| Data-driven modeling for boiling heat transfer: using deep neural networks and high-fidelity simulation results Y Liu, N Dinh, Y Sato, B Niceno Applied Thermal Engineering 144, 305-320, 2018 | 133 | 2018 |
| Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments Y Liu, D Wang, X Sun, N Dinh, R Hu Reliability Engineering & System Safety 212, 107636, 2021 | 53 | 2021 |
| Uncertainty quantification of two-phase flow and boiling heat transfer simulations through a data-driven modular Bayesian approach Y Liu, NT Dinh, RC Smith, X Sun International Journal of Heat and Mass Transfer 138, 1096-1116, 2019 | 45 | 2019 |
| Validation and uncertainty quantification of multiphase-CFD solvers: A data-driven Bayesian framework supported by high-resolution experiments Y Liu, X Sun, NT Dinh Nuclear Engineering and Design 354, 110200, 2019 | 39 | 2019 |
| Validation and uncertainty quantification for wall boiling closure relations in multiphase-CFD solver Y Liu, N Dinh Nuclear Science and Engineering 193 (1-2), 81-99, 2019 | 24 | 2019 |
| Data-driven modeling of coarse mesh turbulence for reactor transient analysis using convolutional recurrent neural networks Y Liu, R Hu, A Kraus, P Balaprakash, A Obabko Nuclear Engineering and Design 390, 111716, 2022 | 23 | 2022 |
| SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability Y Liu, R Hu, L Zou, D Nunez Nuclear Engineering and Design 400, 112059, 2022 | 17 | 2022 |
| Experimental study of post-CHF heat transfer in a vertical tubular test section Q Liu, H Sun, Y Liu, J Kelly, X Sun International Journal of Heat and Mass Transfer, 120697, 2021 | 15 | 2021 |
| Evaluation of public dose from FHR tritium release with consideration of meteorological uncertainties X Wu, Y Liu, K Kearfott, X Sun Science of The Total Environment 709, 136085, 2020 | 15 | 2020 |
| Uncertainty quantification of deep neural network-based turbulence model for reactor transient analysis Y Liu, R Hu, P Balaprakash Verification and Validation 84782, V001T11A001, 2021 | 14 | 2021 |
| Uncertainty analysis of PIV measurements in bubbly flows considering sampling and bubble effects with ray optics modeling Y Liu, C Wang, Y Qian, X Sun Nuclear Engineering and Design 364, 110677, 2020 | 11 | 2020 |
| Flow boiling in tubes Y Liu, N Dinh Handbook of Thermal Science and Engineering, Springer International …, 2017 | 10 | 2017 |
| Benchmarking FFTF LOFWOS Test# 13 using SAM code: Baseline model development and uncertainty quantification Y Liu, T Mui, Z Xie, R Hu Annals of Nuclear Energy 192, 110010, 2023 | 9 | 2023 |
| A hybrid porous model for full reactor core scale CFD investigation of a prismatic HTGR C Wang, Y Liu, X Sun, P Sabharwall Annals of Nuclear Energy 151, 107916, 2021 | 8 | 2021 |
| Coarse Mesh Turbulence Prediction for Reactor Transient Simulations Using Densely Connected Convolutional Networks Y Liu, R Hu, P Balaprakash, A Brunett, A Obabko 2020 ANS Virtual Winter Meeting, 2020 | 8 | 2020 |
| Eulerian Two-Fluid RANS-Based CFD Simulations of a Helical Coil Steam Generator Boiling Tube WD Pointer, Y Liu The 17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics …, 2017 | 8 | 2017 |
| Benchmark Modeling and Simulation of the FFTF LOFWOS Test# 13 using SAM Y Liu, R Hu Argonne National Lab.(ANL), Argonne, IL (United States), 2020 | 7 | 2020 |
| Evaluation of CFD Methods for Simulation of Two-Phase Boiling Flow Phenomena in a Helical Coil Steam Generator WD Pointer, D Shaver, Y Liu, P Vegendla, A Tentner Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States), 2016 | 6 | 2016 |
| Analysis of heat transfer under high heat flux nucleate boiling conditions Y Liu, N Dinh Kerntechnik 81 (3), 308-314, 2016 | 6 | 2016 |
| Validation and uncertainty quantification of DNB closures in MCFD solver using inverse Bayesian inference method Y Liu, N Dinh, Y Sato, N Bojan Proc. ANS Best Estimate Plus Uncertainty International Conference, Real …, 2018 | 5 | 2018 |
Nam Dinh (Truc-Nam Dinh)North Carolina State University (also, Royal Inst. Tech.-KTH; UC-Santa Barbara, Idaho Nat. Lab.)Potvrđena adresa e-pošte na ncsu.edu
