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Intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods

Diffusion is a dominant mechanism regulating the transport of released nuclides. The through-diffusion method is typically applied to determine the diffusion coefficients (D). Depending on the design of the experiment, the concentrations in the source term [i.e., inlet reservoir (IR)] or the end ter...

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Autores principales: Chen, Chih-Lung, Wang, Tsing-Hai, Lee, Ching-Hor, Teng, Shi-Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4514585/
https://www.ncbi.nlm.nih.gov/pubmed/26224970
http://dx.doi.org/10.1007/s10967-014-2974-8
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author Chen, Chih-Lung
Wang, Tsing-Hai
Lee, Ching-Hor
Teng, Shi-Ping
author_facet Chen, Chih-Lung
Wang, Tsing-Hai
Lee, Ching-Hor
Teng, Shi-Ping
author_sort Chen, Chih-Lung
collection PubMed
description Diffusion is a dominant mechanism regulating the transport of released nuclides. The through-diffusion method is typically applied to determine the diffusion coefficients (D). Depending on the design of the experiment, the concentrations in the source term [i.e., inlet reservoir (IR)] or the end term [i.e., outlet reservoir (OR)] can be fixed or vary. The combinations involve four distinct models (i.e., the CC–CC model, CC–VC model, VC–CC model, and the VC–VC model). Studies discussing the VC–CC model are scant. An analytical method considering the decay effect is required to accurately interpret the radioactive nuclide diffusion experiment results. Therefore, we developed a CC–CC model and a CC–VC model with a decay effect and the simplified formulas of these two models to determine the diffusion coefficient (i.e., the CC–CC method and CC–VC method). We also proposed two simplified methods using the VC–VC model to determine the diffusion coefficient straightforwardly based upon the concentration variation in IR and OR. More importantly, the best advantage of proposed method over others is that one can derive three diffusion coefficients based on one run of experiment. In addition, applying our CC–VC method to those data reported from Radiochemica Acta 96:111–117, 2008; and J Contam Hydrol 35:55–65, 1998, derived comparable diffusion coefficient lying in the identical order of magnitude. Furthermore, we proposed a formula to determine the conceptual critical time (Tc), which is particularly beneficial for the selection of using CC–VC or VC–VC method. Based on our proposed method, it becomes possible to calculate diffusion coefficient from a through-diffusion experiment in a shorter period of time.
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spelling pubmed-45145852015-07-27 Intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods Chen, Chih-Lung Wang, Tsing-Hai Lee, Ching-Hor Teng, Shi-Ping J Radioanal Nucl Chem Article Diffusion is a dominant mechanism regulating the transport of released nuclides. The through-diffusion method is typically applied to determine the diffusion coefficients (D). Depending on the design of the experiment, the concentrations in the source term [i.e., inlet reservoir (IR)] or the end term [i.e., outlet reservoir (OR)] can be fixed or vary. The combinations involve four distinct models (i.e., the CC–CC model, CC–VC model, VC–CC model, and the VC–VC model). Studies discussing the VC–CC model are scant. An analytical method considering the decay effect is required to accurately interpret the radioactive nuclide diffusion experiment results. Therefore, we developed a CC–CC model and a CC–VC model with a decay effect and the simplified formulas of these two models to determine the diffusion coefficient (i.e., the CC–CC method and CC–VC method). We also proposed two simplified methods using the VC–VC model to determine the diffusion coefficient straightforwardly based upon the concentration variation in IR and OR. More importantly, the best advantage of proposed method over others is that one can derive three diffusion coefficients based on one run of experiment. In addition, applying our CC–VC method to those data reported from Radiochemica Acta 96:111–117, 2008; and J Contam Hydrol 35:55–65, 1998, derived comparable diffusion coefficient lying in the identical order of magnitude. Furthermore, we proposed a formula to determine the conceptual critical time (Tc), which is particularly beneficial for the selection of using CC–VC or VC–VC method. Based on our proposed method, it becomes possible to calculate diffusion coefficient from a through-diffusion experiment in a shorter period of time. Springer Netherlands 2014-02-02 2014 /pmc/articles/PMC4514585/ /pubmed/26224970 http://dx.doi.org/10.1007/s10967-014-2974-8 Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/2.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Chen, Chih-Lung
Wang, Tsing-Hai
Lee, Ching-Hor
Teng, Shi-Ping
Intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods
title Intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods
title_full Intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods
title_fullStr Intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods
title_full_unstemmed Intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods
title_short Intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods
title_sort intercomparison of diffusion coefficient derived from the through-diffusion experiment using different numerical methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4514585/
https://www.ncbi.nlm.nih.gov/pubmed/26224970
http://dx.doi.org/10.1007/s10967-014-2974-8
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