.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/gallery/plot_pulsed_breakdown_example.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_gallery_plot_pulsed_breakdown_example.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_gallery_plot_pulsed_breakdown_example.py:


Pulsed Breakdown Model
=======================

This example demonstrates the RepetitivePulseBreakdownModel which calculates breakdown voltage
with memory effects from repetitive pulsing.

.. GENERATED FROM PYTHON SOURCE LINES 8-80



.. image-sg:: /auto_examples/gallery/images/sphx_glr_plot_pulsed_breakdown_example_001.png
   :alt: Breakdown Voltage vs Number of Pulses (Memory Effect)
   :srcset: /auto_examples/gallery/images/sphx_glr_plot_pulsed_breakdown_example_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    ============================================================
    Pulsed Breakdown Model - Memory Effects
    ============================================================
    N =   1 pulses: V_breakdown = 1388 V
    N =  10 pulses: V_breakdown = 1388 V
    N = 100 pulses: V_breakdown = 1388 V
    ============================================================
    Note: Breakdown voltage decreases with more pulses
          (memory effect from repetitive pulsing)
    ============================================================

    Generating plot: Breakdown Voltage vs Number of Pulses...






|

.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np
    import openmdao.api as om

    from paroto.models.breakdown_voltage import RepetitivePulseBreakdownModel

    # Create OpenMDAO problem
    prob = om.Problem()
    prob.model.add_subsystem(
        "breakdown",
        RepetitivePulseBreakdownModel(
            model_parameters={
                "A_paschen": 24.4,
                "B_paschen": 6.73,
                "field_enhancement_factor": 1.0,
                "ionization_time": 1e-7,
                "pulse_amplitude_factor": 4.0,
                "decay_constant": 1.0,
            }
        ),
    )
    prob.setup()

    # Set common parameters
    prob.set_val("breakdown.gas_properties_pressure", 101325.0)  # 1 atm
    prob.set_val("breakdown.preheat_temperature", 300.0)  # K
    prob.set_val("breakdown.gap_distance", 0.01)  # 10 mm
    prob.set_val("breakdown.pulse_frequency", 50e3)  # 50 kHz
    prob.set_val("breakdown.pulse_duration", 1e-6)  # 1 μs

    print("=" * 60)
    print("Pulsed Breakdown Model - Memory Effects")
    print("=" * 60)

    # Test for different number of pulses
    n_pulses_list = [1, 10, 100]

    for n_pulses in n_pulses_list:
        # Residence time determines number of pulses
        t_res = n_pulses / 50e3  # seconds

        prob.set_val("breakdown.residence_time", t_res)
        prob.run_model()

        V_bd = prob.get_val("breakdown.breakdown_voltage")[0]
        print(f"N = {n_pulses:3d} pulses: V_breakdown = {V_bd:.0f} V")

    print("=" * 60)
    print("Note: Breakdown voltage decreases with more pulses")
    print("      (memory effect from repetitive pulsing)")
    print("=" * 60)

    # Plot breakdown voltage vs number of pulses
    print("\nGenerating plot: Breakdown Voltage vs Number of Pulses...")
    n_pulses_range = np.logspace(0, 3, 50)  # 1 to 1000 pulses
    V_bd_values = []

    for n_pulses in n_pulses_range:
        t_res = n_pulses / 50e3  # seconds
        prob.set_val("breakdown.residence_time", t_res)
        prob.run_model()
        V_bd_values.append(prob.get_val("breakdown.breakdown_voltage")[0])

    plt.figure(figsize=(8, 5))
    plt.semilogx(n_pulses_range, V_bd_values, "b-", linewidth=2)
    plt.xlabel("Number of Pulses")
    plt.ylabel("Breakdown Voltage (V)")
    plt.title("Breakdown Voltage vs Number of Pulses (Memory Effect)")
    plt.grid(True, alpha=0.3, which="both")
    plt.tight_layout()
    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.224 seconds)


.. _sphx_glr_download_auto_examples_gallery_plot_pulsed_breakdown_example.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_pulsed_breakdown_example.ipynb <plot_pulsed_breakdown_example.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_pulsed_breakdown_example.py <plot_pulsed_breakdown_example.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_pulsed_breakdown_example.zip <plot_pulsed_breakdown_example.zip>`