:class:`DynaISPH` ================= .. py:class:: ansys.dyna.core.pre.dynaisph.DynaISPH Bases: :py:obj:`ansys.dyna.core.pre.dynabase.DynaBase` Contains methods for creating a keyword related to ISPH. .. !! processed by numpydoc !! .. py:currentmodule:: DynaISPH Overview -------- .. tab-set:: .. tab-item:: Methods .. list-table:: :header-rows: 0 :widths: auto * - :py:attr:`~set_des` - Provide controls related to ISPH. * - :py:attr:`~save_file` - Save keyword files. .. tab-item:: Attributes .. list-table:: :header-rows: 0 :widths: auto * - :py:attr:`~isphanalysis` - Import detail ------------- .. code-block:: python from ansys.dyna.core.pre.dynaisph import DynaISPH Attribute detail ---------------- .. py:attribute:: isphanalysis Method detail ------------- .. py:method:: set_des(num_timestep=1, boxid=0, space_dimension=3, neighbors=150, approximation_theory=0, max_velocty=1000000000000000.0) Provide controls related to ISPH. :Parameters: **num_timestep** : :class:`python:int`, :obj:`optional` Number of time steps between particle sorting. The default is ``1``. **boxid** : :class:`python:int`, :obj:`optional` Box ID. The default is ``0``. ISPH approximations are computed inside the specified box. When a particle has gone outside this box, it is deactivated. **space_dimension** : :class:`python:int`, :obj:`optional` Space dimension for ISPH particles. The default is ``3``. Options are: - EQ.3: 3D problems - EQ.2: 2D plane strain problems - EQ.-2: 2D axisymmetric problems **neighbors** : :class:`python:int`, :obj:`optional` Initial number of neighbors per particle. The default is ``150``. **approximation_theory** : :class:`python:int`, :obj:`optional` Particle approximation theory. The default is ``0``. **max_velocty** : :class:`python:float`, :obj:`optional` Maximum value for velocity for the ISPH particles. The default is ``1000000000000000.0``. :Returns: :ref:`bool ` ``True`` when successful, ``False`` when failed. .. !! processed by numpydoc !! .. py:method:: save_file() Save keyword files. :Returns: :ref:`bool ` ``True`` when successful, ``False`` when failed. .. !! processed by numpydoc !!