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LLNL, Ampera partner to develop thorium-based TRISO fuel
Lawrence Livermore National Laboratory has formed a strategic partnership with Ampera to develop the company’s nuclear fuel concept through a project named THUNDER, for Thorium Unimodal Droplet Ejection for Reactors.
The focus of THUNDER is fabricating TRISO made with kernels of thorium rather than the usual uranium. LLNL and Ampera will evaluate and optimize liquid metal–jetting technology to produce highly uniform, spherical kernels of thorium-232 for later processing into TRISO fuel.
Greg J. Evans
Nuclear Technology | Volume 116 | Number 3 | December 1996 | Pages 293-305
Technical Paper | Nuclear Reactor Safety | doi.org/10.13182/NT96-A35285
Articles are hosted by Taylor and Francis Online.
Any release of radioiodine to the environment following a reactor accident depends to a large extent on its volatility within a containment structure. A common measure of iodine volatility is the water-air volumetric iodine partition coefficient (IPC), defined as the ratio of aqueous to airborne radioiodine concentrations. The impact of pH and total iodine concentration on volatility is evaluated through experiments and modeling to establish the relevant trends and improve the understanding of the underlying mechanisms. The model consists of kinetic expressions for 125 reactions. The IPC is evaluated experimentally by irradiating, at 0.25 kGy/h and 25°C, 131I-labeled CsI solutions ranging in concentration from 10−8 to 10−4 Mand in pH from 3 to 12. Both the experiments and the modeling indicate that under acidic conditions, the IPC for 10−6 M solutions is substantially higher than that for 10−5 M solutions. The predicted dependence of the IPC on pH for acidic 10−5 M solutions is in good agreement with that observed experimentally. However, substantial divergence occurred for more dilute solutions and for basic pH conditions. It is speculated that under these conditions, atomic iodine may contribute substantially to the overall volatility; adding atomic iodine volatility to the model is found to greatly improve the agreement.