Whewell | Publications

Publications & Presentations

Application of Reinforcement Learning for Multigroup Energy Grid Optimization for Neutron Transport Criticality Problems.

Ben Whewell, Nathan Gibson, and Ajeeta Khatiwada, (2026). Under Review. ArXiv: 2605.27895 Request publication

Deep reinforcement learning for sequential decision-making and combinatorial optimization.

@misc{whewell2026rlgrid,
  author        = {Whewell, Ben and Gibson, Nathan and Khatiwada, Ajeeta},
  title         = {{Application of Reinforcement Learning for Multigroup Energy Grid Optimization for Neutron Transport Criticality Problems}},
  year          = {2026},
  eprint        = {2605.27895},
  archivePrefix = {arXiv},
  note          = {Under review}
}

Application of Reinforcement Learning to Multigroup Energy Grid Optimization for Criticality Problems.

Ben Whewell, Nathan Gibson, and Ajeeta Khatiwada, (2025). International Conference on the Physics of Reactors (PHYSOR). Accepted. Request publication

Deep reinforcement learning for sequential decision-making and combinatorial optimization.

@inproceedings{whewell2025physor,
  author    = {Whewell, Ben and Gibson, Nathan and Khatiwada, Ajeeta},
  title     = {{Application of Reinforcement Learning to Multigroup Energy Grid Optimization for Criticality Problems}},
  booktitle = {International Conference on the Physics of Reactors (PHYSOR)},
  year      = {2025},
  note      = {Accepted}
}

Predicting Self-Shielded Multigroup Microscopic Cross Sections Using Artificial Neural Networks.

Joshua Nichols, Ben Whewell, Nathan Gibson, and Andrew Osborne, (2025). International Conference on the Physics of Reactors (PHYSOR). Under Review.

Artificial neural networks for surrogate regression modeling.

@inproceedings{nichols2025shielding,
  author    = {Nichols, Joshua and Whewell, Ben and Gibson, Nathan and Osborne, Andrew},
  title     = {{Predicting Self-Shielded Multigroup Microscopic Cross Sections Using Artificial Neural Networks}},
  booktitle = {International Conference on the Physics of Reactors (PHYSOR)},
  year      = {2025},
  note      = {Under review}
}

MetaHeuristic Feature Selection for Energy Group Optimization and Analysis.

Natalie Rouse, Benjamin Whewell, and Nathan Gibson, (2025). Technical Report LA-UR-25-29285, Los Alamos National Laboratory. DOI: 10.2172/2588817

Metaheuristic feature selection for high-dimensional optimization.

@techreport{rouse2025metaheuristic,
  author      = {Rouse, Natalie and Whewell, Benjamin and Gibson, Nathan},
  title       = {{MetaHeuristic Feature Selection for Energy Group Optimization and Analysis}},
  institution = {Los Alamos National Laboratory},
  year        = {2025},
  number      = {LA-UR-25-29285},
  doi         = {10.2172/2588817}
}

Single Grid Error Estimation for Neutron Transport Solvers.

Ben Whewell and Ryan G. McClarren, (2025). Journal of Verification, Validation and Uncertainty Quantification. 10(2): 021001. DOI: 10.1115/1.4069426 Request publication

@article{whewell2025vvuq,
  author  = {Whewell, Ben and McClarren, Ryan G.},
  title   = {{Single Grid Error Estimation for Neutron Transport Solvers}},
  journal = {Journal of Verification, Validation and Uncertainty Quantification},
  year    = {2025},
  volume  = {10},
  number  = {2},
  pages   = {021001},
  doi     = {10.1115/1.4069426}
}

Collision-Based Hybrid Method for Two-Dimensional Neutron Transport Problems.

Ben Whewell and Ryan G. McClarren, (2025). Nuclear Science and Engineering, 1-23. DOI: 10.1080/00295639.2025.2489778 Request publication

@article{whewell2025hybrid2d,
  author  = {Whewell, Ben and McClarren, Ryan G.},
  title   = {{Collision-Based Hybrid Method for Two-Dimensional Neutron Transport Problems}},
  journal = {Nuclear Science and Engineering},
  year    = {2025},
  pages   = {1--23},
  doi     = {10.1080/00295639.2025.2489778}
}

Single Grid Error Estimate in Two-Dimensional Neutron Transport Problems.

Ben Whewell and Ryan G. McClarren, (2025). The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering. Request publication

@inproceedings{whewell2025mcsinglegrid,
  author    = {Whewell, Ben and McClarren, Ryan G.},
  title     = {{Single Grid Error Estimate in Two-Dimensional Neutron Transport Problems}},
  booktitle = {The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering},
  year      = {2025}
}

Single Grid Error Estimate in Two-Dimensional Neutron Transport Problems.

Ben Whewell and Ryan G. McClarren, (2025). The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering. Technical Session. Request publication

@misc{whewell2025mcsinglegrid-talk,
  author       = {Whewell, Ben and McClarren, Ryan G.},
  title        = {{Single Grid Error Estimate in Two-Dimensional Neutron Transport Problems}},
  year         = {2025},
  howpublished = {Technical session, The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering}
}

Hybrid Numerical Methods and Solution Verification for the Neutron Transport Equation.

Benjamin Joseph Whewell, (2024). University of Notre Dame. Dissertation. DOI: 10.7274/27927858.v1 Request publication

@phdthesis{whewell2024dissertation,
  author = {Whewell, Benjamin Joseph},
  title  = {{Hybrid Numerical Methods and Solution Verification for the Neutron Transport Equation}},
  school = {University of Notre Dame},
  year   = {2024},
  doi    = {10.7274/27927858.v1}
}

Solution Verification with the Method of Nearby Problems for Neutron Transport Applications.

Ben Whewell and Ryan G. McClarren, (2023). The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering. Request publication

@inproceedings{whewell2023nearby,
  author    = {Whewell, Ben and McClarren, Ryan G.},
  title     = {{Solution Verification with the Method of Nearby Problems for Neutron Transport Applications}},
  booktitle = {The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering},
  year      = {2023}
}

Solution Verification with the Method of Nearby Problems for Neutron Transport Applications.

Ben Whewell and Ryan G. McClarren, (2023). The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering. Poster Presentation. Request publication

@misc{whewell2023nearby-poster,
  author       = {Whewell, Ben and McClarren, Ryan G.},
  title        = {{Solution Verification with the Method of Nearby Problems for Neutron Transport Applications}},
  year         = {2023},
  howpublished = {Poster presentation, The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering}
}

Multigroup Neutron Transport Using a Collision-Based Hybrid Method.

Ben Whewell, Ryan G. McClarren, Cory D. Hauck, and Minwoo Shin, (2023). Nuclear Science and Engineering, 197:7, 1386-1405. DOI: 10.1080/00295639.2022.2154119 Request publication

@article{whewell2023multigroup,
  author  = {Whewell, Ben and McClarren, Ryan G. and Hauck, Cory D. and Shin, Minwoo},
  title   = {{Multigroup Neutron Transport Using a Collision-Based Hybrid Method}},
  journal = {Nuclear Science and Engineering},
  year    = {2023},
  volume  = {197},
  number  = {7},
  pages   = {1386--1405},
  doi     = {10.1080/00295639.2022.2154119}
}

A low-rank power iteration scheme for neutron transport criticality problems.

Jonas Kusch, Benjamin Whewell, Ryan McClarren, and Martin Frank, (2022). Journal of Computational Physics, 470, 111587. DOI: 10.1016/j.jcp.2022.111587

@article{kusch2022lowrank,
  author  = {Kusch, Jonas and Whewell, Benjamin and McClarren, Ryan G. and Frank, Martin},
  title   = {{A low-rank power iteration scheme for neutron transport criticality problems}},
  journal = {Journal of Computational Physics},
  year    = {2022},
  volume  = {470},
  pages   = {111587},
  doi     = {10.1016/j.jcp.2022.111587}
}

Data Reduction in Deterministic Neutron Transport Calculations Using Machine Learning.

Ben Whewell and Ryan G. McClarren, (2022). Annals of Nuclear Energy, 176, p. 109276. DOI: 10.1016/j.anucene.2022.109276 Request publication

Neural-network autoencoders for dimensionality reduction and model compression.

@article{whewell2022datareduction,
  author  = {Whewell, Ben and McClarren, Ryan G.},
  title   = {{Data Reduction in Deterministic Neutron Transport Calculations Using Machine Learning}},
  journal = {Annals of Nuclear Energy},
  year    = {2022},
  volume  = {176},
  pages   = {109276},
  doi     = {10.1016/j.anucene.2022.109276}
}

Reduced Models for Nuclear Data in Transport Equations.

B. Whewell and Ryan G. McClarren, (2021). The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, p. 1427-1436. Request publication

Dimensionality reduction and reduced-order modeling.

@inproceedings{whewell2021reduced,
  author    = {Whewell, Ben and McClarren, Ryan G.},
  title     = {{Reduced Models for Nuclear Data in Transport Equations}},
  booktitle = {The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering},
  year      = {2021},
  pages     = {1427--1436}
}

Reduced Models for Nuclear Data in Transport Equations.

B. Whewell and Ryan G. McClarren, (2021). Society for Industrial and Applied Mathematics Conference on Computational Science and Engineering. Virtual. Request publication

Dimensionality reduction and reduced-order modeling.

@misc{whewell2021reduced-talk,
  author       = {Whewell, Ben and McClarren, Ryan G.},
  title        = {{Reduced Models for Nuclear Data in Transport Equations}},
  year         = {2021},
  howpublished = {Society for Industrial and Applied Mathematics Conference on Computational Science and Engineering, virtual}
}

Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features.

B. Whewell, M. Grosskopf, and D. Neudecker, (2020). Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment, 978, p. 164305. DOI: 10.1016/j.nima.2020.164305 Request publication

Supervised ML regression with feature engineering on experimental data and covariances.

@article{whewell2020pu239,
  author  = {Whewell, Ben and Grosskopf, Michael and Neudecker, Denise},
  title   = {{Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features}},
  journal = {Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment},
  year    = {2020},
  volume  = {978},
  pages   = {164305},
  doi     = {10.1016/j.nima.2020.164305}
}

Applying Autoencoders for Data Reduction of Neutron Scattering Matrices.

Ben Whewell and Ryan G. McClarren, (2020). Conference on Data Analysis. Poster Presentation. Request publication

Autoencoder representation learning for high-dimensional data compression.

@misc{whewell2020autoencoders,
  author       = {Whewell, Ben and McClarren, Ryan G.},
  title        = {{Applying Autoencoders for Data Reduction of Neutron Scattering Matrices}},
  year         = {2020},
  howpublished = {Poster presentation, Conference on Data Analysis}
}

Data Fusion Techniques for Improving Fission Neutron Multiplicity Data.

Benjamin Whewell, Ryan G. McClarren, and Simon Bolding, (2019). The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, p. 1072-1080. Request publication

Statistical data fusion for multi-source data integration.

@inproceedings{whewell2019datafusion,
  author    = {Whewell, Benjamin and McClarren, Ryan G. and Bolding, Simon},
  title     = {{Data Fusion Techniques for Improving Fission Neutron Multiplicity Data}},
  booktitle = {The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering},
  year      = {2019},
  pages     = {1072--1080}
}

Adjusting for Outlying Observations in Nuclear Data Evaluation using Machine Learning.

Benjamin Whewell, (2019). Technical Report LA-UR-19-26924, Los Alamos National Laboratory. Request publication

ML-based anomaly and outlier detection for data quality.

@techreport{whewell2019outliers,
  author      = {Whewell, Benjamin},
  title       = {{Adjusting for Outlying Observations in Nuclear Data Evaluation using Machine Learning}},
  institution = {Los Alamos National Laboratory},
  year        = {2019},
  number      = {LA-UR-19-26924}
}