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Deterministic High-Fidelity Neutronics Simulation of Pebble Bed Reactors Using Pebble Tracking Transport.

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Title: Deterministic High-Fidelity Neutronics Simulation of Pebble Bed Reactors Using Pebble Tracking Transport.
Authors: Carlson, Liam1 (AUTHOR) carlsonl@tamu.edu, Ragusa, Jean C.1 (AUTHOR), Balestra, Paolo2 (AUTHOR), Wang, Yaqi2 (AUTHOR)
Source: Nuclear Science & Engineering. 2026 Suppl 1, Vol. 200, pS574-S594. 21p.
Subject Terms: *Pebble bed reactors, *Neutron transport theory, *Clustering algorithms, *K-means clustering, *Deterministic algorithms, *Nuclear reactor cores, *Supercomputers
Abstract: The pebble tracking transport (PTT) algorithm offers a high-fidelity deterministic approach for neutron transport for pebble bed reactors (PBRs). This approach requires the mesh for the active-core region to consist exclusively of tetrahedral elements, where each node in the pebble-packing region represents a pebble centroid. This paper investigates the application of PTT for full-scale PBRs, considering both the isothermal and the temperature-dependent core conditions. Macroscopic cross sections are generated using Serpent 2 full-core eigenvalue simulations where pebbles are grouped into disjoint subsets using machine learning. To minimize the need for individual cross-section sets for each pebble in the core, K-means clustering is used to group pebbles by temperature and neutronic environment parameters. We compare the multiplication factor and power rate distributions between PTT simulations using the Griffin reactor physics software and reference solutions from Serpent 2. Our analysis shows that a full-core, high-fidelity PTT calculation produces accurate results with minimal local (pebblewise) errors. Additionally, timing results indicate that PTT simulations converge rapidly on modern supercomputing platforms. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 192155921
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Deterministic High-Fidelity Neutronics Simulation of Pebble Bed Reactors Using Pebble Tracking Transport.
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  Data: <searchLink fieldCode="AR" term="%22Carlson%2C+Liam%22">Carlson, Liam</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> carlsonl@tamu.edu</i><br /><searchLink fieldCode="AR" term="%22Ragusa%2C+Jean+C%2E%22">Ragusa, Jean C.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Balestra%2C+Paolo%22">Balestra, Paolo</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Yaqi%22">Wang, Yaqi</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Nuclear+Science+%26+Engineering%22">Nuclear Science & Engineering</searchLink>. 2026 Suppl 1, Vol. 200, pS574-S594. 21p.
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  Data: *<searchLink fieldCode="DE" term="%22Pebble+bed+reactors%22">Pebble bed reactors</searchLink><br />*<searchLink fieldCode="DE" term="%22Neutron+transport+theory%22">Neutron transport theory</searchLink><br />*<searchLink fieldCode="DE" term="%22Clustering+algorithms%22">Clustering algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22K-means+clustering%22">K-means clustering</searchLink><br />*<searchLink fieldCode="DE" term="%22Deterministic+algorithms%22">Deterministic algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Nuclear+reactor+cores%22">Nuclear reactor cores</searchLink><br />*<searchLink fieldCode="DE" term="%22Supercomputers%22">Supercomputers</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The pebble tracking transport (PTT) algorithm offers a high-fidelity deterministic approach for neutron transport for pebble bed reactors (PBRs). This approach requires the mesh for the active-core region to consist exclusively of tetrahedral elements, where each node in the pebble-packing region represents a pebble centroid. This paper investigates the application of PTT for full-scale PBRs, considering both the isothermal and the temperature-dependent core conditions. Macroscopic cross sections are generated using Serpent 2 full-core eigenvalue simulations where pebbles are grouped into disjoint subsets using machine learning. To minimize the need for individual cross-section sets for each pebble in the core, K-means clustering is used to group pebbles by temperature and neutronic environment parameters. We compare the multiplication factor and power rate distributions between PTT simulations using the Griffin reactor physics software and reference solutions from Serpent 2. Our analysis shows that a full-core, high-fidelity PTT calculation produces accurate results with minimal local (pebblewise) errors. Additionally, timing results indicate that PTT simulations converge rapidly on modern supercomputing platforms. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/00295639.2025.2471722
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: S574
    Subjects:
      – SubjectFull: Pebble bed reactors
        Type: general
      – SubjectFull: Neutron transport theory
        Type: general
      – SubjectFull: Clustering algorithms
        Type: general
      – SubjectFull: K-means clustering
        Type: general
      – SubjectFull: Deterministic algorithms
        Type: general
      – SubjectFull: Nuclear reactor cores
        Type: general
      – SubjectFull: Supercomputers
        Type: general
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      – TitleFull: Deterministic High-Fidelity Neutronics Simulation of Pebble Bed Reactors Using Pebble Tracking Transport.
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            NameFull: Carlson, Liam
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            NameFull: Ragusa, Jean C.
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            NameFull: Balestra, Paolo
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            NameFull: Wang, Yaqi
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            – D: 02
              M: 02
              Text: 2026 Suppl 1
              Type: published
              Y: 2026
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              Value: 200
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            – TitleFull: Nuclear Science & Engineering
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