Point Detector Tally

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Description

This repository contains the development and benchmarking of a relativistic point detector within the OpenMC framework. The detector efficiently estimates neutron flux at a point using full relativistic kinematic calculations, making it ideal for high-energy particle simulations. This first implementation of a point detector tally in OpenMC is validated through single and multiple collision experiments, showing excellent agreement with conventional methods. This enhancement significantly improves OpenMC's capabilities for complex shielding analyses and other scenarios where traditional Monte Carlo methods may be inefficient.

Use Example

To configure a point tally in OpenMC, follow the standard procedure for creating a tally but specify the estimator as "point" and provide the coordinates for positioning and the exclusion sphere radius $R_0$ using a list of x, y, z, $R_0$ values. The following code snippet demonstrates how to set up a point detector located at coordinates (0, 0, 1) with an exclusion sphere radius of 0.01 cm, along with an energy filter, using the OpenMC Python API:

point_detector = openmc.Tally(name="pDet")
point_detector.scores = ["flux"]  
point_detector.filters = [energy_filter]  
point_detector.estimator = 'point'  
point_detector.positions = [0, 0, 1 , 0.01]  

Checklist

• I have performed a self-review of my own code
• I have run clang-format (version 15) on any C++ source files (if applicable)
• I have followed the style guidelines for Python source files (if applicable)
• I have made corresponding changes to the documentation (if applicable)
• I have added tests that prove my fix is effective or that my feature works (if applicable)