News

Lauren has been selected by the OECD NEA Global Forum Rising Stars Programme. She will present her research work at the NEA Global Forum Rising Stars Workshop 2024 at the European Commission Joint Research Centre (JRC) in Karlsruhe, Germany on 25-26 November 2024.

Ziyu successfully defended his PhD thesis titled “Machine Learning-based Model Discrepancy in Bayesian Inverse Uncertainty Quantification”. Congratulations Ziyu!

Aidan won the 2nd place in the 2024 DOE Cybersecurity and Technology Innovation Conference student poster contest. The title of his poster is “Hybrid and Pure Machine Learning Models in Limited Data Scenarios”, based on his work at ORNL with Dr. Xingang Zhao and Dr. Bob Salko.

The U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) Office of Defense Nuclear Nonproliferation has awarded $25 million to the “Enabling Capabilities in Technology Consortium” led by the University of Tennessee – Knoxville. Dr. Wu will be a co-PI of this 5-year consortium award along with three other faculty members at NCSU NE Department. See more details at https://www.energy.gov/nnsa/articles/nnsa-awards-50-million-cooperative-agreements-two-university-consortia-support and https://ne.ncsu.edu/news/2024/nc-state-nuclear-engineering-faculty-to-participate-in-university-of-tennessee-knoxville-nnsa-funded-award/

Chris and Sofiia attended the 2024 DOE National Nuclear Security Administration (NNSA) University Program Review (UPR) Meeting at Texas A&M University, College Station, TX during June 4-6, 2024. Chris gave a presentation titled “Improving the Quality of Nuclear Data for Radiation Transport Simulations in Nuclear Forensics Applications” as part of the Consortium for Nuclear Forensics (CNF).

PhD students Farah, Alie, and undergraduate student (incoming PhD) Lauren attended the 2024 Best Estimate Plus Uncertainty International Conference (BEPU 2024) at Lucca, Italy during May 19-24, 2024. Five papers from the ARTISANS group were presented: (1) “Uncertainty Quantification of Long Short-Term Memory Autoencoder for Monitoring of Liquid Sodium Cold Trap”, (2) “Bayesian Calibration of Fiber Optic Distributed Temperature Sensing in a Thermal Mixing Tee”, (3) “Uncertainty Quantification and Improved Neural Networks Predictions using Data Augmentation by Variational Autoencoders”, (4) “Hierarchical Bayesian Inverse Uncertainty Quantification with Application to the ATRIUM project”, and (5) “Elucidating the Uncertainties Introduced by Data-Driven Machine Learning Models”.

Chris’s journal article titled “Design Considerations and Monte Carlo Criticality Analysis of Spiral Plate Heat Exchangers for Molten Salt Reactors” has been accepted for publication in Progress in Nuclear Energy.

Lauren has been selected for the 2024-2025 ANS John and Muriel Landis Scholarship! She will receive $5,000 fund support each year for up to five years.

Sofiia has been selected for the American Nuclear Society (ANS) general scholarship.

Dr. Wu has been elected to the Executive Committee of the Thermal Hydraulics Division of the American Nuclear Society (ANS).

Dr. Wu has been awarded the US DOE Office of Nuclear Energy Distinguished Early Career Program (DECP). He will receive $625,000 funding support over the next five years to support a project on “Establishing the Predictive Credibility of Data-Driven Scientific Machine Learning for Nuclear Applications.” Read More

Both Jason and Sofiia have been awarded the $10,000 US DOE University Nuclear Leadership Program (UNLP) Scholarship for the 2024 – 2025 academic year.

Lauren has been awarded the US DOE University Nuclear Leadership Program (UNLP) Fellowship, a three-year, $169,000 fellowship beginning in the Fall of 2024. It will support Lauren’s PhD research at NCSU.

Congratulations to Lauren for winning the Best Presentation Award in the Division of Power Reactor Reliability Operations & Safety at the 2024 ANS Student Conference, for her senior design presentation titled “Enhancing Probabilistic Risk Assessment for the PULSTAR Research Reactor with Advanced Fault Tree and Initiating Event Analysis Techniques.”

Congratulations to Lauren and Jason for winning the Best Overall Paper Award at the 2024 ANS Student Conference, for a paper titled “ML-LIBS: Machine Learning-Based Spectra Predictions of Time-Dependent Lithium Emission Spectroscopy Imaging.”

Our invited Technical Opinion Paper (TOP) titled “ARTISANS – Artificial Intelligence for Simulation of Advanced Nuclear Systems for Nuclear Fission Technology” has been accepted for publication at Nuclear Engineering and Design. This TOP is a part of Virtual Special Issues (VSI) Nuclear Fission Technology (NFT) series at NED.

Aidan successfully defended his MS thesis, with the title “Prediction of CIPS Susceptibility in PWR Assemblies Using 3D Convolutional Neural Networks.”

Mahmoud successfully defended his MS thesis, with the title “Uncertainty Quantification in Deep Neural Network Models for Nuclear Reactor Benchmarks.”

Lauren has been awarded the 2024-2025 ANS Robert A. Dannels Memorial Scholarship by the ANS Mathematics and Computation Division (MCD).

Jason has been awarded the 2024-2025 ANS Joseph Naser Undergraduate Scholarship by the ANS Human Factors, Instrumentation and Controls Division (HFICD).

Our collaboration paper titled “A systematic approach for the adequacy analysis of a set of experimental databases: Application in the framework of the ATRIUM activity” has been published at Nuclear Engineering and Design. It is part of the OECD/NEA ATRIUM (Application Tests for Realization of Inverse Uncertainty quantification and validation Methodologies in thermal-hydraulics) project.

Dr. Wu attended the SIAM UQ24 conference in Trieste Italy, and gave two invited presentations. The first one is titled “Inverse Uncertainty Quantification Methods of Nuclear System Thermal-Hydraulics Codes” in the mini-symposium on “Uncertainty Quantification of Thermal-Hydraulics Models in Nuclear Engineering”. The second one is titled “Uncertainty Quantification of Deep Neural Networks for Nuclear Reactor Applications” in the mini-symposium on “Recent Advances in Uncertainty Quantification for Scientific Machine Learning”. (https://www.siam.org/conferences/cm/conference/uq24)

Ziyu’s paper titled “Functional PCA and Deep Neural Networks-based Bayesian Inverse Uncertainty Quantification with Transient Experimental Data” has been accepted for publication in a prestigious journal in computational science and engineering, Computer Methods in Applied Mechanics and Engineering (impact factor 7.2).

Congratulations to Lauren for being selected by the Roy G. Post scholarship, through which she is invited for a poster presentation at Waste Management Conference 2024 (WM2024) in March 10 – 14, 2024 at Phoenix, AZ.

Chris passed his PhD Qualification Exam. The presentation title is “Review of Inverse Problems and Their Application to Nuclear Forensics.”

Ziyu passed his PhD Preliminary Examination. The title is “Machine Learning-based Model Discrepancy in Bayesian Inverse Uncertainty Quantification”.

Dr. Wu attended the OECD/NEA WGAMA ATRIUM workshop at the OECD Convention Center in Paris where he was invited to give two presentations on Inverse Uncertainty Quantification.

Alie’s research work with Argonne National Laboratory has been featured at a Press Release of Argonne. “Advances in machine learning for nuclear power operations spell a brighter future for carbon-free energy – New Argonne research shows how machine learning can enhance nuclear reactor security and efficiency for a sustainable tomorrow.” Read more

Farah’s paper titled “Deep Generative Modeling-based Data Augmentation with Demonstration using the BFBT Benchmark Void Fraction Datasets” has been accepted for publication in Nuclear Engineering and Design.