ansys.dyna.core.pre.dynabase.ImplicitAnalysis
=============================================

.. py:class:: ansys.dyna.core.pre.dynabase.ImplicitAnalysis(analysis_type=AnalysisType.IMPLICIT, initial_timestep_size=0)

   
   Activates implicit analysis and defines associated control parameters.
















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   .. py:attribute:: defined
      :value: False



   .. py:attribute:: defined_auto
      :value: False



   .. py:attribute:: defined_dynamic
      :value: False



   .. py:attribute:: defined_eigenvalue
      :value: False



   .. py:attribute:: defined_solution
      :value: False



   .. py:attribute:: defined_mass_matrix
      :value: False



   .. py:attribute:: imflag
      :value: 1



   .. py:attribute:: dt0
      :value: 0



   .. py:attribute:: stub


   .. py:method:: set_initial_timestep_size(size=0)

      
      Define the initial time step size.
















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   .. py:method:: set_timestep(control_flag=TimestepCtrol.CONSTANT_TIMESTEP_SIZE, Optimum_equilibrium_iteration_count=11)

      
      Define parameters for automatic time step control during implicit analysis.


      :Parameters:

          **control_flag** : :class:`python:int`
              Automatic time step control flag.

          **Optimum_equilibrium_iteration_count** : :class:`python:int`, :obj:`optional`
              Optimum equilibrium iteration count per time step. The default is ``11``.



      :Returns:

          :ref:`bool <python:bltin-boolean-values>`
              ``True`` when successful, ``False`` when failed.











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   .. py:method:: set_dynamic(integration_method=Integration.NEWMARK_TIME_INTEGRATION, gamma=0.5, beta=0.25)

      
      Activate implicit dynamic analysis and define time integration constants.


      :Parameters:

          **integration_method** : :obj:`enum`
              Implicit analysis type.

          **gamma** : :class:`python:float`, :obj:`optional`
              Newmark time integration constant. The default is ``0.5``.

          **beta** : :class:`python:float`, :obj:`optional`
              Newmark time integration constant. The default is ``0.25``.



      :Returns:

          :ref:`bool <python:bltin-boolean-values>`
              ``True`` when successful, ``False`` when failed.











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   .. py:method:: set_eigenvalue(number_eigenvalues=0, shift_scale=0)

      
      Activate implicit eigenvalue analysis and define associated input parameters.


      :Parameters:

          **number_eigenvalues** : :class:`python:int`, :obj:`optional`
              Number of eigenvalues to extract. The default is ``0``.

          **shift_scale** : :class:`python:float`, :obj:`optional`
              Shift scale. The default is ``0``.



      :Returns:

          :ref:`bool <python:bltin-boolean-values>`
              ``True`` when successful, ``False`` when failed.











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   .. py:method:: set_solution(solution_method=12, iteration_limit=11, stiffness_reformation_limit=55, absolute_convergence_tolerance=1e-10)

      
      Specify whether a linear or nonlinear solution is desired.


      :Parameters:

          **solution_method** : :class:`python:int`, :obj:`optional`
              Solution method for implicit analysis. The default is ``12``.

          **iteration_limit** : :class:`python:int`, :obj:`optional`
              Iteration limit between automatic stiffness reformations.
              The default is ``11``.

          **stiffness_reformation_limit** : :class:`python:int`, :obj:`optional`
              Stiffness reformation limit per time step. The default is
              ``55``.

          **absolute_convergence_tolerance** : :class:`python:float`, :obj:`optional`
              Absolute convergence tolerance. The default is ``1e-10``.



      :Returns:

          :ref:`bool <python:bltin-boolean-values>`
              ``True`` when successful, ``False`` when failed.











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   .. py:method:: set_consistent_mass_matrix()

      
      Use the consistent mass matrix in implicit dynamics and eigenvalue solutions.
















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   .. py:method:: create()

      
      Create an implicit analysis.
















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