Quality classification of rock mass based on MCS-TOPSIS coupling model

The quality classification of rock mass is a basic geotechnical engineering issue. The classification of rock mass quality shows the uncertainty due to the fuzziness and randomness of the rock mass parameters. The effect of parameter uncertainty on the classification results is ignored in the existing classification model. The reliability method was thus introduced into the classification of rock mass quality, and a coupled model of Monte Carlo simulation(MCS) and technique for order preference by similarity to ideal solution(TOPSIS) was proposed, which can consider the effect of the parameter uncertainty on the classification. The model consists of two parts. One part is to obtain the weight of classification system index with the game theory and to determine the limit-state equation of the reliability with the TOPSIS model, and the other part is to perform uncertainty analysis and to provide the final classification result based on the probability function. The TOPSIS model was tested with 25 sets of samples. The analysis results of the MCS-TOPSIS model indicate that the misjudgment ratio of the model is 0. The quality classification of the surrounding rock at Shuibuya underground powerhouse is examined based on the certainty and uncertainty methods using Matlab programs. The results demonstrate that it is feasible to use the MCS-TOPSIS model to classify the rock mass quality and the model has high accuracy and is easy to use. © 2017, Science Press. All right reserved.