scholarly journals Drill Monitoring for Rock Mass Grouting: Case Study at the Stockholm Bypass

2020 ◽  
Author(s):  
Jeroen van Eldert ◽  
Johan Funehag ◽  
Håkan Schunnesson ◽  
David Saiang
Keyword(s):  
Rock Mass ◽  
Environmental Impact ◽  
Water Loss ◽  
Penetration Rate ◽  
Classification Systems ◽  
Water Ingress ◽  
Measurement While Drilling ◽  
Mass Classification ◽  
The Mean

Abstract In tunneling, rock mass grouting is a method applied to reduce water ingress. Grouting is influenced by rock mass conditions, especially apertures, frequency, and continuation of fracturing. These rock mass conditions can partly be determined by rock mass classification systems. At the Stockholm bypass, the Measurement While Drilling (MWD) Fracturing Index was applied to characterize the rock mass for grouting purposes, with a focus on adjusting the grout hole drill plan to minimize environmental impact. This study divided the rock mass in a 1.9 km tunnel into six categories based on rock mass conditions, identifying rock mass quality, apparent fracturing, and grout consumption. These categories were then compared with the mean fracturing index based on the coefficients of penetration rate and rotation pressure variations, as well as grout consumption at each grout umbrella. The fracturing index was 93% successful in assessing favorable and unfavorable rock mass conditions in the studied tunnel and 85% successful in determining grout consumption. Finally, a conceptual method was developed to reduce the grouting activities using the MWD fracturing index and water loss tests. The introduction of this conceptual method for grouting decisions could potentially reduce 59% of the umbrellas found in the case study.

scholarly journals Rock Mass Classification for Columnar Jointed Basalt: A Case Study of Baihetan Hydropower Station

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Shiyue Zhang ◽  
Mingjie He ◽  
Jinjian Gu ◽  
Zhihao Cui ◽  
Jian Wang ◽  
...  
Keyword(s):  
Rock Mass ◽  
Classification Scheme ◽  
Jointed Rock ◽  
Rock Mass Classification ◽  
Classification Systems ◽  
Hydropower Station ◽  
Columnar Jointed Basalt ◽  
Baihetan Hydropower Station ◽  
Mass Classification

Rock mass classification is important in preliminary design of geotechnical engineering projects. Using the columnar jointed basalt at the foundation of Baihetan Hydropower Station as an example, this paper presents a classification scheme of the columnar jointed rock. Unlike many common rock masses, an obvious characteristic of columnar jointed rock is that it is discontinuous in geometry while continuous in mechanics. Due to the inapplicability of existing rock mass classification systems, a classification scheme, combined with rock mass integrity, weak plane tightness, and permeability, is proposed. The new classification system has five grades with quantitative factors, which takes into account the features of columnar joints. As an easy-to-use scheme and case study, it would be helpful as a reference in the rock mass classification of similar problems.

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

2021 ◽  
pp. qjegh2021-039
Author(s):  
Beverly Yang ◽  
Amichai Mitelman ◽  
Davide Elmo ◽  
Doug Stead
Keyword(s):  
Rock Mass ◽  
Rock Mass Classification ◽  
Classification Systems ◽  
Empirical Knowledge ◽  
Rock Engineering ◽  
Geotechnical Data ◽  
Use Of Technology ◽  
Data Collection Process ◽  
Engineering Problems ◽  
Mass Classification

Despite recent efforts, digitisation in rock engineering still suffers from the difficulty in standardising and statistically analysing databases that are created by a process of quantification of qualitative assessments. Indeed, neither digitisation nor digitalisation 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 which 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.

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