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Automating HotSpot health physics code for enhanced radiological risk assessment using python.

Najeeb N M Maglas1, Merouane Najar2, Zhao Qiang2

  • 1College of Nuclear Science and Technology, Harbin Engineering University, Harbin, 150001, China; Thamar University, Republic of Yemen, Faculty of Science, Department of Physics, Yemen; National Atomic Energy Commission-Yemen (NATEC), Sana'a, Yemen.

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Summary
This summary is machine-generated.

This study introduces a Python automation framework to enhance the HotSpot Health Physics Code for radiological risk assessment. The automation improves efficiency and accuracy in nuclear emergency scenarios.

Keywords:
Emergency responseGaussian plume modelHotSpot code automationNuclear safetyPython programmingRadiological risk assessment

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Area of Science:

  • Health Physics
  • Computational Science
  • Environmental Science

Background:

  • The HotSpot Health Physics Code is crucial for radiological risk assessment during nuclear incidents.
  • Manual data input and analysis in HotSpot limit efficiency for complex scenarios with parameter variations.

Purpose of the Study:

  • To develop a Python-based automation framework for the HotSpot Health Physics Code.
  • To address limitations in manual data processing and analysis for improved efficiency and accuracy.

Main Methods:

  • Developed a Python framework to automate HotSpot parameter adjustments (radionuclide concentration, weather, terrain).
  • Implemented real-time organized dataset generation.
  • Integrated automated visualization and streamlined data extraction.

Main Results:

  • Achieved dynamic adjustment of key parameters for HotSpot.
  • Enabled real-time data generation and organization.
  • Enhanced precision and reduced analysis time for radiological risk assessment.

Conclusions:

  • Automating HotSpot significantly improves radiological risk assessment capabilities.
  • The framework offers increased accuracy, flexibility, and rapid decision-making for diverse emergency situations.
  • Advances methodologies for nuclear incident and emergency response.