chewing robots and its adaptive control law is induced using Lyapunov stability theory. Simulations are conducted to test the performances of force tracking with the single impedance control and the novel adaptive impedance control, respectively. The findings of the simulations clearly demonstrate that the proposed adaptive impedance control outperforms the conventional single impedance control in force tracking.