| dc.contributor.author | Thomas Strauhal | |
| dc.contributor.author | Christian Zangerl | |
| dc.contributor.other | Institute of Applied Geology, University of Natural Resources and Life Sciences Vienna, 1190 Vienna, Austria | |
| dc.contributor.other | Institute of Applied Geology, University of Natural Resources and Life Sciences Vienna, 1190 Vienna, Austria | |
| dc.date.accessioned | 2021-04-28T00:05:56Z | |
| dc.date.available | 2025-10-02T03:44:04Z | |
| dc.date.issued | 01-04-2021 | |
| dc.identifier.issn | - | |
| dc.identifier.uri | https://www.mdpi.com/2076-3417/11/9/3973 | |
| dc.description.abstract | 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. | |
| dc.format | - | |
| dc.language.iso | EN | |
| dc.publisher | MDPI AG | |
| dc.relation.uri | ['https://journals.oslomet.no/index.php/yrke/about/submissions', 'https://journals.oslomet.no/index.php/yrke/about', 'https://journals.hioa.no/index.php/yrke'] | |
| dc.rights | CC BY | |
| dc.subject | ['vocational', 'teacher', 'education', 'Special aspects of education', 'LC8-6691'] | |
| dc.subject.lcc | Technology | |
| dc.title | The Impact of Fracture Persistence and Intact Rock Bridge Failure on the In Situ Block Area Distribution | |
| dc.type | Article | |
| dc.description.keywords | rockfall | |
| dc.description.keywords | rock mass characterization | |
| dc.description.keywords | in situ block area distribution | |
| dc.description.keywords | discrete fracture network | |
| dc.description.pages | - | |
| dc.description.doi | 10.3390/app11093973 | |
| dc.title.journal | Applied Sciences | |
| dc.identifier.e-issn | 2076-3417 | |
| dc.identifier.oai | oai:doaj.org/journal:e884478f62824c8ea74474a44aded17f | |
| dc.journal.info | Volume 11, Issue 9 | |
