PNN-based Rockburst Prediction Model and Its Applications

Yu Zhou,Tingling Wang

doi:10.15446/esrj.v21n3.65216

Abstract

Rock burst is one of main engineering geological problems significantly threatening the safety of construction. Prediction of rock burst is always an important issue concerning the safety of workers and equipment in tunnels. In this paper, a novel PNN-based rock burst prediction model is proposed to determine whether rock burst will happen in the underground rock projects and how much the intensity of rock burst is. The probabilistic neural network (PNN) is developed based on Bayesian criteria of multivariate pattern classification. Because PNN has the advantages of low training complexity, high stability, quick convergence, and simple construction, it can be well applied in the prediction of rock burst. Some main control factors, such as rocks’ maximum tangential stress, rocks’ uniaxial compressive strength, rocks’ uniaxial tensile strength, and elastic energy index of rock are chosen as the characteristic vector of PNN. PNN model is obtained through training data sets of rock burst samples which come from underground rock project in domestic and abroad. Other samples are tested with the model. The testing results agree with the practical records. At the same time, two real-world applications are used to verify the proposed method. The results of prediction are same as the results of existing methods, just same as what happened in the scene, which verifies the effectiveness and applicability of our proposed work.

Highlights

Rock burst samples which come from underground rock projects in domestic and abroad are collected as training data set (Show in Table 3) and testing data set (Show in Table 4) to verify the rationality of our posed method
Probabilistic neural network (PNN) model and criterion are obtained through training data sets of rock burst samples which come from underground rock projects in domestic and abroad
The results show that the prediction results agree well with the practical records, which prove the PNN-based rock burst model is useful and available and can be applied to the prediction for the possibility and classification of rock burst in underground engineering

Summary

Introduction

A rock burst is a sudden and violent expulsion of rock from the surrounding rock mass. Rock burst is considered a dynamic instability phenomenon of surrounding rock mass of un-derground space in high geostatic stress and caused by the violent release of strain energy stored in the rock mass. Rock bursts are related to the fracture of rock in place and require two conditions for their occurrence: stress in the rock mass sufficiently high to exceed its strength, and physical characteristics of the rock which enable it to store energy up to the threshold value for sudden rupture. Rock bursts are affected by the size of excavation, becoming more likely if the excavation size is around 180m and above.

Results

Discussion

Conclusion