Transport in tight material enlightened by process tomography

Abstract. The analysis of fluid transport through tight barrier materials poses two major challenges: (i) Long equilibration periods require long minimum experiment durations, and (ii) the fluid transport frequently results in complex pattern formation. Measuring times that are too short may feign transport rates that are too low; intact homogeneous samples are often missing problematic features, e.g. fractures. Both issues are detected and analyzed by using process tomography techniques, thereby providing an improved understanding of transport processes in complex materials. We thus continuously develop and apply the positron emission tomography (PET) method for geomaterials (Kulenkampff et al., 2016). This is able to trace very low concentrations of β+-emitting radionuclides during their passage through drill cores of barrier material with reasonable resolution (1 mm) and over variable periods (hours to years). The method yields time-resolved quantitative tomographic images of the tracer concentration (e.g. https://doi.org/10.5281/zenodo.166509), in contrast to input-output experiments like common permeability measurements, diffusion cells or break-through curves. Our current research includes the analysis of diffusive transport in heterogeneous shales (sandy facies of the Opalinus Clay) (BMBF and HGF iCross project), the reactive flow in fracture-filling materials of crystalline rocks (Eurad FUTURE project) and transport in engineered barriers and the contact zone (Euratom Cebama, Eurad Magic, as well as MgO and Stroefun BMWi projects). The efforts combine flow field tomography, structural imaging and reactive transport modelling to improve process understanding and to provide a bridge from the molecular to the macroscopic scale. The benefits include: Insight into temporal stability and spatial heterogeneity of the observed transport process Parameterization of local velocity distribution and effective volume as well as comparability with pore-scale model simulations Ability to quantify multiple internal transport rates without the need to register the delayed output signal Transparent and palpable visualization of processes hidden in the opaque material The method requires specific constraints of the experimental setup (size, fluid pressure, temperature). Nevertheless, it provides unique insight into reactive transport processes observed in potential materials for nuclear waste management.

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A compositional formulation for multiphase multicomponent reactive transport modelling of highly coupled systems

10.5194/egusphere-egu2020-5615 ◽

2020 ◽

Author(s):

Nicolas Seigneur ◽

K. Ulrich Mayer

Keyword(s):

Water Resources ◽

Reactive Transport ◽

Transport Processes ◽

Coupled Systems ◽

Phase Flow ◽

Reactive Transport Modelling ◽

Two Phase ◽

Transport Modelling ◽

Geochemical Reactions ◽

Contaminant Hydrology

In certain reactive transport applications, strong coupling between geochemical reactions and hydrodynamics exists. Dissolution and precipitation of minerals, such as the conversion between gypsum and anhydrite [1] or the precipitation of nesquehonite during CO2 sequestration [2], as well as gas bubble formation [3] are geochemical processes which modify the multiphase flow dynamics, with direct feedback on reactive transport processes. In addition, heat generation induced by sulphide mineral oxidation can lead to significant increases in temperature [4], impacting flow, transport and geochemical reactions. In these instances, commonly used reactive transport modelling approaches, which rely on decoupling flow and reactive transport processes, have limitations. For density dependent or two-phase flow problems in the presence of a gas phase, the coupling between flow and reactive transport can be accounted for through a Picard iterative approach [3,5,6]. However, this approach is computationally expensive, involving the solution of nonlinear problems multiple times during each timestep, and convergence properties are often poor. More recently, a weak explicit coupling approach was developed to capture the impact of chemistry on flow by integrating water as a component and perform a volume balance calculation [7]. In the current work, a compositional approach is implemented into MIN3P-THCm, in which the flow variables (pressure, density) are expressed based on mass variables. Hence, this global implicit approach does not require solving the flow problem, but instead integrates groundwater flow processes directly into the reactive transport equations. We show that this approach yields very similar results to the commonly used approaches for single and two-phase flow. Finally, we show that, in highly coupled systems, not considering these coupled effects may lead to significant errors in simulating system evolution, highlighting the benefits of the newly developed approach.&#160;[1] Jowett, Cathles & Davis (1993). AAPG Bulletin,&#160;77(3), 402-413.[2] Harrison, Dipple, Power & Mayer (2015). Geochimica et cosmochimica Acta,&#160;148, 477-495.[3] Amos and Mayer (2006). Journal of contaminant hydrology, 87(1-2), 123-154.[4] Lefebvre, Hockley, Smolensky & G&#233;linas (2001). Journal of contaminant hydrology,&#160;52(1-4), 137-164.[5] Henderson, Mayer, Parker, & Al (2009).&#160;Journal of contaminant hydrology,&#160;106(3-4), 195-211.[6] Sin, Lagneau and Corvisier (2017). Advances in Water Resources, 100, 62-77.[7] Seigneur, Lagneau, Corvisier & Dauz&#232;res (2018). Advances in Water Resources 122, 355-366.

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Evaluation of Reactive Transport Processes in a Heterogeneous Porous Aquifer Within a Non-Parametric Numerical Stochastic Transport Modelling Framework Based on Sequential Indicator Simulation of Categorical Variables

geoENV I — Geostatistics for Environmental Applications - Quantitative Geology and Geostatistics ◽

10.1007/978-94-017-1675-8_13 ◽

1997 ◽

pp. 153-164 ◽

Cited By ~ 2

Author(s):

Thomas Ptak

Keyword(s):

Reactive Transport ◽

Transport Processes ◽

Categorical Variables ◽

Sequential Indicator Simulation ◽

Transport Modelling ◽

Modelling Framework ◽

Porous Aquifer ◽

Stochastic Transport ◽

Indicator Simulation ◽

Non Parametric

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Pore-Scale Modeling of Air–Water Two Phase Flow and Oxygen Transport in Gas Diffusion Layer of Proton Exchange Membrane Fuel Cell

Energies ◽

10.3390/en14133812 ◽

2021 ◽

Vol 14 (13) ◽

pp. 3812

Author(s):

Chongbo Zhou ◽

Lingyi Guo ◽

Li Chen ◽

Xin Tian ◽

Tiefeng He ◽

...

Keyword(s):

Liquid Water ◽

Reactive Transport ◽

Proton Exchange Membrane ◽

Water Saturation ◽

Gas Diffusion ◽

Transport Processes ◽

Proton Exchange ◽

Scale Model ◽

Pore Scale ◽

Two Phase

Understanding multiphase flow and gas transport occurring in electrodes is crucial for improving the performance of proton exchange membrane fuel cells. In the present study, a pore-scale model using the lattice Boltzmann method (LBM) was proposed to study the coupled processes of air–water two-phase flow and oxygen reactive transport processes in porous structures of the gas diffusion layer (GDL) and in fractures of the microscopic porous layer (MPL). Three-dimensional pore-scale numerical results show that the liquid water generation rate is gradually reduced as the oxygen consumption reaction proceeds, and the liquid water saturation in the GDL increases, thus the constant velocity inlet or pressure inlet condition cannot be maintained while the results showed that at t = 1,200,000 iterations after 2900 h running time, the local saturation at the GDL/MPL was about 0.7, and the maximum value was about 0.83, while the total saturation was 0.35. The current density reduced from 2.39 to 0.46 A cm-2. Effects of fracture number were also investigated, and the results showed that for the fracture numbers of 8, 12, 16, and 24, the breakthrough point number was 4, 3, 3, and 2, respectively. As the fracture number increased, the number of the water breakthrough points at the GDL/GC interface decreased, the liquid water saturation inside the GDL increased, the GDL/MPL interface was more seriously covered, and the current density decreased. The pore-scale model for the coupled multiphase reactive transport processes is helpful for understanding the mechanisms inside the porous electrodes of PEMFC.

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Probabilistic nucleation governs time, amount, and location of mineral precipitation and geometry evolution in the porous medium

Scientific Reports ◽

10.1038/s41598-021-95237-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Mohammad Nooraiepour ◽

Mohammad Masoudi ◽

Helge Hellevang

Keyword(s):

Porous Medium ◽

Reactive Transport ◽

Solid Phase ◽

Mutual Effect ◽

Transport Processes ◽

Primary Control ◽

Spatiotemporal Evolution ◽

Mineral Precipitation ◽

Phase Accumulation ◽

Insight Into

AbstractOne important unresolved question in reactive transport is how pore-scale processes can be upscaled and how predictions can be made on the mutual effect of chemical processes and fluid flow in the porous medium. It is paramount to predict the location of mineral precipitation besides their amount for understanding the fate of transport properties. However, current models and simulation approaches fail to predict precisely where crystals will nucleate and grow in the spatiotemporal domain. We present a new mathematical model for probabilistic mineral nucleation and precipitation. A Lattice Boltzmann implementation of the two-dimensional mineral surface was developed to evaluate geometry evolution when probabilistic nucleation criterion is incorporated. To provide high-resolution surface information on mineral precipitation, growth, and distribution, we conducted a total of 27 calcium carbonate synthesis experiments in the laboratory. The results indicate that nucleation events as precursors determine the location and timing of crystal precipitation. It is shown that reaction rate has primary control over covering the substrate with nuclei and, subsequently, solid-phase accumulation. The work provides insight into the spatiotemporal evolution of porous media by suggesting probabilistic and deterministic domains for studying reactive transport processes. We indicate in which length- and time-scales it is essential to incorporate probabilistic nucleation for valid predictions.

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