Risk assessment for tunnel portals in the construction stage has been widely recognized as one of the most critical phases in tunnel construction as it easily causes accident than the overall length of a tunnel. However, the risk in tunnel portal construction is complicated and uncertain which has made such a neural network very attractive to the construction projects. This paper presents a risk evaluation model, which is obtained from historical data of 50 tunnels, by combining the fuzzy method and BP neural network. The proposed model is used for the risk assessment of the Tiefodian tunnel. The results show that the risk evaluation level is IV, slope instability is the greatest impact index among four risk events, and the major risk factors are confirmed. According to the evaluation results, corresponding risk control measures are suggested and implemented. Finally, numerical simulation is carried out before and after the implementation of risk measures, respectively. The rationality of the proposed risk evaluation model is proved by comparing the numerical simulation results.

Intermediate principal stress is a significant factor when calculate to determine the surrounding rock loose circles. Based on it, this paper is trying to modify the Hoek-Brown strength criterion, and put forwards a theoretical formula of the loose circle radius. The theoretical formula is applied to Shimen Tunnel, and a comparative analysis between theoretical calculations and field test results is conducted. Here are the results as follows: 1) With an increase of intermediate principal stress, the strength of the rock mass increases and the surrounding rock becomes more difficult to break. Consequently, loose circle thickness is gradually reduced and forms a significant negative linear relationship with the Lode parameter. 2) The results indicate that with a decrease of surrounding rock level in a three-lane hard rock tunnel, the radius of the loose circle increases continuously. 3) The results of the field acoustic wave test show that the theoretical calculation values are consistent with the field measurement results. According to above analysis, the deduced formula is feasible.

Given that rock masses are complex, the geomechanical parameters of rock masses are hard to determine in underground engineering. In this paper, the inverse model and method are established to identify the parameters based on the coupled stress and fluid flow model combined with the finite element method and adaptive genetic algorithm. Moreover, the model and method are applied in the Lianghekou highway tunnel, and the initial permeability coefficients of the stratum and the lateral pressure coefficients of the initial ground stress are identified by the back analysis with relative errors of the measured and fitted values at measuring points below 5%. Results show that the inverse model and method are effective and sound.

Recycling construction and demolition waste not only reduces project costs; and saves natural resources, but also solves the environmental threat caused by construction waste disposal. In this paper, C25 waste road concrete is used as an experimental material, the uniaxial compression strength and tensile splitting strength of C25 RAC whose coarse aggregate replacement rate is 0%, 25%, 50%, 75%, and 100% are tested under the condition that the water-to-cement ratio is 0.47, 0.55 and 0.61. The results show: (1) the uniaxial compression strength and tensile splitting strength decrease with the increase of RAC; (2) for concrete with the same water-to-cement ratio, when the coarse aggregate replacement rate changes from 0% to 50%, the uniaxial compression strength and tensile splitting strength of RAC changes slightly. When the coarse aggregate replacement rate changes from 50% to 100%, the uniaxial compression strength and tensile splitting strength of RAC decreases rapidly.