English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

. This paper presents analytical solutions to estimate atany scale the fracture density variability associated to stochastic DiscreteFracture Networks. These analytical solutions are based upon the assumptionthat each fracture in the network is an independent event. Analyticalsolutions are developed for any kind of fracture density indicators. Thoseanalytical solutions are verified by numerical computing of the fracturedensity variability in three-dimensional stochastic Discrete FractureNetwork (DFN) models following various orientation and size distributions,including the heavy-tailed power-law fracture size distribution. We showthat this variability is dependent on the fracture size distribution and themeasurement scale, but not on the orientation distribution. We also showthat for networks following power-law size distribution, the scaling of thethree-dimensional fracture density variability clearly depends on thepower-law exponent.

On the Density Variability of Poissonian Discrete Fracture Networks, with application to power-law fracture size distributions