Attribute recognition model for risk assessment of water inrush

Abstract

An attribute recognition model of water inrush risk evaluation is established based on attribute mathematic theory and software is developed for risk assessment in a tunnel. In our model, the entropy weight method is applied to analyze the weights of evaluation indexes. Considering karst hydrologic and engineering geological conditions of a tunnel under construction, eight major influencing factors of water inrush (formation lithology, unfavorable geology, groundwater level, attitude of rocks, contact zone of dissolvable and insoluble rocks, layer and interlayer fissures, catchment ability and surrounding rock mass classification) are selected as the evaluation indexes, and an index system of water inrush risk assessment is constituted. The tunnel is divided into 26 sections, and 340 evaluation objects are selected from these 26 sections in order to construct a judgment matrix. The water inrush risk of the whole tunnel is evaluated by using the proposed software. The results indicate that the attribute recognition model of water inrush risk evaluation is scientific and reasonable and that the software is convenient for use in calculations and is easy to master.