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November 20
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12:00 PM
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1:00 PM
Thursday, November 20
12:00 – 1:00pm
106 Engineering Research Building
Please contact office@neep.wisc.edu for assistance with remote participation.
Efficient Tritium Extractor Design Enabled by High-Fidelity Simulation
Tritium is the essential fuel in D-T fusion reactions, which underpin both inertial confinement and magnetic confinement fusion concepts. Given the extremely limited natural supply, in-situ breeding is the only viable pathway to sustain commercial fusion power. Liquid blankets containing ⁶Li, such as molten salts FLiBe and FLiNaK, are particularly promising because they enable both tritium breeding and efficient thermal management. Molten fluoride salts are especially attractive as coolants due to their excellent thermal and neutronic properties, as well as their inherently low tritium solubility. While significant research has been devoted to breeding mechanisms, tritium extraction remains relatively understudied, which creates a critical bottleneck in the D-T fuel cycle.
In this talk, I will present two ongoing efforts to design efficient tritium extractor concepts, i.e., both permeator against vacuum (PAV) and gas-liquid contactor (GLC), using high-fidelity simulations. I will demonstrate that advanced extractor design requires resolving a coupled multidimensional, multiphase transport problem. High-fidelity modeling provides detailed insights into local transport phenomena that are otherwise difficult to probe experimentally. With the added transport physics incorporated into existing CFD tools, we are well-positioned to perform refined parametric studies and optimize extractor geometries to advance tritium management strategies for fusion systems.
Guanyu Su is an Assistant Professor in the Department of Nuclear Engineering at the University of California, Berkeley. He earned his M.S. and Ph.D. in Nuclear Science and Engineering from MIT. At Berkeley, Dr. Su’s research focuses on addressing critical scientific and engineering challenges in nuclear thermal-hydraulics and clean energy systems. His interests span four main areas: (1) heat and mass transfer in high-temperature molten salt technologies, (2) advanced diagnostic tool development for fission and fusion systems, (3) high-temperature thermal storage for advanced energy systems, and (4) applications of machine learning in nuclear reactor simulation, experimentation, and maintenance. He also serves as the faculty lead for the Master of Engineering program in the Nuclear Engineering Department.