The Rocscience International Conference 2021 Proceedings are now available. Read Now
 

Search Results

Correlation Coefficient

If you are performing a Probabilistic analysis with RocPlane and you are using the Mohr-Coulomb strength criterion for the Failure Plane, you can define a Correlation Coefficient between cohesion and friction angle in the Strength tab of the Probabilistic Input Data dialog.

It is known that Cohesion and Friction Angle are related in a general way such that materials with low friction angles tend to have high cohesion and materials with low cohesion tend to have high friction angles. This option allows the user to define the correlation between these two variables.

The Correlation Coefficient option is enabled only under the following conditions:

  1. Strength Model = Mohr-Coulomb.
  2. Random Variables = Parameters.
  3. BOTH Cohesion and Friction Angle are defined as random variables (i.e., assigned a Statistical Distribution).
  4. Statistical Distribution = Normal/Uniform/Lognormal/Exponential/Gamma (will not work for other distribution types).

NOTE: When the check box is NOT selected (the default), Cohesion and Friction Angle are treated as completely independent variables.

By default, when the check box is NOT selected, Cohesion and Friction Angle are treated as completely independent variables.

To see the effect of the Correlation Coefficient:

  1. Create a file with probabilistic input data.
  2. Use Normal or Uniform distributions for Cohesion and Friction Angle.
  3. Select the Correlation coefficient between cohesion and friction angle check box Strength tab of the Probabilistic Input Data dialog.
  4. Enter a correlation coefficient. (Initially, use the default value of –0.5.)
  5. Run the probabilistic analysis.
  6. Create a Scatter Plot of Cohesion vs. Friction Angle.
  7. Note the correlation coefficient listed at the bottom of the Scatter Plot. It should be approximately equal to the value entered in the Input Data dialog. (It will not in general be exactly equal to the user-defined correlation coefficient since the results are still based on random sampling of the input data distributions).
  8. Note the appearance of the plots (i.e., the degree of scatter between the two variables).
  9. Repeat steps 4 to 8, using correlation coefficients of -0.6 to -1.0, in 0.1 increments. Observe the effect on the Scatter Plot. Notice that, when the correlation coefficient is equal to –1, the Scatter Plot results in a straight line.
Account Icon - click here to log in or out of your account Shopping Cart icon Click here to search our site Click here to close Learning Tech Support Documentation Info Chevron Delete Back to Top View More" PDF File Calendar Location Language Fees Video Click here to visit Rocscience's LinkedIn page Click here to visit Rocscience's YouTube page Click here to visit Rocscience's Twitter page Click here to visit Rocscience's Facebook page Click here to visit Rocscience's Instagram page Bookmark Network Scroll down for more Checkmark Download Print Back to top Single User Multiple Users CPillar Dips EX3 RocFall RocPlane RocSupport RocTopple RS2 RS3 RSData RSPile Settle3 Slide2 Slide3 SWedge UnWedge Commercial License Education License Trial License Shop safe & secure Money-back guarantee