The Chaos of the Prediction for Tailings Pond Dam Break Disasters

Tailings pond is a special geotechnical structure. It is of great significance to carry out the analysis and study of the monitoring data on tailings ponds to improve the prediction and early warning of tailings dam breaks and prevent tailings dam accidents. Based on the analysis of the basic structure of the monitoring system, the data on the displacement of the tailings dam is deeply studied using chaos theory from the perspective of non-linear dynamical systems. By compiling the software under the MATLAB environment, we obtain the Lyapunov exponent as well as the calculation method for the correlation dimension D 2 of the dynamical characteristics of the tailings pond system. The monitoring data obtained from the actual measurement is used for studying the prediction of tailings dam breaks. The prediction results show that there are non-integral dimensions and positive maximum Lyapunov exponents in the displacement evolution of the tailings dam, and that the minimum factor needed for describing the displacement evolution is greater than 3, which indicates that tailings dam is a very complex non-linear dynamical system. The maximum Lyapunov exponent can be used as an index for evaluating the displacement changes.