New question #248315 on Yade:
https://answers.launchpad.net/yade/+question/248315
Dear Prof. Chareyre and all users:
Thanks for helping me to understand the PSD task in Yade and I now have
finished to write my own python codes for generating spheres with a given PSD
in Yade with inserting some simple statistical algorithms for PSD analysis.
After this work, I should have to test these procedures with the combination of
3D tri-axial compression codes in a whole simulation. So my questions today are
closely related to ‘radius expansion method’ in Yade for sample preparing,
which I am the first time to use.
As I know, in almost all DEM softwares(include Yade), the collision detection
algorithm and no contacts generation requirement always make it hardly possible
for directly generated sample to meet a appropriate porosity compared to that
just in lab. So it necessary for us to just do a ‘secondary treatment’ in order
to obtaining a correct one. I always called this process before as
‘consolidation’. Of course, in this process, the porosity of the sample is
always determined mainly just by two things, one is the material properties of
particles and the other is confinment pressure. And it is obviously that if one
of the above two is a constant, the final porosity of the sample in the state
of consolidation finished may vary monotonically with the changed another. So,
when we treat the material properties as a constant, Yade provides a common way
for the process of consolidation as I just employed in my provious tasks, which
can be shown as follow:
###########################################################################
Consolidation =TriaxialStressController(
wall_bottom_id=wallids[2],wall_top_id=wallids[3],
wall_left_id=wallids[0],wall_right_id=wallids[1],
wall_back_id=wallids[4],wall_front_id=wallids[5],
wall_front_activated = False,wall_back_activated = False,
internalCompaction=False,
stressMask = 7, # stressMask = 0
goal1=100000, # goal1 = goal2 = goal3 = strain rate
goal2=100000,
goal3=100000,
)
###########################################################################
But there are just two problems in using the method, which can be described as:
(1). With a determined material properties, the desired porosity is uniquely
related to a constant but unknown confinement pressure , So it can hardly to
predict this appropriate one at the beginning of consolidation even if the
strain-rate controlling style is used.
(2). In the consolidation process, the ‘aabb’ walls is moving toward and the
size of simulation sample is reducing step by step, this situation may make us
difficult to describe the final volume of the sample and compare it to that in
the lab.
For these two problems, Yade also provides a another way for consolidation
process, this way here can be called ‘radius expansion method’. You have
defined it in your provious paper ‘Micromechanics of granular materials with
capillary effects (2009)’.
‘All particles are randomly positioned inside a cube made of six frictionless
rigid walls such that no overlap/contact force develops between any two
particles. The interparticle friction angle is set to a small value (the
smaller the friction angle is, the denser the assembly is. A value of 0.5
degree has been chosen here) and particle radii are then homogeneously
increased, whereas the boundary walls remain fixed. The process continues until
the confining pressure (5kPa in this study) is reached and static equilibrium
between the internal stress state and the external load is satisfied. The
interparticle friction coefficient is then changed to a value classically used
in DEM simulation to reproduce an acceptable shear strength (30 degree) and the
boundary walls are controlled in displacement to keep the equilibrium state.’
My today’s question are that:
(1). I have try these codes in Yade:
###########################################################################
consolidation = TriaxialStressController(
wall_left_id=wallids[0],wall_right_id=wallids[1],
wall_bottom_id=wallids[2],wall_top_id=wallids[3],
wall_back_id=wallids[4],wall_front_id=wallids[5],
maxMultiplier = 1.005, # spheres growing factor (fast growth)
finalMaxMultiplier = 1.0005, # spheres growing factor (slow growth)
thickness=.0001,
internalCompaction=True, # 'False' here may close the task
stressMask=7,
goal1 = confine_pressure, # confine-pressure applied in x-derection.
goal2 = confine_pressure, # confine-pressure applied in y-derection.
goal3 = confine_pressure, # confine-pressure applied in z-derection.
)
###########################################################################
These codes can run sucessfully in Yade but I now can not fully understand how
these two parameters ‘maxMultiplier’ and ‘finalMaxMultiplier’ works but only
know that they can help to control the spheres growth speed. Please tell how.
(2). In the process of radius expansion, all the radius of particles are
homogeneously increasing and the normal stiffness of each one may be larger
step by step. I think this situation may only exsit just in DEM software since
the igorance of natural attributes of materials make it just as a pure
mathematical method in DEM analysis. For natural cohesionless soils, the normal
stiffness of spheres may be a constant in the consolidation process or decrease
progressively because of particle crashing appearing. My this view may not very
right because I do not know whether there exsit some other restricted
conditions in this method to ensure that the material attributes of spheres in
expansion process are approximately be the natural attributes or not. Please
tell me that.
(3) How to get a dense sample in Yade using radius expansion, I test a
simulation with the parameters in your article.
1. 10000 particles
2. initial volume of sample is 1.0 mm * 1.0 mm * 1.0 mm.
3. E = 50Mpa and possion ratio is 0.5
4. some different simulations were carried out with a changed range of friction
angle from 0.5 degree to 30 degree.
The simulation results show that the porosity may increase with a increased
friction angle, but all the tasks can only give me different loose samples with
the range from 48.7% to 53.5%. Please tell me if there are some other ways to
obtain a dense sample.
Seeking your help!
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