A machine learning approach to thermal conductivity modeling: A case study on irradiated uranium-molybdenum nuclear fuels EJ Kautz, AR Hagen, JM Johns, DE Burkes Computational Materials Science 161, 107-118, 2019 | 27 | 2019 |
GEANT4 CALCULATIONS OF NEUTRON DOSE IN RADIATION PROTECTION USING A HOMOGENEOUS PHANTOM AND A CHINESE HYBRID MALE PHANTOM DC Changran Geng, Xiaobin Tang, Fada Guan, Jesse Johns, Latha Vasudevan ... Radiation Protection Dosimetry, 2015 | 27* | 2015 |
Development of multilayer perceptron networks for isothermal time temperature transformation prediction of U-Mo-X alloys JM Johns, D Burkes Journal of Nuclear Materials 490, 155-166, 2017 | 18 | 2017 |
Critical processes and parameters in the development of accident tolerant fuels drop-in capsule irradiation tests KE Barrett, KD Ellis, CR Glass, GA Roth, MP Teague, J Johns Nuclear Engineering and Design 294, 38-51, 2015 | 17 | 2015 |
A Monte Carlo-based radiation safety assessment for astronauts in an environment with confined magnetic field shielding C Geng, X Tang, C Gong, F Guan, J Johns, D Shu, D Chen Journal of Radiological Protection 35 (4), 777, 2015 | 16 | 2015 |
Calculations of S values and effective dose for the radioiodine carrier and surrounding individuals based on Chinese hybrid reference phantoms using the Monte Carlo technique C Geng, X Tang, W Qian, F Guan, J Johns, H Yu, C Gong, D Shu, D Chen Journal of Radiological Protection 35 (3), 707, 2015 | 5 | 2015 |
A new approach to calculating fuel temperature in TRIGA Mark I research reactors JM Johns, WD Reece International Conference on Nuclear Engineering 44977, 631-637, 2012 | 4 | 2012 |
High Temperature super-critieal CO (2)-eooled Integrated Multi-Modular Thermal Reactor P Tsvetkov, S Chirayath, J Ragusa, S Mcdeavitt, C Gariazzo, J Johns, ... Transactions of the American Nuclear Society 105, 1117-1119, 2011 | 4 | 2011 |
Multi-modal geolocation estimation using deep neural networks JM Johns, J Rounds, MJ Henry arXiv preprint arXiv:1712.09458, 2017 | 3 | 2017 |
Subchannel analysis of fuel temperature and departure of nucleate boiling of TRIGA Mark I J Johns, WD Reece Annals of Nuclear Energy 75, 331-339, 2015 | 3 | 2015 |
GaN nuclear batteries: radiation modeling for the accelerated contact exposure of betavoltaics L Hubbard, C Cowles, A Prichard, G Sevigny, J Johns, DC Morales, ... MRS Advances 5 (27-28), 1483-1489, 2020 | 2 | 2020 |
Accident Tolerant Fuel Analysis C Smith, H Chichester, J Johns, M Teague, M Tonks, R Youngblood Idaho National Lab.(INL), Idaho Falls, ID (United States), 2014 | 2 | 2014 |
Autonomous corium reactor for terrestrial applications JM Johns, PV Tsvetkov International Conference on Nuclear Engineering 44953, 667-680, 2012 | 2 | 2012 |
Estimation of Plutonium-240 Mass in Waste Tanks Using Ultra-Sensitive Detection of Radioactive Xenon Isotopes from Spontaneous Fission TW Bowyer, CJ Gesh, DA Haas, JC Hayes, JM Johns, CD Lukins, ... Pacific Northwest National Lab.(PNNL), Richland, WA (United States), 2017 | 1 | 2017 |
Dynamic Simulation of Nuclear Reactors Experiencing High Rates of Deformation J Johns, V Valtavirtaǂ, R LenardX | 1 | 2015 |
3D in-core monitoring in advanced reactor environments PV Tsvetkov, SM Bragg-Sitton, JM Johns, MP Johnson Transactions of the American Nuclear Society 106, 626-627, 2012 | 1 | 2012 |
Detection of Marine Borne Radioactive Sources Report JM Johns, BC Archambault, BE Bernacki, KC Gorecke, TW Hossbach, ... Pacific Northwest National Laboratory (PNNL), Richland, WA (United States), 2022 | | 2022 |
Neural Interactive Machine Learning: Final Report: Compilation of presentation material JD Suter, JV Cree, JM Johns, G Longoni Pacific Northwest National Laboratory (PNNL), Richland, WA (United States), 2021 | | 2021 |
Neural Interactive Machine Learning JD Suter, JV Cree, JM Johns, G Longoni | | 2021 |
Betavoltaic Power Contacts: Accelerated Aging L Hubbard, C Cowles, G Sevigny, J Johns, E Fuller, L Kovarik, ... Materials Research Society Fall Conference 2020, 2020 | | 2020 |