Production and measurement of fission product noble gases

Goodwin, Matthew A.; Bell, Steven; Britton, R.; Davies, A. V.; Abilama, Marc; Collins, S.M.; Shearman, R.; Regan, P.H.

doi:10.1016/j.jenvrad.2021.106733

Cited by 2 publications

(3 citation statements)

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“…A simple MATLAB code was written to make a polynomial regression and the statistical indicators for every regression, ensuring that the model fits the data or the goodness of regression. These statistical indicators are root mean squared error (RMSE) as shown in Eq (2) and R-squared (R 2 ) as shown in Eq (3). RMSE tells us the typical error between the Y Eq value made by the regression code and Y i value.…”

Section: Methodsmentioning

confidence: 99%

“…Many publications have shown that most of these bubbles are a group of non-reactive fission gases (xenon and krypton) emitted during the operation or shutdown of the reactor and are related to the level of burnup. Therefore, researchers have been interested in studying the growth of these gas bubbles resulting from fission within different types of nuclear fuel [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

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Accurate prediction of gaseous isotopes Xe and Kr concentrations from the burnup of nuclear fuel using simple regression algorithm

et al. 2023

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Mathematical techniques for modeling and simulating dangerous or complex systems, such as nuclear technology systems, often require high-performance computing to process and analyze available data. In this paper, simple and quick method to support studies and research related to nuclear fuel is presented. This reasonably simple method helps to predict different concentrations of actinides and fission products in nuclear fuels without the need for expensive specialized programs and highly-trained researchers. The great importance of this approach is the speed of predicting the components of nuclear fuel concentrations, which in turn leads to quick decision-making, such as the possibility of operating fuel at higher burnup values, predicting the amount of gases resulting from nuclear fission (which may accumulate and cause problems in nuclear fuel such as volume swells), and other important decisions in nuclear fuel technology. The predicted equations have been generalized for higher values of burnup and compared with comparable results from MCNP codes. The equations deduced in calculating the different concentrations of xenon and krypton isotopes resulting from fission in burnup of nuclear fuel showed very precise results with discrepancies (magnitude of an error between the data points and the corresponding predicted ones) less than 2%. The suggested method offers a great advantage for researchers, which are the use one of any simple or common computational programs available to most researchers and do not need much experience to deal with, such as MATLAB, Excel that are easy to use for regression analyses. In this paper, the advantages of the proposed method are explained along with the limitations of its use.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accurate prediction of gaseous isotopes Xe and Kr concentrations from the burnup of nuclear fuel using simple regression algorithm

et al. 2023

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“…However, radioactive waste is an important issue that must be considered in the context of the sustainability of nuclear power. "Fluid nuclear wastes, like liquid or gaseous wastes, can easily mix into water or air, which humans can easily intake during their lives [2]. In particular, gaseous radioactive waste contains a large proportion of inert gases such as Xe and Kr, which are of great value in the semiconductor and biomedical industries [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Grand Canonical Monte Carlo Simulation with MOF-303 and Metal-doped MOF-303

Ahn,

Kim,

Chang

2024

Preprint

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This study investigates the factors that enhance the selective adsorption performance of Xe and Kr in Metal Organic Frameworks (MOFs) using Grand Canonical Monte Carlo simulation. Simulations were conducted with MOFs such as SBMOF-1, UiO-66, and MOF-303, which have large pores capable of trapping Xe and Kr inside their structures. In the case of MOF-303, doping with copper increased adsorption and selectivity performance. To further investigate the effect of different doping metals on MOF-303, additional atoms such as silver and gold were used in simulations, as they belong to the same group in the periodic table as copper. The simulation results showed that Cu-doped MOF-303 exhibited a high Xe adsorption capacity per unit mass. However, Ag-doped MOF-303 demonstrated better adsorption performance per unit cell than Cu-doped MOF-303 due to larger Van der Waals interaction energy with Xe when Ag was doped. Additionally, Ag-doped MOF-303 showed better adsorption than Au-doped MOF-303 because Ag-doped MOF-303 has more pores suitable for Xe and Kr adsorption than Au-doped MOF-303. The simulation results indicate that when different metals are doped into the MOF structure, higher adsorption performance is achieved with metals that exhibit stronger Van der Waals interaction energy with the adsorbate and when the MOF contains more pores larger than the adsorbate atoms.

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Production and measurement of fission product noble gases

Cited by 2 publications

References 20 publications

Accurate prediction of gaseous isotopes Xe and Kr concentrations from the burnup of nuclear fuel using simple regression algorithm

Accurate prediction of gaseous isotopes Xe and Kr concentrations from the burnup of nuclear fuel using simple regression algorithm

Grand Canonical Monte Carlo Simulation with MOF-303 and Metal-doped MOF-303

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