Hi,
The following code is used in example linear_elasticity/material_nonlinearity.py to evaluate the Cauchy strain during post processing:
strain = problem.evaluate('ev_cauchy_strain.i.Omega(u)', mode='el_avg') out['cauchy_strain'] = Struct(name='output_data', mode='cell', data=strain, dofs=None)
Using ParaView to visualize the result on a tetrahedral mesh from VTK output, I find the strain to have 8 decomposition components with arbitrary names 1 through 8. Is it possible to obtain the strain as a vector in Cartesian components?
Regards, Radko
Hi Radko,
On 12/26/2016 02:50 PM, Radko Bankras wrote:
Hi,
The following code is used in example linear_elasticity/material_nonlinearity.py to evaluate the Cauchy strain during post processing:
strain = problem.evaluate('ev_cauchy_strain.i.Omega(u)', mode='el_avg') out['cauchy_strain'] = Struct(name='output_data', mode='cell', data=strain, dofs=None)
Using ParaView to visualize the result on a tetrahedral mesh from VTK output, I find the strain to have 8 decomposition components with arbitrary names 1 through 8. Is it possible to obtain the strain as a vector in Cartesian components?
what do you mean by "as a vector"? The strain is a tensor (let's say e) with 9 components in 3D. The components you see in paraview are e_11, e_12, e_13, e_21, e_22, e_23, e_31, e_32, e_33, starting from 0.
r.
Regards, Radko
Hi Robert,
On Wednesday, December 28, 2016 at 2:05:22 PM UTC+1, Robert Cimrman wrote: >
Hi Radko,
On 12/26/2016 02:50 PM, Radko Bankras wrote:
Hi,
The following code is used in example linear_elasticity/material_nonlinearity.py to evaluate the Cauchy strain during post processing:
strain = problem.evaluate('ev_cauchy_strain.i.Omega(u)', mode='el_avg') out['cauchy_strain'] = Struct(name='output_data', mode='cell', data=strain, dofs=None)
Using ParaView to visualize the result on a tetrahedral mesh from VTK output, I find the strain to have 8 decomposition components with arbitrary names 1 through 8. Is it possible to obtain the strain as a vector in Cartesian components?
what do you mean by "as a vector"? The strain is a tensor (let's say e) with 9 components in 3D. The components you see in paraview are e_11, e_12, e_13, e_21, e_22, e_23, e_31, e_32, e_33, starting from 0.
Ah ... that makes sense. I guess my confusion started by trying to grasp everything in sfepy at once and then looked at how ParaView visualizes tensor components on mesh cell surfaces. I have now added some line probes to my script, based on examples/linear_elasticity/linear_elastic_probes.py. That helps. I should play more with this and look for that Dummies book though.
Regards, Radko
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Radko Bankras -
Robert Cimrman