Hydro-chemo-mechanical modelling of tunnels in sulfated rocks

Ramon, A.; Alonso, Eduardo E.; Olivella, S.

doi:10.1680/jgeot.sip17.p.252

Cited by 18 publications

(30 citation statements)

References 34 publications

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“…The inversely determined parameter b of 2.5 is similar to the estimate by Ramon et al () and yields a bulking coefficient γ of 0.15 ± 0.11 (For further details on γ , refer to the supporting information). Thus, according to the theoretical basis of γ a large part of the gypsum crystals precipitates in already existing cavities and therefore does not cause significant deformation.…”

Section: Resultssupporting

confidence: 81%

“…Consequently, the solution volume V in contact with the mineral equals the immobile porosity ( im ) instead of the total porosity. It should be noted that this assumption is different from the model of Ramon et al (2017), who assumed that gypsum crystal growth occurs solely in fractures. The focus of their study, however, was on mechanical considerations such as fracture opening.…”

Section: Geochemical Reactionsmentioning

confidence: 90%

“…In order to relate stress to strain and derive the vertical deformation from the mass of precipitated gypsum crystals determined by the coupled flow, transport and reaction simulations in the swelling zone, a bulking (swelling) coefficient was used, following the work by Oldecop and Alonso (), and Ramon et al ():

\frac{normald ϵ_{i}}{normald t} = - \frac{γ_{i}}{ρ_{G}} \frac{normald m_{G}}{normald t},

where ϵ i is the deformation (strain) and γ i the bulking coefficient in the i direction, respectively, ρ G is the gypsum density (kg/m 3 ) and m G the mass of precipitated gypsum crystals (kg). The geomechanical stress ‐ strain relationship is calculated posterior to the completed MODFLOW and PHT3D model simulation using a Python script.…”

Section: Conceptual and Numerical Model Developmentmentioning

confidence: 99%

“…The effect of stress (expressed by γ ) is approximated by an exponential decay function:

γ_{i} = γ_{\max} e^{- b σ_{i}^{'}},

where γ max is the bulking coefficient for zero pressure stress which was set to 2 as in Ramon et al (), b is a model fitting parameter estimated during the inversion process, and

σ_{i}^{'}

is the effective stress.…”

Section: Conceptual and Numerical Model Developmentmentioning

confidence: 99%

Section: Swelling Modelmentioning

confidence: 99%

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Reactive Transport Modeling of Swelling Processes in Clay‐sulfate Rocks

Schweizer

Prommer

Blum

et al. 2018

Water Resources Research

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Swelling of clay‐sulfate rocks often causes large problems in geotechnical applications such as tunneling. The primary mechanism inducing the increase in rock volume is the chemical transformation of anhydrite to gypsum, which is triggered by the ingress of groundwater. In the present study, a novel conceptual and numerical modeling approach is developed that emphasizes the effect of groundwater flow in conjunction with the associated availability of water and changing geochemical conditions on the chemical transformation of anhydrite to gypsum. A reactive transport model was developed and hydraulic, reactive, and solute transport as well as mechanical model parameters were estimated through an inversion process, constrained by geodetic ground heave measurements from a study site in Staufen, Germany. The conceptual model of the swelling process was implemented numerically through a dual‐domain modeling approach, whereby the mobile domain accounts for solute transport along discontinuities, and the immobile reactive domain represents the matrix. A mass transfer process accounts for diffusive and/or capillary water transport into the matrix, where the rate‐limited transformation of anhydrite to gypsum takes place. The model calculates heave at the land surface depending on water inflow, the transformation of anhydrite into gypsum and the local stress conditions exerted by overburden pressure. The results show that the proposed reactive transport modeling approach is suitable to quantify the observed swelling‐induced heave at the study site with a plausible parameterization. The study also highlights that diffusion is a decisive factor for the effective rate of anhydrite dissolution and, therefore, the overall chemical transformation process.

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Section: Resultssupporting

confidence: 81%

Section: Geochemical Reactionsmentioning

confidence: 90%

\frac{normald ϵ_{i}}{normald t} = - \frac{γ_{i}}{ρ_{G}} \frac{normald m_{G}}{normald t},

Section: Conceptual and Numerical Model Developmentmentioning

confidence: 99%

“…The effect of stress (expressed by γ ) is approximated by an exponential decay function:

γ_{i} = γ_{\max} e^{- b σ_{i}^{'}},

where γ max is the bulking coefficient for zero pressure stress which was set to 2 as in Ramon et al (), b is a model fitting parameter estimated during the inversion process, and