Semi-automatic characterization of fractured rock masses using 3D point clouds discontinuity orientation, spacing and SMR geomechanical classification A.Riquelme a1 R.Tomás a2 A.Abellán b3 M.Cano a4 M.Jaboyedoff b5 a Civil Engineering Department, University of Alicante, Spain b Center for Research on Terrestrial Environment, University of Lausanne, Switzerland { 1 [email protected], 2 [email protected], 3 [email protected], 4 [email protected], 5 [email protected]} April 13, 2015 A. Riquelme et al; [email protected]EGU General Assembly 2015, Vienna (Austria)
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Semi-automatic characterization of fractured rock massesusing 3D point clouds
discontinuity orientation, spacing and SMR geomechanical classification
2 Case studySources of informationMean planes and spacing analysisSMR results
3 Conclusions
A. Riquelme et al; [email protected] EGU General Assembly 2015, Vienna (Austria)
Applied methodologyCase study
Conclusions
A brief descriptionDiscontinuity sets extractionSpacing analysisSMRTool
Flowchart
Data acquisition
Fieldwork3D LS SfM
DS extractionSpacing analysis
DS extractionSpacing analysis
RMRb RMRb RMRb
SMRSMR SMR
Comparison of results
A. Riquelme et al; [email protected] EGU General Assembly 2015, Vienna (Austria)
Applied methodologyCase study
Conclusions
A brief descriptionDiscontinuity sets extractionSpacing analysisSMRTool
Discontinuity Set Extractor (DSE) software
Figure : Classified 3D laser scanning dataset (A new approach for semi-automatic rock massjoints recognition from 3D PC, Riquelme et al, Computer and Geosciences, 2014)
A. Riquelme et al; [email protected] EGU General Assembly 2015, Vienna (Austria)
Applied methodologyCase study
Conclusions
A brief descriptionDiscontinuity sets extractionSpacing analysisSMRTool
Normal spacing analysis from 3D point clouds
Figure : Normal spacing from 3D PC (Riquelme et al, Engineering Geology, under review)
A. Riquelme et al; [email protected] EGU General Assembly 2015, Vienna (Austria)
Applied methodologyCase study
Conclusions
A brief descriptionDiscontinuity sets extractionSpacing analysisSMRTool
SMRTool: a calculator for computing SMR
Figure : SMRTool software (Riquelme et al 2014, on-line)
A. Riquelme et al; [email protected] EGU General Assembly 2015, Vienna (Austria)
Applied methodologyCase study
Conclusions
Sources of informationMean planes and spacing analysisSMR results
2 Case studySources of informationMean planes and spacing analysisSMR results
3 Conclusions
A. Riquelme et al; [email protected] EGU General Assembly 2015, Vienna (Austria)
Applied methodologyCase study
Conclusions
ConclusionsThe 3D dataset was classified and its DS were extracted. The use of 3D PCallowed to identify more mean orientations.
Normal spacing was calculated automatically using the classified PC. Using 3Ddataset, spacing was minor or closer to those obtained through classicalapproach.
The results comparison of SMR evidenced some deviations, up to 1 class.
A. Riquelme et al; [email protected] EGU General Assembly 2015, Vienna (Austria)
Semi-automatic characterization of fractured rock massesusing 3D point clouds
discontinuity orientation, spacing and SMR geomechanical classification