Model and analysis of performance for the method of characteristics direction probabilities with boundary averaging

• The CDP with boundary averaging combines the benefits of the CPM and the MOC.
• A performance model demonstrates the benefits of boundary averaging.
• Numerical results certify the correctness of the performance model.
• Numerical results show the performance improvement of boundary averaged CDP.

The work presents a performance model of the method of characteristic direction probabilities (CDP) which integrates the benefits of the collision probability method (CPM) and the method of characteristics (MOC) for solution of the integral form of the Boltzmann Transport Equation and has been implemented in the Michigan PArallel Characteristic based Transport (MPACT) code for 2-D and 3-D transport calculations. The process of boundary averaging reduced the storage and computation but the capability of dealing with complicated geometries is preserved since the same ray tracing information is used as in MOC. The benefits of CDP are demonstrated by the developed performance model which describes the storage, floating point operations and calculation time. The numerical results are given for different cases to show the accuracy, storage, floating point operations and computing time of the CDP compared to the MOC using the performance model. From the cases examined, the boundary average method shows significant improvement on the storage and computational efficiency for three-dimensional cases with sufficient accuracy.