Vladimir Sobes

Assistant Professor and Charles P. Postelle Professor in Nuclear Engineering

Biography

Vladimir Sobes is an Assistant Professor and Charles P. Postelle Professor in Nuclear Engineering at the University of Tennessee, Knoxville. Professor Sobes’ research covers a broad spectrum of neutron transport physics. Vlad received his Bachelor Science degree in 2011 and a PhD in 2013, both from the Department of Nuclear Science and Engineering at the Massachusetts Institute of Technology. Prior to joining UTK, he was a Research and Development staff member at Oak Ridge National Laboratory.

Research

Sobes’ research interests currently span four major areas from nuclear physics to reactor design. With a background in nuclear data, he continues to work on problems in the nuclear data pipeline with a particular interest in the application of Artificial Intelligence (AI)/ Machine Learning (ML) algorithms.

Further research projects look at improving radiation transport calculations and how to accelerate simulations of nuclear systems on modern heterogeneous computing architectures (HPC). Research in advanced and traditional nuclear reactor analysis, including Sensitivity/Uncertainty (S/U) analysis methods, continues to be of interest. Developing algorithms for autonomous design of nuclear systems is a new research area.  Finally, the entire research portfolio is applied to the design and operation of the Flexible Neutron Source experiment.

Education

Massachusetts Institute of Technology, PhD Nuclear Science and Engineering, Feb. 2011–Sept. 2013
Thesis: Coupled Differential and Integral Data Analysis for Improved Uncertainty Quantification of the Cu-63,65 Cross Section Evaluations.

Massachusetts Institute of Technology, BS Nuclear Science and Engineering, Sept. 2007–Feb. 2011
Thesis: Individual Pebble Temperature Peaking Factor due to Local Pebble Arrangement in a Pebble Bed Reactor Core.

Professional Service

• Founding member and group coordinator of OECD/NEA Working Party on International Nuclear Data Evaluation Co-operation (WPEC) Subgroup 51 on “Evaluation, Processing and Validation in the Unresolved Resonance Region.”

• Founding member and group coordinator of OECD/NEA Working Party on International Nuclear Data Evaluation Co-operation (WPEC) Subgroup 44 on “Investigation of Covariance Data in General Purpose Nuclear Data Libraries.
• IAEA Consultants Group on Machine Learning for Nuclear Data

• IAEA International Nuclear Data Evaluation Network (INDEN) Vienna, Austria

• American Nuclear Society, Former Chair of the Technical Program Committee for Nuclear Criticality Safety Division

Awards and Recognitions

• 2023 Excellence in Advising, UTK Academic Honors Award

• 2022 Mark Mills Award, American Nuclear Society. Awarded to PhD advisee, Dr. John Pevey, for the best technical journal article of the year. “Neural Network Acceleration of Genetic Algorithms for the Optimization of A Coupled Fast/Thermal Nuclear Experiment”

• 2020 Early Career Reactor Physicist Award, American Nuclear Society, The Reactor Physics Division Early Career Reactor Physicist Award recognizes early career members of the RPD who have made significant contributions in the field of reactor physics.

• 2020 Transformational Challenge Reactor (TCR) Program Magazine Features. Sobes was the lead PI for the AI optimization of the reactor core.
  • Forbes Magazine: “3D Printing Has Entered The Nuclear Realm”
  • Wired Magazine: “Coming Soon: A Nuclear Reactor—With a 3D-Printed Core”
  • Power Magazine: “Nuclear Reactor with 3D-Printed Core Slated for Operation in 2023”

Publications

A full list of Sobes’ publications is available at his Google Scholar Profile.

• Lentchner, G., Fritsch, W., Crowder, R., Walton, N., Lewis, A., Chvala, O., Clarno, K., & Sobes, V. (2024). Incorrect resonance escape probability in Monte Carlo codes due to the threshold approximation of temperature-dependent scattering. Annals of Nuclear Energy, 207, 110717.

• Sobes, V., Popov, E., Archibald, R., Hiscox, B., & Ade, B. (2024). On the advantages of radial variation in assembly design for a nuclear reactor core. Nuclear Engineering and Design, 417.

• Walton, N. A. W., Zivenko, O., Fritsch, W., Forbes, J., Lewis, A., Brown, J., & Sobes, V. (2024). Automated Resonance Identification in Nuclear Data Evaluation.

• Walton, N., Brown, J., Fritsch, W., Brown, D., Nobre, G., & Sobes, V. (2024). Methodology for physics-informed generation of synthetic neutron time-of-flight measurement data. Computer Physics Communications, 294.

• Williams, A., Walton, N., Maryanski, A., Bogetic, S., Hines, W., & Sobes, V. (2023). Stochastic gradient descent for optimization for nuclear systems. Scientific Reports, 13(1).

• Walton, N. A. W., Crowder, R., Satvat, N., Brown, N. R., & Sobes, V. (2022). Demonstration of a random sampling approach to uncertainty propagation for generic pebble-bed fluoride-salt-cooled high temperature reactor (gFHR). Nuclear Engineering and Design, 395.

• Pevey, J., Sobes, V., & Hines, W. J. (2022). Neural Network Acceleration of Genetic Algorithms for the Optimization of a Coupled Fast/Thermal Nuclear Experiment. Frontiers in Energy Research, 10.

• Sobes, V., Hiscox, B., Popov, E., Archibald, R., Hauck, C., Betzler, B., & Terrani, K. (2021). AI-based design of a nuclear reactor core. Scientific Reports, 11(1).

• Sobes, V., Ducru, P., Alhajri, A., Ganapol, B., & Forget, B. (2021). An Analytic Benchmark for Neutron Boltzmann Transport with Downscattering—Part I: Flux and Eigenvalue Solutions. Nuclear Science and Engineering, 195(8), 795–812.

• Sobes, V., Holcomb, A., Marshall, B. J., Greene, T., Wiarda, D., & Wieselquist, W. (2021). Augmented ENDF/B-VIII.0 covariance library for SCALE 6.3. Annals of Nuclear Energy, 160.