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 and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019
    PublisherAmerican Nuclear Society ANS
    Pages85-95
    Number of pages11
    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 and Computational Methods Applied to Nuclear Science and Engineering, M and 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 and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019. American Nuclear Society ANS, 2019. pp. 85-95
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    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.",
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    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 and Computational Methods Applied to Nuclear Science and Engineering, M and 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 and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019. American Nuclear Society ANS, 2019. p. 85-95.

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

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    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 and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019. American Nuclear Society ANS. 2019. p. 85-95