Rock Mass Classification in the Digital Era: A transformation in Hard Rock Tunnelling

被引:0
|
作者
Klein, Lasse [1 ]
Lehmann, Gabriel [1 ]
Troendle, Johannes [2 ]
di Benedetto, Diego [2 ]
机构
[1] Herrenknecht AG, Geotechn, Schwanau Allmannsweier, Germany
[2] Herrenknecht AG, T&I Digital, Schwanau Allmannsweier, Germany
来源
1ST INTERNATIONAL ROCK MASS CLASSIFICATION CONFERENCE, RMCC 2024 | 2024年 / 1435卷
关键词
D O I
10.1088/1755-1315/1435/1/012005
中图分类号
学科分类号
摘要
The construction industry has witnessed a transformative shift with the advent of digitalization, and tunnelling especially in hard rock is no exception. This study delves into the profound influence of digitalization on rock mass assessment methods employed in tunnelling endeavours. Conventional rock mass classification systems, such as the widely embraced RMR (Rock Mass Rating) and Q-system, have traditionally played a pivotal role in evaluating geological conditions and providing guidance for engineering decisions in hard rock tunnelling projects. While these systems are invaluable for project selection and execution, it is noteworthy that they may not always offer a comprehensive representation, and their applicability can be limited, especially in smaller-diameter tunnelling projects, as evidenced by experience from numerous past projects. The development in the field of machine intelligence and the connectivity of IT systems has increased significantly. The introduction of BIM and numerous independent platforms for construction companies, the processes of all project participants are becoming increasingly digitalized, with professional data management now an essential component of successful process management. Modern OT and IT interfaces make it possible to combine different data sources and to display and analyse them in data management tools. A comparison between geotechnical data and operational parameters can provide important conclusions for the further course of the project. In increasingly complex contract situations, the comparison between expected and encountered geology, in combination with real-time machine data, can be a crucial element between for all involved construction project shareholders.
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页数:11
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