| | 3 | == General considerations |
| | 4 | The time dependent tracking of the neutron population in a multiplying, near critical medium is very challenging in terms of Monte Carlo convergence. A naive analog game in most cases would statistically diverge, moreover it will give an underestimate of the power as the very low chance contributions of a high number of fission in certain chains see Fig. 7. Therefore the calculation is performed always keeping a single particle as a sample of the neutron population gaining or loosing weight at interactions. The neutron weight distribution must be kept around the mean for ensuring statistical convergence. |
| | 5 | The neutrons are followed from time interval to time interval and the population at the interval ends using splitting and Russian roulette while keeping the total population number constant. |
| | 6 | Having single, non-branching calculations also supports the architecture of the GPU where threads can be set to single neutron chains. |
| | 7 | |
| | 8 | [[Image(TDMCC_varP_analog_vs_nonanalog.png, 70%)]] |
| | 9 | |
| | 10 | ''' Fig. 7. Analog and non-analog simulation results for time dependent power evolution for a multiplying medium. Analog simulation produces an underestimate of the power ''' |
| | 11 | |
| | 12 | Biased sampling schemes are applied at fission yield, delayed neutron, interaction type sampling with ongoing development regarding path length sampling and angular biasing. |
| | 13 | |
| | 14 | == Optimization of the GPU workflow |
| | 15 | |
| | 16 | The key idea of GUARDYAN is a massively parallel execution structure making use of advanced programming possibilities available on CUDA enabled GPUs. In order to maximize performance however, the architecture calls for some major deviations from a traditional MC code. |
| | 17 | |
| | 18 | [[Image(NRDI.jpg, 80%)]] |
