PNNL

Yucheng Fu received his PhD in mechanical engineering from Virginia Tech, and his BS in theoretical math from Fudan University. His research focus includes thermal hydraulics, multiphase flow, multiscale and multiphysics modeling, computational energy storage, and data analysis. He has had the honor of publishing more than 20 journal articles with colleagues since 2016 and has reviewed 70 manuscripts for over 20 journals. In 2020, he was invited to serve on the reviewer board for Symmetry and Big Data and Cognitive Computing. His frequent collaborators come from Pacific Northwest National Laboratory (PNNL), along with Los Alamos National Laboratory and Lawrence Livermore National Laboratory, as well as the National Energy Technology Laboratory, The University of Texas at Austin, West Virginia University, and Virginia Tech. 

• Fluid mechanics and multiscale model for complex systems
• Advanced data analytics and scientific machine learning
• Energy storage modeling 
• Multiphase flow and thermal hydraulics
• Image processing and pattern recognition

• PhD in mechanical engineering, Virginia Tech
• BS in theoretical mathematics, Fudan University

• Institute of Electrical and Electronics Engineers
• American Chemical Society
• Scientific Reports, Editorial Board Member

• Best Publication Award, Nuclear Sciences Division, PNNL, 2022
• Best Publication Award, Energy Processes and Materials Division, PNNL, 2022
• Outstanding Performance Award, PNNL, 2022
• Best Paper Award, International Topical Meeting on the Advances in Thermal Hydraulics, 2018
• Thermal Hydraulics Division Travel Award, American Nuclear Society, 2015
• Fudan University Scholarship, 2010 – 2012

• Zeng C., S. Kim, Y. Chen, Y. Fu, J. Bao, Z. Xu, W. Wang. “In situ electroanalytical technique to characterize kinetics for redox flow battery.” iEdison No. 0685901-22-0098. IPID: 32493.

2024

• Fu Y., A.A. Howard, C. Zeng, Y. Chen, P. Gao, and P. Stinis. 2024. "Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance." ACS Energy Letters 9, no. 6:2767-2774. PNNL-SA-192565. doi:10.1021/acsenergylett.4c00493
• Howard A.A., Y. Fu, and P. Stinis. 2024. "A multifidelity approach to continual learning for physical systems." Machine Learning: Science and Technology 5, no. 2:Art No. 25042. PNNL-SA-198022. doi:10.1088/2632-2153/ad45b2

2023

• Chen W., Y. Fu, and P. Stinis. 2023. "Physics-informed machine learning of redox flow battery based on a two-dimensional unit cell model." Journal of Power Sources 584. PNNL-SA-185779. doi:10.1016/j.jpowsour.2023.233548
• Frazier W.E., L. Li, K. Choi, Y. Fu, Z. Xu, V.V. Joshi, and A. Soulami. 2023. "Microstructure-process relationships in monolithic U-10Mo fuel foil single-pass rolling: A parametric simulation study." Journal of Nuclear Materials 576, no. 17: Art. NO. 154271. PNNL-SA-170389. doi:10.1016/j.jnucmat.2023.154271
• Fu Y., J. Bao, C. Zeng, Y. Chen, Z. Xu, S. Kim, and W. Wang. 2023. "A Three-Dimensional Pore-scale Model for Redox Flow Battery Electrode Design Analysis." Journal of Power Sources 556. PNNL-SA-175492. doi:10.1016/j.jpowsour.2022.232329
• Fu Y., R.K. Singh, S. Feng, J. Liu, J. Xiao, J. Bao, and Z. Xu, et al. 2023. "Understanding of Low-Porosity Sulfur Electrode for High-Energy Lithium-Sulfur Batteries." Advanced Energy Materials 13, no. 13:2203386. PNNL-SA-178343. doi:10.1002/aenm.202203386
• Jiang W., L. Kovarik, K. Kruska, Y. Fu, Z. Hu, L. Shao, and W. Setyawan. 2023. "Behavior and properties of helium cavities in ductile-phase-toughened tungsten irradiated with He+ ions at an elevated temperature." Materialia 29. PNNL-SA-182610. doi:10.1016/j.mtla.2023.101789

2022

• Bartoldson B., R. Wang, Y. Fu, D. Widemann, S. Nguyen, J. Bao, and Z. Xu, et al. 2022. "Latent Space Simulation for Carbon Capture Design Optimization." In Proceedings of the 36th AAAI Conference on Artificial Intelligence, February 22- March 1, 2022, Virtual, Online, 36, 12447-12453. Palo Alto, California: AAAI Press. PNNL-SA-166438. doi:10.1609/aaai.v36i11.21511
• Feng S., R.K. Singh, Z. Li, Y. Wang, Y. Fu, J. Bao, and Z. Xu, et al. 2022. "Low-Tortuous and Dense Single-Particle-Layer Electrode for High-Energy Lithium-Sulfur Batteries." Energy & Environmental Science 15, no. 9:3842-3853. PNNL-SA-161239. doi:10.1039/D2EE01442D
• Fu Y., J. Bao, R.K. Singh, R.F. Zheng, C. Anderson-Cook, S. Bhat, and Z. Xu. 2022. "The Influence of Random Packed Column Parameters on the Liquid holdup and Interfacial Area." AIChE Journal 68, no. 8:e17691. PNNL-SA-160943. doi:10.1002/aic.17691
• Fu Y., W.E. Frazier, K. Choi, L. Li, Z. Xu, V.V. Joshi, and A. Soulami. 2022. "Prediction of Grain Structure after Thermomechanical Processing of U-10Mo Alloy using Sensitivity Analysis and Machine Learning Surrogate Model." Scientific Reports 12. PNNL-SA-170738. doi:10.1038/s41598-022-14731-8
• He Q., Y. Fu, P. Stinis, and A.M. Tartakovsky. 2022. "Enhanced physics-constrained deep neural networks for modeling vanadium redox flow battery." Journal of Power Sources 542. PNNL-SA-170353. doi:10.1016/j.jpowsour.2022.231807
• Singh R.K., Y. Fu, C. Zeng, D.T. Nguyen, P. Roy, J. Bao, and Z. Xu, et al. 2022. "Hydrodynamics of countercurrent flow in an additive manufactured column with triply periodic minimal surfaces for carbon dioxide capture." Chemical Engineering Journal 450, no. 2:138124. PNNL-SA-171812. doi:10.1016/j.cej.2022.138124
• Zeng C., S. Kim, Y. Chen, Y. Fu, J. Bao, Z. Xu, and W. Wang. 2022. "Characterization of electrochemical behavior for aqueous organic redox flow batteries." Journal of Electrochemical Society 169, no. 12: Art. No. 120527. PNNL-SA-178207. doi:10.1149/1945-7111/acadad
• Zeng C., Y. Fu, R.K. Singh, J. Bao, and Z. Xu. 2022. "Differentiation of static and dynamic interfacial area in the structured packed column." Chemical Engineering Science 260. PNNL-SA-165106. doi:10.1016/j.ces.2022.117877

2020

• Fu Y., J. Bao, C. Wang, R.K. Singh, and Z. Xu. 2020. CFD Study of Countercurrent Flow in Triply Periodic Minimal Surfaces with CO2BOL Solvent. PNNL-29590. Richland, WA: Pacific Northwest National Laboratory. doi:10.2172/1691506 
• Fu Y., J. Bao, C. Wang, R.K. Singh, D. Barpaga, R.F. Zheng, and Z. Xu, et al. 2020. Absorber Column CFD model validation against PNNL’s device-scale absorber column on the LCFS unit. PNNL-29828. Richland, WA: Pacific Northwest National Laboratory. doi:10.2172/1691502
• Fu Y., J. Bao, R.K. Singh, C. Wang, and Z. Xu. 2020.  "Investigation of Countercurrent Flow Profile and Liquid Holdup in Random Packed Column with Local CFD Data." Chemical Engineering Science 221. PNNL-SA-148356. doi:10.1016/j.ces.2020.115693
• Singh R.K., J. Bao, C. Wang, Y. Fu, and Z. Xu. 2020. "Hydrodynamics of countercurrent flows in a structured packed column: effects of initial wetting and dynamic contact angle." Chemical Engineering Journal 398. PNNL-SA-149254. doi:10.1016/j.cej.2020.125548