Simulation of magnetite nanoparticle mobility in a heterogeneous flow cell

Lyon-Marion, Bonnie A.; Becker, Matthew; Kmetz, Anthony A.; Foster, Edward L.; Johnston, Keith P.; Abriola, Linda M.; Pennell, Kurt D.

doi:10.1039/c7en00152e

Cited by 9 publications

(8 citation statements)

References 60 publications

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“…Retention and formation damage parameters vary with the different rock and NP encapsulation types and are usually determined by column experiments. In this case, experimental NP retention parameters are adopted from a large-scale lab experiment ( [10]). Formation damage is also considered by assuming the maximum permeability reduction is 50%, which means the formation damage coefficient, β adsorption , can be calculated based on Eq.…”

Section: Case 5: Encapsulation Conformance Control In a 3d Reservoirmentioning

confidence: 99%

“…These sur-2 face interactions, in turn, can result in reversible or irreversible capture ( [9]). Additionally, density differences can make NPs respond to gravity or inertial flows in ways that solutes do not ( [10]). Finally, engineered behaviors such as payload release or triggered responses add a more complex reaction component to the modeling, compared to traditional advective-dispersive-reactive transport ( [11,12] Our understanding of basic NP behavior in porous media is founded on a long history of experiments and theory on colloids and interfaces, particularly examples such as ( [13]; [14]; [15]; [16]; [17] and [18]).…”

Section: Introductionmentioning

confidence: 99%

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Streamline-based simulation of nanoparticle transport in field-scale heterogeneous subsurface systems

Wang

Feng

Blears

et al. 2021

Advances in Water Resources

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Nanoparticle (NP) transport is increasingly relevant to subsurface engineering applications such as aquifer characterization, fracture electromagnetic imaging and environmental remediation. An efficient field-scale simulation framework is critical for predicting NP performance and designing subsurface applications. In this work, for the first time, a streamline-based model is presented to simulate NP transport in field-scale subsurface systems. It considers a series of behaviors exhibited by engineered nanoparticles (NPs), including time-triggered encapsulation, retention, formation damage effects and variable nanofluid viscosity. The key methods employed by the algorithm are streamline-based simulation (SLS) and an operator-splitting (OS) technique for modeling NP transport. SLS has proven to be efficient for solving transport in large and heterogeneous systems, where the pressure and velocity fields are firstly solved on underlying grids using finite-difference (FD) methods. After tracing streamlines, one-dimensional (1D) NP transport is solved independently along each streamline. The adoption of OS enhances flexibility for the entire solution procedure by allowing different numerical schemes to solve different governing equations efficiently and accurately. For the NP transport model, an explicit FD scheme is used to solve the advection term, an implicit FD scheme is used for the diffusion term and an adaptive numerical integration is used to solve the retention terms.

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Section: Case 5: Encapsulation Conformance Control In a 3d Reservoirmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Streamline-based simulation of nanoparticle transport in field-scale heterogeneous subsurface systems

Wang

Feng

Blears

et al. 2021

Advances in Water Resources

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“…3), with subsequent transport captured via digital imagery. We used similar data collection techniques to those previously employed in investigations of the migration of solute plumes affected by density gradients in porous media [22,27,32]. Two different concentrations of carbon ink, 2.07 g L -1 and 10.33 g L -1 , were used to investigate effects of changing density gradients.…”

Section: Flume Experimentsmentioning

confidence: 99%

“…Like solutes, nanoparticles can change the density of the carrier fluid. Consequently, nanoparticle concentration variations can result in fluid density gradients that affect both fluid flow and mass transport processes [22,26,27]. Jin et al [28] showed that such density gradients can accelerate solute transfer from the river water to the riverbed and inhibit the release of solutes from the bed.…”

Section: Introductionmentioning

confidence: 99%

“…For nanoparticles, Kanel et al [22] developed a model of nanoparticle transport in porous media that includes density and demonstrated the importance of density during injection of nanoparticles into porous media. Bonnie et al [27] simulated nanoparticle mobility as affected by density gradients in a heterogeneous porous medium and determined that a relatively small contrast in particle density can result in flow instabilities. However, how nanoparticle transport in the hyporheic zone is affected by density gradients in combination with other driving forces remains unclear.…”

Section: Introductionmentioning

confidence: 99%

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Density effects on nanoparticle transport in the hyporheic zone

Jin

Jiang

Tang

et al. 2018

Advances in Water Resources

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A carbon solution composed of nanoparticles (d 50 = 85.7 nm) was used in experiments designed to explore nanoparticle transport characteristics within the hyporheic zone of a riverbed. Experiments and numerical simulations demonstrated that nanoparticle transport in the hyporheic zone is affected by hydraulic head gradients due to river flow-bedform interactions as well as density gradients associated with the nano-carbon solution. Differences with similar flow/transport situations were examined, and it was found that particulate-enhanced density can change hyporheic transport appreciably. In addition to density, particle settling enhances downward movement of the nano-carbon plume in the riverbed. While nanoparticle transport in the upper hyporheic zone is largely controlled by advection due to flow driven by head gradients at the bed surface, density gradients and particle settling influence the transport process significantly in the lower hyporheic zone. During the transport process, nanoparticles become deposited due to attachment to sand particles and filtration by small pores in the bed. Compared with transport where density variations are minimal, the particulate-induced density gradient induces downward transport of nanoparticles and entrained liquids, leading to deposition/accumulation at the base of the bed.

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Deposition mechanism of polydisperse xanthan gum-stabilized graphene oxide/nano-iron composites in saturated porous medium

Ren

Chi

Dong

et al. 2020

Journal of Cleaner Production

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Simulation of magnetite nanoparticle mobility in a heterogeneous flow cell

Abstract: Measured and simulated magnetite nanoparticle transport and retention.

Cited by 9 publications

References 60 publications

Streamline-based simulation of nanoparticle transport in field-scale heterogeneous subsurface systems

Streamline-based simulation of nanoparticle transport in field-scale heterogeneous subsurface systems

Density effects on nanoparticle transport in the hyporheic zone

Deposition mechanism of polydisperse xanthan gum-stabilized graphene oxide/nano-iron composites in saturated porous medium

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