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Journal Articles Scientific Reports Year : 2022

Uncertainty propagation in pore water chemical composition calculation using surrogate models

Abstract

Performance assessment in deep geological nuclear waste repository systems necessitates an extended knowledge of the pore water chemical conditions prevailing in host-rock formations. In the last two decades, important progress has been made in the experimental characterization and thermodynamic modeling of pore water speciation, but the influence of experimental artifacts and uncertainties of thermodynamic input parameters are seldom evaluated. In this respect, we conducted an uncertainty propagation study in a reference geochemical model describing the pore water chemistry of the Callovian-Oxfordian clay formation. Nineteen model input parameters were perturbed, including those associated to experimental characterization (leached anions, exchanged cations, cation exchange selectivity coefficients) and those associated to generic thermodynamic databases (solubilities). A set of 13 quantities of interest were studied by the use of polynomial chaos expansions built non-intrusively with a least-squares forward stepwise regression approach. Training and validation sets of simulations were carried out using the geochemical speciation code PHREEQC. The statistical results explored the marginal distribution of each quantity of interest, their bivariate correlations as well as their global sensitivity indices. The influence of the assumed distributions for input parameters uncertainties was evaluated by considering two parametric domain sizes.

Domains

Earth Sciences
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Dates and versions

hal-03779374 , version 1 (16-09-2022)

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Cite

Pierre Sochala, Christophe Chiaberge, Francis Claret, Christophe Tournassat. Uncertainty propagation in pore water chemical composition calculation using surrogate models. Scientific Reports, 2022, 12 (1), pp.15077. ⟨10.1038/s41598-022-18411-5⟩. ⟨hal-03779374⟩
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