I'm still at version 12.something, but I can update everything before we proceed too
After that, I'll be glad to send along a script; thanks for the offer to look it
On Jan 13, 2014, at 12:46 PM, Robert Cimrman
On 01/13/2014 05:25 PM, David N. Mashburn
On 01/13/2014 09:03 AM, Robert Cimrman wrote:
On 01/13/2014 03:35 PM, David N. Mashburn
Ok, I've managed to make the functions work, but now I'm having trouble
getting the time stepper work. I am using the direct-style script (so that
it runs stand-alone, without simple.py). This has worked out great so far,
but I cannot find a good way to run the time solver without a ProblemConf.
Is there a recommended way to solve time-dependent problems in the direct
It depends on what level you want to do the time-stepping. Do you want to
write down the time-loop yourself? Or do you just want to setup and call the
standard implicit time-stepper? In the latter case, you would need to create
the time solver, specifically a SimpleTimeSteppingSolver instance (see
sfepy/solvers/ts_solvers.py), similarly to how you created the Newton solver
and then just call it.
I'm perfectly happy either way so long as the solution is updated properly,
since this is not a real time-dependent simulation anyway, but more of a
numerical device for solving the nonlinear equations.
go into a lot more specifics about things that I've tried, so let me
know if you need more information.
It might help, see above :)
I tried creating a SimpleTimeSteppingSolver a number of different ways and kept
bumping into problems because I've not defined a ProblemConf. It fails when I
try to create it using "pb.get_time_solver" and the class SimpleTimeStepper
expects a "conf" argument that I assume to be a ProblemConf. After digging
around the source code and looking at error messages, I created a dummy Struct
to try to see if I could hack around this and get something like
"solve_evolutionary" to run, but after getting it to a certain point with it
still not working, I thought I'd see if there was a better way. Here's a
snippet of the code that doesn't quite work:
ts_conf = Struct(t0=t0, t1=t1, dt=None, n_step=n_step,
tss = SimpleTimeSteppingSolver(ts_conf)
ts = TimeStepper.from_conf(ts_conf)
pb = ProblemDefinition('elasticity', equations=eqs, nls=nls, ls=lin_solver,
pb.time_update(ebcs=Conditions([fix_u_left,fix_u_bottom])) ## This sim is now
failing here, whereas this used to work ##
vec = solve_evolutionary(pb)
What version of sfepy do you use? solve_evolutionary() has been removed a year ago.
Is there a better way to be going about this? As I said above, I'm perfectly
happy to manage my own time loop since if that would be easier, but I do like
the flexibility of running everything via direct execution.
As I do not have a simple example ready (using mostly the problem conf. approach with
time-dependent problems), it would be handy if you send me a working (up to the point it
fails now) script + mesh, so that I could play with it. You can send it off-list, if the
mesh is big...
>> Thanks, -David
>>> On 01/10/2014 07:02 AM, Robert Cimrman wrote: Hello David,
>>>> On 01/10/2014 10:51 AM, David N. Mashburn wrote: Hello again Robert,
>>>> I'm finally coming back around to this project.
>>>> I see that using a time stepper with gradual load increase is the way
>>>> go for a very large deformation solution; is there a recommended way to
>>>> go about this in sfepy? Is there a way to implement an increasing
>>>> variable into the built-in time solver, or is it better to run the
>>>> simulation in a python loop and modify the inputs manually?
>>> Have a look at the perfusion example  - there is a pressure traction
>>> term with pressure depending on time (function get_traction()). Ignore the
>>> variables and terms you do not need - the traction is applied using
>>> dw_tl_surface_traction term. Let me know if this helps.
>>>> I am also not clear on whether the original mesh is suitable for every
>>>> time step or if it will need to be updated.
>>> The total Lagrangian formulation integrates over the undeformed domain,
>>> and it should work up to a pretty large deformation. Be sure the mesh is
>>> fine enough, and that the load increments are such that the nonlinear
>>> solver in each time step converges. When you have your problem description
>>> written down, send me the complete example in case of convergence
>>> Cheers, r.
>>>>> On 02/23/2013 06:13 AM, Robert Cimrman wrote: Hi David,
>>>>>> On 02/22/2013 06:40 PM, David Mashburn wrote: Thanks Robert,
>>>>>> already helps a lot. Glad to know it is a non-trivial question.
>>>>>> We are actually trying to cross-check some analytical solutions,
>>>>>> I would like to get this to work at least to some degree of
>>>>> Do you think that those would be a good tests to add to sfepy test
>>>>>> I've tried swapping out a simple neohookean system with bulk
>>>>>> and all that like in the example. A warp violation seems to be
>>>>>> causing an exception after one iteration with a nominal amount
>>>>>> I've been digging through the nonlinear solver's
>>>>>> can't find a way to shrink the initial step size. The other
>>>>>> work-around I can think of is to use a time stepper to
>>>>>> increase the stress. Is there another/easier way to
>>>>> Yes, this is the way to do it - use time stepping to increase the
>>>>> load gradually. I am not aware of other ways. In nonlinear analysis
>>>>> with the Newton solver, a good initial guess is required.
>>>> Ok, that makes sense now.
>>>>>> Also, is it normal for a system with a fairly large deformation
>>>>>> throw a warp violation and then still recover afterwards (if
>>>>>> then maybe this exception is a bug?)
>>>>> How does it recover? I assume it just throws off the warped
>>>>> and the nonlinear iteration does not converge, right?
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