Why the future of rock mass classification systems requires revisiting their empirical past

Beverly Yang, Amichai Mitelman, Davide Elmo, Doug Stead

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Despite recent efforts, digitization in rock engineering still suffers from the difficulty in standardizing and statistically analysing databases that are created by a process of quantification of qualitative assessments. Indeed, neither digitization nor digitalization have to date been used to drive changes to the principles upon which, for example, the geotechnical data-collection process is founded, some of which have not changed in several decades. There is an empirical knowledge gap that cannot be bridged by the use of technology alone. In this context, this paper presents the results of what the authors call a rediscovery of rock mass classification systems, and a critical review of their definitions and limitations in helping engineers to integrate these methods and digital acquisition systems. This discussion has significant implications for the use of technology as a tool to directly determine rock mass classification ratings and for the application of machine learning to address rock engineering problems.

Original languageEnglish
Article numberqjegh2021-039
JournalQuarterly Journal of Engineering Geology and Hydrogeology
Volume55
Issue number1
DOIs
StatePublished - Feb 2022
Externally publishedYes

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