JCFpm Weibull heterogeneity

Asked by Luis Barbosa on 2020-10-15

Dear all,

I am using the function:

Ip2_JCFpmMat_JCFpmMat_JCFpmPhys(
        xSectionWeibullScaleParameter=xSectionScale,
        xSectionWeibullShapeParameter=xSectionShape,

To insert a certain Fn,max heterogeneity in my aggregate pack. However, when I check the Fn,max distribution (pos pack creation) with the imputed values of Weibull shape and scale, it does not match.

For instance, using xSectionScale of 1 and shape of 5 as imput, I obtained a Fn,max distribution with a shape factor of 2,46 and a scale factor of 1,82.

For this I have used the linear distribution of Weibull and regression to calculate the parameters.

Does it make sense to you or it is not the expected result?

Thanks
Luis

Question information

Language:
English Edit question
Status:
Solved
For:
Yade Edit question
Assignee:
No assignee Edit question
Solved by:
Robert Caulk
Solved:
2020-10-21
Last query:
2020-10-21
Last reply:
2020-10-15
Best Robert Caulk (rcaulk) said : #1

Hello,

>Does it make sense to you or it is not the expected result?

xSectionWeibullShapeParameter is the distribution of alpha where:

FnMax = pi * (alpha * min(r1,r2))²

So statistically speaking, the distribution of FnMax depends on the distribution of particles multiplied by the weibull distribution, squared. Clearly further complicated by the "minimum" function.

If you want the distribution of FnMax to be exactly that of your assigned weibull distribution, you are better off iterating on the bonds individually in python and setting the FnMax accordingly.

for i in O.interactions:
  alpha = weibullDeviate()
  i.phys.FnMax = alpha

Relevant thread [1].

Cheers.

Robert

[1] https://answers.launchpad.net/yade/+question/693275

Luis Barbosa (luis-pires-b) said : #2

Thanks Robert Caulk, that solved my question.