### Abstract

Original language | English |
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Title of host publication | Proceedings |

Subtitle of host publication | International Conference on Mathematics and Computational Methods Applied to Nuclear Science & Engineering, M&C 2013 |

Pages | 950-961 |

Publication status | Published - 2013 |

MoE publication type | Not Eligible |

Event | International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M&C 2013 - Sun Valley, ID, United States Duration: 5 May 2013 → 9 May 2013 |

### Publication series

Name | |
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Publisher | Idaho National Laboratory |

Volume | 2 |

### Conference

Conference | International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M&C 2013 |
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Abbreviated title | M&C 2013 |

Country | United States |

City | Sun Valley, ID |

Period | 5/05/13 → 9/05/13 |

### Fingerprint

### Keywords

- doppler
- Monte Carlo
- neutron tracking
- on-the-fly
- tempereature

### Cite this

*Proceedings: International Conference on Mathematics and Computational Methods Applied to Nuclear Science & Engineering, M&C 2013*(pp. 950-961)

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*Proceedings: International Conference on Mathematics and Computational Methods Applied to Nuclear Science & Engineering, M&C 2013.*pp. 950-961, International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M&C 2013, Sun Valley, ID, United States, 5/05/13.

**Optimizing the implementation of the target motion sampling temperature treatment technique : How fast can it get?** / Viitanen, Tuomas; Leppänen, Jaakko.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Optimizing the implementation of the target motion sampling temperature treatment technique

T2 - How fast can it get?

AU - Viitanen, Tuomas

AU - Leppänen, Jaakko

PY - 2013

Y1 - 2013

N2 - This article discusses the optimization of the target motion sampling (TMS) temperature treatment method, previously implemented in the Monte Carlo reactor physics code Serpent 2. The TMS method was introduced in [1] and first practical results were presented at the PHYSOR 2012 conference [2]. The method is a stochastic method for taking the effect of thermal motion into account on-the-fly in a Monte Carlo neutron transport calculation. It is based on sampling the target velocities at collision sites and then utilizing the 0 K cross sections at target-at-rest frame for reaction sampling. The fact that the total cross section becomes a distributed quantity is handled using rejection sampling techniques. The original implementation of the TMS requires 2.0 times more CPU time in a PWR pin-cell case than a conventional Monte Carlo calculation relying on pre-broadened effective cross sections. In a HTGR case examined in this paper the overhead factor is as high as 3.6. By first changing from a multi-group to a continuous-energy implementation and then fine-tuning a parameter affecting the conservativity of the majorant cross section, it is possible to decrease the overhead factors to 1.4 and 2.3, respectively. Preliminary calculations are also made using a new and yet incomplete optimization method in which the temperature of the basis cross section is increased above 0 K. It seems that with the new approach it may be possible to decrease the factors even as low as 1.06 and 1.33, respectively, but its functionality has not yet been proven. Therefore, these performance measures should be considered preliminary.

AB - This article discusses the optimization of the target motion sampling (TMS) temperature treatment method, previously implemented in the Monte Carlo reactor physics code Serpent 2. The TMS method was introduced in [1] and first practical results were presented at the PHYSOR 2012 conference [2]. The method is a stochastic method for taking the effect of thermal motion into account on-the-fly in a Monte Carlo neutron transport calculation. It is based on sampling the target velocities at collision sites and then utilizing the 0 K cross sections at target-at-rest frame for reaction sampling. The fact that the total cross section becomes a distributed quantity is handled using rejection sampling techniques. The original implementation of the TMS requires 2.0 times more CPU time in a PWR pin-cell case than a conventional Monte Carlo calculation relying on pre-broadened effective cross sections. In a HTGR case examined in this paper the overhead factor is as high as 3.6. By first changing from a multi-group to a continuous-energy implementation and then fine-tuning a parameter affecting the conservativity of the majorant cross section, it is possible to decrease the overhead factors to 1.4 and 2.3, respectively. Preliminary calculations are also made using a new and yet incomplete optimization method in which the temperature of the basis cross section is increased above 0 K. It seems that with the new approach it may be possible to decrease the factors even as low as 1.06 and 1.33, respectively, but its functionality has not yet been proven. Therefore, these performance measures should be considered preliminary.

KW - doppler

KW - Monte Carlo

KW - neutron tracking

KW - on-the-fly

KW - tempereature

M3 - Conference article in proceedings

SN - 978-162748643-9

SP - 950

EP - 961

BT - Proceedings

ER -