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Published November 10, 2023 | Version v1
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Effect of the loading condition on the statistics of crackling noise accompanying the failure of porous rocks

Authors/Creators

  • 1. University of Debrecen
  • 2. University of Edinburgh

Description

We test the hypothesis that loading conditions affect the statistical features of crackling noise accompanying the failure of porous rocks by performing discrete element simulations of the tensile failure of numerical rock samples and comparing the results to those of compressive simulations of the same specimens. Cylindrical samples are constructed by sedimenting randomly sized spherical particles connected by beam elements representing the cementation of granules. Under a slowly increasing tensile load, the cohesive contacts between particles break in bursts whose size fluctuates over a broad range. Close to failure breaking avalanches are found to localize on a highly stressed region where the catastrophic avalanche starts and the specimen falls apart into two pieces along a spanning crack. The fracture plane has a random position and orientation falling most likely close to the center of the specimen perpendicular to the load direction. In spite of the strongly different strengths and spatial structure of damage of tensile and compressive failure of numerical rocks, our calculations revealed that the size, energy, and duration of crackling avalanches, and the waiting time between consecutive events all obey scale free statistics with power law exponents which agree within the error bars in the two loading cases.

Other

Data analysis and graphical representation of the numerical results were carried out using two freely available open source program packages:

  • the GLE (Graphics Layout Engine) program package was used to carry data the data analysis and the graphical representation of the numerical results. GLE is available under the link: https://glx.sourceforge.io/index.html
  • To generate snapshots of the simulations, the povray package was used which is available under the link: http://www.povray.org/

The data is organized in folders according to the figures of the manuscript. In each folder all the data files of the figure are stored together with the GLE script files (with .gle extension) and with the .c code which was used to generate the data files from the raw data of simulations. The open a figure the .gle script file has to be opened either using the GUI called qgle of GLE or from the command line using the command "gle -d eps filename.gle". The later generates a .eps file of the figure.

If a figure presents snapshot(s) of the simulation, the povray file (with .pov extension) is also available in the folder. To render the image the following command has to be executed

povray +w640 +h480 +x -D -v -ifilename.pov

which renders the file called filename.pov.

For the case of need, the content of the coloumns of data files is explained in a separate file called repositorium_read_me.doc

Funding provided by: National Research, Development and Innovation Office
Crossref Funder Registry ID: https://ror.org/03g2am276
Award Number: ÚNKP-22-3

Funding provided by: National Research, Development and Innovation Office
Crossref Funder Registry ID: https://ror.org/03g2am276
Award Number: EFOP-3.6.1-16-2016-0002

Funding provided by: National Research, Development and Innovation Office
Crossref Funder Registry ID: https://ror.org/03g2am276
Award Number: K 119967

Funding provided by: National Research, Development and Innovation Office
Crossref Funder Registry ID: https://ror.org/03g2am276
Award Number: TKP2021-NKTA-34

Methods

The primary data files were obtained from our simulation program which generates the breaking process of numerical porous rock samples under slowly increasing elongation. The raw data obtained from discrete element simulations are further processed by a data evaluation program which identifies crackling avalanches, determines their characteristic quantities along with the probability distributions of the quantities of interest.  To further analyse the data we used two main freely available open source program packages:

  • the GLE Graphics program package was used to carry out the data analysis and the graphical representation of the numerical results. GLE is available under the link: https://glx.sourceforge.io/index.html
  • To generate snapshots of the simulations, the povray package was used which is available under the link: http://www.povray.org/

Files

README.md

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