Global variance reduction scheme with self-adaptive weight-window mesh in the Serpent 2 Monte Carlo Code

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

A global variance reduction (GVR) scheme with self-adaptive weight-window mesh was recently implemented in the Serpent 2 Monte Carlo code. Importances used to define the weight-window boundaries are obtained from a built-in deterministic solver, which applies the response matrix method to the adjoint transport problem. The mesh is based on an octree-type data structure, which can be refined by recursively dividing the mesh cells. The split criteria take into account the local density of the medium and the gradient of the importance distribution. The methodology is demonstrated by photon transport
simulations in a hot-cell geometry, which consists of both heavily shielded structures and large volumes of empty space. The results show that the weight-window mesh adaptation obeys the constraints imposed by the problem geometry, and that the variance reduction scheme provides significant improvement in computational performance compared to an analog Monte Carlo simulation.
Original languageEnglish
Title of host publicationInternational Conference on Mathematics Computational Methods and Reactor Physics (M&C 2019)
PublisherAmerican Nuclear Society ANS
Pages85-95
ISBN (Print)978-0-89448-769-9
Publication statusPublished - 2019
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Mathematics and Computational Methods applied to Nuclear Science and Engineering - Portland, United States
Duration: 25 Aug 201929 Aug 2019

Conference

ConferenceInternational Conference on Mathematics and Computational Methods applied to Nuclear Science and Engineering
CountryUnited States
CityPortland
Period25/08/1929/08/19

Fingerprint

Geometry
Data structures
Photons
Monte Carlo simulation

Keywords

  • Serpent
  • Monte Carlo
  • Global Variance Reduction
  • Weight-windows
  • Radiation Shielding

Cite this

Leppänen, J., & Jokipii, M. (2019). Global variance reduction scheme with self-adaptive weight-window mesh in the Serpent 2 Monte Carlo Code. In International Conference on Mathematics Computational Methods and Reactor Physics (M&C 2019) (pp. 85-95). American Nuclear Society ANS.
Leppänen, Jaakko ; Jokipii, Mika. / Global variance reduction scheme with self-adaptive weight-window mesh in the Serpent 2 Monte Carlo Code. International Conference on Mathematics Computational Methods and Reactor Physics (M&C 2019). American Nuclear Society ANS, 2019. pp. 85-95
@inproceedings{8c47a5c1231d47baa309170f37217602,
title = "Global variance reduction scheme with self-adaptive weight-window mesh in the Serpent 2 Monte Carlo Code",
abstract = "A global variance reduction (GVR) scheme with self-adaptive weight-window mesh was recently implemented in the Serpent 2 Monte Carlo code. Importances used to define the weight-window boundaries are obtained from a built-in deterministic solver, which applies the response matrix method to the adjoint transport problem. The mesh is based on an octree-type data structure, which can be refined by recursively dividing the mesh cells. The split criteria take into account the local density of the medium and the gradient of the importance distribution. The methodology is demonstrated by photon transportsimulations in a hot-cell geometry, which consists of both heavily shielded structures and large volumes of empty space. The results show that the weight-window mesh adaptation obeys the constraints imposed by the problem geometry, and that the variance reduction scheme provides significant improvement in computational performance compared to an analog Monte Carlo simulation.",
keywords = "Serpent, Monte Carlo, Global Variance Reduction, Weight-windows, Radiation Shielding",
author = "Jaakko Lepp{\"a}nen and Mika Jokipii",
year = "2019",
language = "English",
isbn = "978-0-89448-769-9",
pages = "85--95",
booktitle = "International Conference on Mathematics Computational Methods and Reactor Physics (M&C 2019)",
publisher = "American Nuclear Society ANS",
address = "United States",

}

Leppänen, J & Jokipii, M 2019, Global variance reduction scheme with self-adaptive weight-window mesh in the Serpent 2 Monte Carlo Code. in International Conference on Mathematics Computational Methods and Reactor Physics (M&C 2019). American Nuclear Society ANS, pp. 85-95, International Conference on Mathematics and Computational Methods applied to Nuclear Science and Engineering, Portland, United States, 25/08/19.

Global variance reduction scheme with self-adaptive weight-window mesh in the Serpent 2 Monte Carlo Code. / Leppänen, Jaakko; Jokipii, Mika.

International Conference on Mathematics Computational Methods and Reactor Physics (M&C 2019). American Nuclear Society ANS, 2019. p. 85-95.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

TY - GEN

T1 - Global variance reduction scheme with self-adaptive weight-window mesh in the Serpent 2 Monte Carlo Code

AU - Leppänen, Jaakko

AU - Jokipii, Mika

PY - 2019

Y1 - 2019

N2 - A global variance reduction (GVR) scheme with self-adaptive weight-window mesh was recently implemented in the Serpent 2 Monte Carlo code. Importances used to define the weight-window boundaries are obtained from a built-in deterministic solver, which applies the response matrix method to the adjoint transport problem. The mesh is based on an octree-type data structure, which can be refined by recursively dividing the mesh cells. The split criteria take into account the local density of the medium and the gradient of the importance distribution. The methodology is demonstrated by photon transportsimulations in a hot-cell geometry, which consists of both heavily shielded structures and large volumes of empty space. The results show that the weight-window mesh adaptation obeys the constraints imposed by the problem geometry, and that the variance reduction scheme provides significant improvement in computational performance compared to an analog Monte Carlo simulation.

AB - A global variance reduction (GVR) scheme with self-adaptive weight-window mesh was recently implemented in the Serpent 2 Monte Carlo code. Importances used to define the weight-window boundaries are obtained from a built-in deterministic solver, which applies the response matrix method to the adjoint transport problem. The mesh is based on an octree-type data structure, which can be refined by recursively dividing the mesh cells. The split criteria take into account the local density of the medium and the gradient of the importance distribution. The methodology is demonstrated by photon transportsimulations in a hot-cell geometry, which consists of both heavily shielded structures and large volumes of empty space. The results show that the weight-window mesh adaptation obeys the constraints imposed by the problem geometry, and that the variance reduction scheme provides significant improvement in computational performance compared to an analog Monte Carlo simulation.

KW - Serpent

KW - Monte Carlo

KW - Global Variance Reduction

KW - Weight-windows

KW - Radiation Shielding

UR - http://www.ans.org/store/item-700432/

M3 - Conference article in proceedings

SN - 978-0-89448-769-9

SP - 85

EP - 95

BT - International Conference on Mathematics Computational Methods and Reactor Physics (M&C 2019)

PB - American Nuclear Society ANS

ER -

Leppänen J, Jokipii M. Global variance reduction scheme with self-adaptive weight-window mesh in the Serpent 2 Monte Carlo Code. In International Conference on Mathematics Computational Methods and Reactor Physics (M&C 2019). American Nuclear Society ANS. 2019. p. 85-95