Determination of the In situ Block Size Distribution in Fractured Rock, an Approach for Comparing In-situ Rock with Rock Sieve Analysis

2004 ◽  
Vol 37 (5) ◽  
pp. 391-401 ◽  
Author(s):  
M. Jern
Keyword(s):  
Size Distribution ◽  
Fractured Rock ◽  
Block Size ◽  
Sieve Analysis ◽  
Block Size Distribution

scholarly journals The Impact of Fracture Persistence and Intact Rock Bridge Failure on the In Situ Block Area Distribution

2021 ◽  
Vol 11 (9) ◽  
pp. 3973
Author(s):  
Thomas Strauhal ◽  
Christian Zangerl
Keyword(s):  
Rock Mass ◽  
Size Distribution ◽  
Block Size ◽  
Intact Rock ◽  
Rock Bridge ◽  
Block Area ◽  
The Mean ◽  
Bridge Failure ◽  
Block Size Distribution

The in situ block size distribution is an essential characteristic of fractured rock masses and impacts the assessment of rockfall hazards and other fields of rock mechanics. The block size distribution can be estimated rather easily for fully persistent fractures, but it is a challenge to determine this parameter when non-persistent fractures in a rock mass should be considered. In many approaches, the block size distribution is estimated by assuming that the fractures are fully persistent, resulting in an underestimation of the block sizes for many fracture geometries. In addition, the block size distribution is influenced by intact rock bridge failure, especially in rock masses with non-persistent fractures, either in a short-term perspective during a slope failure event when the rock mass increasingly disintegrates or in a long-term view when the rock mass progressively weakens. The quantification of intact rock bridge failure in a rock mass is highly complex, comprising fracture coalescence and crack growth driven by time-dependent changes of the in situ stresses due to thermal, freezing-thawing, and pore water pressure fluctuations. This contribution presents stochastic analyses of the two-dimensional in situ block area distribution and the mean block area of non-persistent fracture networks. The applied 2D discrete fracture network approach takes into account the potential failure of intact rock bridges based on a pre-defined threshold length and relies on input parameters that can be easily measured in the field by classical discontinuity mapping methods (e.g., scanline mapping). In addition, on the basis of these discrete fracture network analyses, an empirical relationship was determined between (i) the mean block area for persistent fractures, (ii) the mean block area for non-persistent fractures, and (iii) the mean interconnectivity factor. The further adaptation of this 2D approach to 3D block geometries is discussed on the basis of general considerations. The calculations carried out in this contribution highlight the large impact of non-persistent fractures and intact rock bridge failure for rock mass characterization, e.g., rockfall assessment.

A Method to Estimate In Situ Block Size Distribution

2011 ◽  
Vol 45 (3) ◽  
pp. 401-407 ◽  
Author(s):  
M. K. Elmouttie ◽  
G. V. Poropat
Keyword(s):  
Size Distribution ◽  
Block Size ◽  
Block Size Distribution

scholarly journals In Situ Determination of Thermal Resistivity of Soil: Case Study of Olorunsogo Power Plant, Southwestern Nigeria

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Michael Adeyinka Oladunjoye ◽  
Oluseun Adetola Sanuade
Keyword(s):  
Grain Size ◽  
Power Plant ◽  
Moisture Content ◽  
Size Distribution ◽  
Thermal Resistivity ◽  
Dry Density ◽  
Physical Parameters ◽  
Southwestern Nigeria

This study measured in situ the thermal resistivity of soils at Olorunsogo Gas Turbine Power Station (335 MW Phase 1) which is located in Ogun State, Southwestern Nigeria. Ten pits, each of about 1.5 m below the ground surface, were established in and around the power plant in order to measure the thermal resistivity of soils in situ. A KD 2-Pro was used for the in situ measurement of thermal properties. Samples were also collected from the ten pits for laboratory determination of the physical parameters that influence thermal resistivity. The samples were subjected to grain size distribution analysis, compaction, specific gravity and porosity tests, moisture content determination, and XRD analysis. Also, thermal resistivity values were calculated by an algorithm using grain size distribution, dry density, and moisture content for comparison with the in situ values. The results show that thermal resistivity values range from 34.07 to 71.88°C-cm/W with an average of 56.43°C-cm/W which falls below the permissible value of 90°C-cm/W for geomaterials. Also, the physical parameters such as moisture content, porosity, degree of saturation, and dry density vary from 13.00 to 16.20%, 39.74 to 45.64%, 40.72 to 63.52%, and 1725.05 to 1930.00 Kg/m3, respectively. The temperature ranges from 28.92 to 35.39°C with an average of 32.11°C in the study area. The calculated thermal resistivity from an algorithm was found to vary from 48.43 to 81.22°C-cm/W with an average of 65.56°C-cm/W which is close to the thermal resistivity values measured in situ. Good correlation exists between the in situ thermal resistivity and calculated thermal resistivity with suggesting that both methods are reliable.

Sign in / Sign up

Export Citation Format

Share Document