selected publications academicarticle Wang, C., Liu, Y., Sun, X., & Sabharwall, P. A hybrid porous model for full reactor core scale CFD investigation of a prismatic HTGR. Annals of Nuclear Energy. 151, 107916-107916. Ndum, Z., Tao, J., Ford, J., & Liu, Y. Automating Input-File Based Modeling and Simulation with Large Language Model Agents: An Autofluka Case Study Liu, Y., Mui, T., Xie, Z., & Hu, R. Benchmarking FFTF LOFWOS Test# 13 using SAM code: Baseline model development and uncertainty quantification. Annals of Nuclear Energy. 192, 110010-110010. Liu, Y., Hu, R., Kraus, A., Balaprakash, P., & Obabko, A. Data-driven modeling of coarse mesh turbulence for reactor transient analysis using convolutional recurrent neural networks. Nuclear Engineering and Design. 390, 111716-111716. Liu, Y., Alsafadi, F., Mui, T., OGrady, D., & Hu, R. Development of Whole System Digital Twins for Advanced Reactors: Leveraging Graph Neural Networks and SAM Simulations. Nuclear Technology. 1-18. Zhong, X., Wang, J., Zhao, X., Liu, Y., & Revankar, S. T. Editorial: Artificial Intelligence Applications in Nuclear Energy. Frontiers in Energy Research. 10. Liu, Q., Sun, H., Liu, Y., Kelly, J., & Sun, X. Experimental study of post-CHF heat transfer in a vertical tubular test section. International Journal of Heat and Mass Transfer. 166, 120697-120697. Liu, Y., Hu, R., Zou, L., & Nunez, D. SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability. Nuclear Engineering and Design. 400, 112059-112059. Liu, Q., Liu, Y., Burak, A., Kelly, J., Bajorek, S., & Sun, X. Tree-Based Ensemble Learning Models for Wall Temperature Predictions in Post-Critical Heat Flux Flow Regimes at Subcooled and Low-Quality Conditions. 145(4), Liu, Y., Dinh, N., Sun, X., & Hu, R. Uncertainty Quantification for Multiphase Computational Fluid Dynamics Closure Relations with a Physics-Informed Bayesian Approach. Nuclear Technology. 209(12), 2002-2015. Liu, Y., Wang, C., Qian, Y., Sun, X., & Liu, Y. Uncertainty analysis of PIV measurements in bubbly flows considering sampling and bubble effects with ray optics modeling. Nuclear Engineering and Design. 364, 110677-110677. Liu, Y., Wang, D., Sun, X., Liu, Y., Dinh, N., & Hu, R. Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments. Reliability Engineering & System Safety. 212, 107636-107636. conference paper Ndum, Z. N., Lim, D., Tao, J., Ford, J., Adu, S., Hassan, H., & Liu, Y. (2025). Development and Demonstration of a Digital Twin-based Remote-Control Framework for Small-Scale Advanced Reactors Ndum, Z. N., Tao, J., Liu, Y., Ford, J., Vlassov, V., Morton, N., ... Adu, S. (2024). A Digital Twin-Based Simulator for Small Modular and Microreactors Ndum, Z. N., Ford, J., Mazzucconi, D., Pola, A., Perez, D., Braby, L., Olive, A., & Liu, Y. (2024). Design, construction, and calibration of an Avalanche-confinement Tissue Equivalent Proportional Counter (AcTEPC) for Radiation Monitoring in Space and Therapeutic Applications Liu, Y., Hu, G., & Hu, R. BENCHMARK SIMULATION OF THE FFTF LOFWOS TEST #13 USING SAM Liu, Y. Development of data-driven eddy viscosity closure to support MSR flow and heat transfer modeling based on SAM-ML Abulawi, Z., Hu, R., & Liu, Y. Eddy Viscosity Prediction and Uncertainty Quantification with Bayesian Optimized Deep Ensemble Liu, Y., Hu, R., & Balaprakash, P. Uncertainty Quantification of Deep Neural Network-Based Turbulence Model for Reactor Transient Analysis institutional repository document Ndum Ndum, Z., Tao, J., Ford, J., & Liu, Y. (2024). AutoFLUKA: A Large Language Model Based Framework for Automating Monte Carlo Simulations in FLUKA Abulawi, Z., Hu, R., Balaprakash, P., & Liu, Y. Bayesian optimized deep ensemble for uncertainty quantification of deep neural networks: a system safety case study on sodium fast reactor thermal stratification modeling report Liu, Y., Hu, R., Dai, D., Balaprakash, P., & Obabko, A. Machine Learning Assisted Safety Modeling and Analysis of Advanced Reactors
teaching activities NUEN302 Intro To Nuen Ii Instructor NUEN489 Sptp: Deep Learning For Eng Ap Instructor NUEN689 Sptp: Deep Learning - Eng Apps Instructor NUEN689 Sptp: Deep Learning For Engine Instructor NUEN691 Research Instructor
awards and honors Distinguished Early Career Award, conferred by United States Department of Energy - (Washington D.C., District of Columbia, United States), 2024
