Wen Jiang

Assistant Professor of Nuclear Engineering, Joint Faculty Appointment with INL

  • 919-515-5877
  • Burlington Laboratory 2156

Dr. Wen Jiang is an Assistant Professor of Nuclear Engineering at the NCSU and holds a joint faculty appointment with INL. Prior to coming to the NCSU, Dr. Jiang was a computational scientist in the Computational Mechanics and Materials Department at the Idaho National Laboratory. He joined INL in 2015 after Ph.D from the Duke University to work on computational methods for nuclear material modeling and multi-physics simulation. Dr. Jiang is a key developer for the BISON nuclear fuel simulation code which won R&D 100 Award in 2022, and he is leading developer for additive manufacturing simulation code in MOOSE Application Library for Advanced Manufacturing Utilities (MALAMUTE). He currently leads the development of multi-scale TRISO particle fuels modeling for DOE’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS). He is also involved in DOE’s Advanced Gas Reactor (AGR) Fuel Development and Qualification Program where he performs TRISO fuel performance calculations with BISON in support of analysis of the AGR irradiation tests.

Education

B.S. 2007

Aeronautical Science and Engineering

Beijing University of Aeronautics and Astronautics

M.S. 2009

Aeronautical Science and Engineering

Beijing University of Aeronautics and Astronautics

Ph.D. 2015

Mechanical Engineering and Materials Science

Duke University

Publications

A mixed formulation of the plane-stress problem to facilitate reuse of constitutive models in finite-element programs
Chen, H., Jiang, W., & Spencer, B. W. (2024), MECHANICS RESEARCH COMMUNICATIONS, 139. https://doi.org/10.1016/j.mechrescom.2024.104307
Fracture mechanics approach to TRISO fuel particle failure analysis
Recuero, A. M., Singh, G., & Jiang, W. (2024), JOURNAL OF NUCLEAR MATERIALS, 596. https://doi.org/10.1016/j.jnucmat.2024.155083
Versatile TRISO fuel particle modeling in Bison
Hales, J. D., & Jiangb, W. (2024), NUCLEAR ENGINEERING AND DESIGN, 428. https://doi.org/10.1016/j.nucengdes.2024.113515
A comparative study of two numerical approaches for solving Kim–Kim–Suzuki phase-field models
Bognarova, X., Jiang, W., Schwen, D., & Tonks, M. R. (2023), Computational Materials Science. https://doi.org/10.1016/j.commatsci.2023.112375
General Multifidelity Surrogate Models: Framework and Active-Learning Strategies for Efficient Rare Event Simulation
Chakroborty, P., Dhulipala, S. L. N., Che, Y., Jiang, W., Spencer, B. W., Hales, J. D., & Shields, M. D. (2023), Journal of Engineering Mechanics. https://doi.org/10.1061/JENMDT.EMENG-7111
MOOSE Stochastic Tools: A module for performing parallel, memory-efficient in situ stochastic simulations
Slaughter, A. E., Prince, Z. M., German, P., Halvic, I., Jiang, W., Spencer, B. W., … Gaston, D. R. (2023), SoftwareX. https://doi.org/10.1016/j.softx.2023.101345
Multi-scale fission product release model with comparison to AGR data
Simon, P.-C., Aagesen, L., Jr., Bhave, C., Jiang, C., Jiang, W., Ke, J.-H., & Yang, L. (2023). , . https://doi.org/10.2172/2203700
TRISO fuel performance analysis: Uncertainty quantification toward optimization
Baghdasaryan, N., Jiang, W., Hales, J., Kozlowski, T., & Krajewska, Z. (2023), Nuclear Engineering and Design. https://doi.org/10.1016/j.nucengdes.2023.112401
A phase-field model of quasi-brittle fracture for pressurized cracks: Application to UO2 high-burnup microstructure fragmentation
Jiang, W., Hu, T., Aagesen, L. K., Biswas, S., & Gamble, K. A. (2022), Theoretical and Applied Fracture Mechanics. https://doi.org/10.1016/j.tafmec.2022.103348
A phase-field study of stainless-steel oxidation from high-temperature carbon dioxide exposure
Wu, X., Abdallah, I., Jiang, W., Ullberg, R. S., Phillpot, S. R., Couet, A., … Tonks, M. R. (2023), Computational Materials Science. https://doi.org/10.1016/j.commatsci.2022.111996

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