Abstract
Data detailed on artificial intelligence have been presented. According to news originating from Ultimo, Australia, by NewsRx correspondents, research stated, “At the initial phases of tunnel design, information on rock properties is often limited.” Our news correspondents obtained a quote from the research from University of Technology Sydney: “In such instances, the engineering classification of the rock is recommended as a primary assessment of its geotechnical condition. This paper reviews different rock mass classification methods in the tunnel industry. First, some important considerations for the classification of rock are discussed, such as rock quality designation (RQD), uniaxial compressive strength (UCS) and groundwater condition. Traditional rock classification methods are then assessed, including the rock structure rating (RSR), rock mass rating (RMR), rock mass index (RMI), geological strength index (GSI) and tunnelling quality index (Q system). As RMR and the Q system are two commonly used methods, the relationships between them are summarized and explored. Subsequently, we introduce the detailed application of artificial intelligence (AI) method on rock classification.”
NETL
NSTL