scholarly journals Correlation of P-wave Velocity with Rock Quality Designation (RQD) in Volcanic Rocks

2019 ◽  
Vol 3 (2) ◽  
pp. 11
Author(s):  
Ainul Fatayaatis Salaamah ◽  
Teuku Faisal Fathani ◽  
Wahyu Wilopo
Keyword(s):  
Rock Mass ◽  
Wave Velocity ◽  
Volcanic Rocks ◽  
Rock Mass Classification ◽  
Classification Systems ◽  
P Wave ◽  
Rock Quality Designation ◽  
Rock Quality ◽  
P Wave Velocity ◽  
Mass Classification

One important part of rock mass investigation is the geomechanical assessment in terms of rock mass classification systems. Rock mass classification is one of themost efficient methods in rock mechanics to provide a basic understanding of rock masscharacterization. Rock mass properties can be determined by a seismic refraction surveyas an indirect geophysical assessment. In this study, the P-wave velocity from seismicrefraction was compared with the Rock Quality Designation (RQD) from the boreholes.The empirical correlation between the RQD and the P-wave velocity was found by usingthe linear regression analysis. The RQD value estimated from the P-wave velocity can beapplied for tropical environment study with geological conditions of volcanic rocks. This study helps to estimate and predict the subsurface rock quality, to reduce investigation costs, and to improve understanding of subsurface rock quality.

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.

Comparison of rock mass classification systems

2007 ◽  
Vol 43 (4) ◽  
pp. 404-408 ◽  
Author(s):  
R. Rahmannejad ◽  
H. Mohammadi
Keyword(s):  
Rock Mass ◽  
Rock Mass Classification ◽  
Classification Systems ◽  
Mass Classification
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