bluemira.equilibria.optimisation.problem._breakdown
===================================================

.. py:module:: bluemira.equilibria.optimisation.problem._breakdown


Classes
-------

.. autoapisummary::

   bluemira.equilibria.optimisation.problem._breakdown.BreakdownZoneStrategy
   bluemira.equilibria.optimisation.problem._breakdown.CircularZoneStrategy
   bluemira.equilibria.optimisation.problem._breakdown.InboardBreakdownZoneStrategy
   bluemira.equilibria.optimisation.problem._breakdown.OutboardBreakdownZoneStrategy
   bluemira.equilibria.optimisation.problem._breakdown.InputBreakdownZoneStrategy
   bluemira.equilibria.optimisation.problem._breakdown.BreakdownCOP


Module Contents
---------------

.. py:class:: BreakdownZoneStrategy(R_0, A, tk_sol, **kwargs)

   Bases: :py:obj:`abc.ABC`

   .. autoapi-inheritance-diagram:: bluemira.equilibria.optimisation.problem._breakdown.BreakdownZoneStrategy
      :parts: 1
      :private-bases:


   Abstract base class for the definition of a breakdown zone strategy.

   :param R_0: Major radius of the reference plasma
   :param A: Aspect ratio of the reference plasma
   :param tk_sol: Thickness of the scrape-off layer


   .. py:attribute:: R_0


   .. py:attribute:: A


   .. py:attribute:: tk_sol


   .. py:property:: breakdown_point
      :type: tuple[float, float]

      :abstractmethod:


      The location of the breakdown point.

      :returns: * *x_c* -- Radial coordinate of the breakdown point
                * *z_c* -- Vertical coordinate of the breakdown point


   .. py:property:: breakdown_radius
      :type: float

      :abstractmethod:


      The radius of the breakdown zone.


   .. py:method:: calculate_zone_points(n_points: int) -> tuple[numpy.ndarray, numpy.ndarray]
      :abstractmethod:


      Calculate the discretised set of points representing the breakdown zone.



.. py:class:: CircularZoneStrategy(R_0, A, tk_sol, **kwargs)

   Bases: :py:obj:`BreakdownZoneStrategy`

   .. autoapi-inheritance-diagram:: bluemira.equilibria.optimisation.problem._breakdown.CircularZoneStrategy
      :parts: 1
      :private-bases:


   Circular breakdown zone strategy.


   .. py:method:: calculate_zone_points(n_points: int) -> tuple[numpy.ndarray, numpy.ndarray]

      Calculate the discretised set of points representing the breakdown zone.

      :returns: * *x* -- The x coordinates of the zone
                * *z* -- The z coordinates of the zone



.. py:class:: InboardBreakdownZoneStrategy(R_0, A, tk_sol, **kwargs)

   Bases: :py:obj:`CircularZoneStrategy`

   .. autoapi-inheritance-diagram:: bluemira.equilibria.optimisation.problem._breakdown.InboardBreakdownZoneStrategy
      :parts: 1
      :private-bases:


   Inboard breakdown zone strategy.


   .. py:property:: breakdown_point
      :type: tuple[float, float]


      The location of the breakdown point.

      :returns: * *x_c* -- Radial coordinate of the breakdown point
                * *z_c* -- Vertical coordinate of the breakdown point


   .. py:property:: breakdown_radius
      :type: float


      The radius of the breakdown zone.


.. py:class:: OutboardBreakdownZoneStrategy(R_0, A, tk_sol, **kwargs)

   Bases: :py:obj:`CircularZoneStrategy`

   .. autoapi-inheritance-diagram:: bluemira.equilibria.optimisation.problem._breakdown.OutboardBreakdownZoneStrategy
      :parts: 1
      :private-bases:


   Outboard breakdown zone strategy.


   .. py:property:: breakdown_point
      :type: tuple[float, float]


      The location of the breakdown point.

      :returns: * *x_c* -- Radial coordinate of the breakdown point
                * *z_c* -- Vertical coordinate of the breakdown point


   .. py:property:: breakdown_radius
      :type: float


      The radius of the breakdown zone.


.. py:class:: InputBreakdownZoneStrategy(x_c, z_c, r_c)

   Bases: :py:obj:`CircularZoneStrategy`

   .. autoapi-inheritance-diagram:: bluemira.equilibria.optimisation.problem._breakdown.InputBreakdownZoneStrategy
      :parts: 1
      :private-bases:


   User input breakdown zone strategy.


   .. py:attribute:: x_c


   .. py:attribute:: z_c


   .. py:attribute:: r_c


   .. py:property:: breakdown_point
      :type: tuple[float, float]


      The location of the breakdown point.

      :returns: * *x_c* -- Radial coordinate of the breakdown point
                * *z_c* -- Vertical coordinate of the breakdown point


   .. py:property:: breakdown_radius
      :type: float


      The radius of the breakdown zone.


.. py:class:: BreakdownCOP(breakdown: bluemira.equilibria.equilibrium.Breakdown, breakdown_strategy: BreakdownZoneStrategy, B_stray_max: float, B_stray_con_tol: float, n_B_stray_points: int, max_currents: numpy.typing.ArrayLike | None = None, opt_algorithm: bluemira.optimisation.AlgorithmType = Algorithm.SLSQP, opt_conditions: dict[str, float | int] | None = None, constraints: list[bluemira.equilibria.optimisation.constraints.UpdateableConstraint] | None = None)

   Bases: :py:obj:`bluemira.equilibria.optimisation.problem.base.EqCoilsetOptimisationProblem`

   .. autoapi-inheritance-diagram:: bluemira.equilibria.optimisation.problem._breakdown.BreakdownCOP
      :parts: 1
      :private-bases:


   Coilset optimisation problem for the premagnetisation / breakdown phase.


   .. py:attribute:: _args


   .. py:method:: optimise(x0=None, *, fixed_coils: bool = True, keep_history: bool = False, check_constraints: bool = False, verbose: bool = False)

      Solve the optimisation problem.