Creep characteristics are integral mechanical properties of rock salt and are related to both long-term stability and security of rock salt repository. Rock salt creep properties are studied in this paper through employing combined methods of theoretical analysis and numerical simulation with a nonlinear creep model and the secondary development in FLAC^3Dsoftware. A numerical simulation of multistage loading creep was developed with the model and resulting calculations were found consequently to coincide with previously tested data.

Noise-vibration-harshness (NVH) design optimization problems have become major concerns in the vehicle product development process. The Body-in-White (BIW) plays an important role in determining the dynamic characteristics of vehicle system during the concept design phase. Finite Element (FE) models are commonly used for vehicle design. However, even though the speed of computers has been increased a lot, the simulation of FE models is still too time-consuming due to the increase in model complexity. For complex systems, like vehicle body structures, the numerous design variables and constraints make the FE simulations based optimization design inefficient. This calls for the development of a systematic and efficient approach that can effectively perform optimization to further improve the NVH performance, while satisfying the stringent design constraints.In the present work, an efficient method to optimize the structural dynamic response is proposed considering the low-frequency NVH performances. As a first step, to reduce computational burden, a response sensitivity analysis is performed to detect the most important variables prior to the design optimization. Then an analytical approximation model of vibration resonance peak is constructed and coupled with the adaptive simulated annealing (ASA) algorithm to replace the time-consuming finite element analysis. Subsequently, an optimization of NVH performance considering dynamic response is formulated and carried out. The methodology aims at improving the NVH behavior of body structure by simultaneously suppressing several resonance peaks. Finally, the proposed method and its process are successfully illustrated through a vehicle body example. The results demonstrate that the proposed method of incorporating response surface model with ASA algorithm is feasible and cost-efficient in solving the vibration optimization problem.

Utilizing deep rock salt cavern is not only a widely recognized energy reserve method but also a key development direction for implementing the energy strategic reserve plan. And rock salt cavern adopts solution mining techniques to realize building cavity. In view of this, the paper, based on the dissolving properties of rock salt, being simplified and hypothesized the dynamic dissolving process of rock salt, combined conditions between dissolution effect and seepage effect in establishing dynamic dissolving models of rock salt under different flow quantities. Devices were also designed to test the dynamic dissolving process for rock salt samples under different flow quantities and then utilized the finite-difference method to find the numerical solution of the dynamic dissolving model. The artificial intelligence algorithm, Particle Swarm Optimization algorithm (PSO), was finally introduced to conduct inverse analysis of parameters on the established model, whose calculation results coincide with the experimental data.