SERPENT validation and optimization with mesh adaptive search on stereolithography geometry models

Alberto Talamo (Corresponding Author), Yousry Gohar, Jaakko Leppänen

    Research output: Contribution to journalArticleScientificpeer-review

    17 Citations (Scopus)


    The SERPENT Monte Carlo code has the unique capability to simulate neutron and gamma transport using a stereolithography (STL) geometry. The STL geometry can model irregular complex geometries often encountered, for example, in research reactors. This geometry type can be used in combination with an unstructured mesh-based interface to couple SERPENT to OpenFOAM for CFD analyses. The STL file format also allows printing the geometry model with 3D printers. This work validates SERPENT simulations based on the STL geometry using the GIACINT critical experimental facility and the YALINA Thermal subcritical experimental facility. The results and performances of SERPENT have been compared with those of the well-known MCNP code. Finally, SERPENT computing time has been significantly reduced by using its mesh adaptive search algorithm, which has been introduced to optimize simulations based on the stereolithography STL geometry, and a hybrid modeling that mixes combinatorial and STL geometries. In this work, the STL geometry model of SERPENT involved the use of multiple software and programming languages, including: CUBIT, PYTHON, C, and MATLAB.

    Original languageEnglish
    Pages (from-to)619-632
    JournalAnnals of Nuclear Energy
    Publication statusPublished - 1 May 2018
    MoE publication typeA1 Journal article-refereed


    • ABAQUS
    • CUBIT
    • Stereolithography
    • Tetrahedron
    • Unstructured mesh


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