Measurement of 3D pore-scale flow in index-matched porous media

Stöhr, Michael; Roth, Kurt; Jähne, Bernd

doi:10.1007/s00348-003-0641-x

Cited by 79 publications

(58 citation statements)

References 9 publications

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“…The authors reported satisfactory results with PVA in their application. PMMA, which is also known by the trade names Perspex, Plexiglas, or acrylic glass, is the most commonly employed solid in RIM experiments with a RI of ≈ 1.490, a density of 1180 kg/m 3 , and an air-water contact angle of θ = 59.3° (Stöhr et al 2003). It is optically clear and is easily machined, although it is also brittle and prone to cracking.…”

Section: Common Plasticsmentioning

confidence: 99%

“…The silicone rubber was then RI matched to two immiscible fluids, where the aqueous phase was a 67.9 wt% glycerol solution and the organic phase was methylcyclohexane. In another study, by Stöhr et al (2003), two-phase liquid flows through porous media were investigated using PLIF and a fully matched RIM system. The porous medium consisted of fused quartz matched to two immiscible fluid combinations.…”

Section: Solid-liquid-liquid Systemsmentioning

confidence: 99%

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A review of solid–fluid selection options for optical-based measurements in single-phase liquid, two-phase liquid–liquid and multiphase solid–liquid flows

2017

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Experimental techniques based on optical measurement principles have experienced significant growth in recent decades. They are able to provide detailed information with high-spatiotemporal resolution on important scalar (e.g., temperature, concentration, and phase) and vector (e.g., velocity) fields in single-phase or multiphase flows, as well as interfacial characteristics in the latter, which has been instrumental to step-changes in our fundamental understanding of these flows, and the development and validation of advanced models with ever-improving predictive accuracy and reliability. Relevant techniques rely upon well-established optical methods such as direct photography, laser-induced fluorescence, laser Doppler velocimetry/phase Doppler anemometry, particle image/tracking velocimetry, and variants thereof. The accuracy of the resulting data depends on numerous factors including, importantly, the refractive indices of the solids and liquids used. The best results are obtained when the observational materials have closely matched refractive indices, including test-section walls, liquid phases, and any suspended particles. This paper reviews solid–liquid and solid–liquid–liquid refractive-index-matched systems employed in different fields, e.g., multiphase flows, turbomachinery, bio-fluid flows, with an emphasis on liquid–liquid systems. The refractive indices of various aqueous and organic phases found in the literature span the range 1.330–1.620 and 1.251–1.637, respectively, allowing the identification of appropriate combinations to match selected transparent or translucent plastics/polymers, glasses, or custom materials in single-phase liquid or multiphase liquid–liquid flow systems. In addition, the refractive indices of fluids can be further tuned with the use of additives, which also allows for the matching of important flow similarity parameters such as density and viscosity

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Section: Common Plasticsmentioning

confidence: 99%

Section: Solid-liquid-liquid Systemsmentioning

confidence: 99%

A review of solid–fluid selection options for optical-based measurements in single-phase liquid, two-phase liquid–liquid and multiphase solid–liquid flows

2017

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“…The corresponding unique solution for the case of an ambigious 2D motion estimate represented by (48) is k = 0 or u = (u x , 0) T . For models of processes with anisotropic diffusion however, this constraint leads to unphysical results and a modified criterion based on physical constraints as presented by [Stöhr, 2003] has to be applied instead.…”

Section: Aperture Problemmentioning

confidence: 99%

“…Whereas TLS is relatively insensitive against low noise levels, higher levels can change the order of the eigenvalues and thereby strongly affect the solution [Mühlich and Mester, 1999]. Most of the approaches are based on the analysis of the eigenvalue spectrum of J [Spies, 2001;Stöhr, 2003]. When the data is contaminated with noise, the smallest eigenvalue of J is no longer zero.…”

Section: Measure Of Confidencementioning

confidence: 99%

“…As a consequence, an adequate model for flow and transport in such a medium requires reliable information about the local values v(x) and D(x) instead of one single macroscopic value for v and D. This implies that the concentrations are measured with a sufficiently high spatial and temporal resolution. A growing number of techniques for the laboratory, like, e.g., light transmission with Hele-Shaw cells [Berest et al, 1999;Detwiler and Rajaram, 2000], 3D planar laser-induced fluorescence [Stöhr et al, 2003], positron emission projection imaging [Loggia et al, 2004] and X-ray computed tomography [Keller et al, 1999] are available to provide such data. Although the task is much more challenging on the field scale, high-resolution measurements of tracer migration have been obtained recently using 3D electrical resistivity tomography [Kemna et al, 2002;Singha et al, 2003].…”

Section: Introductionmentioning

confidence: 99%

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Gradient‐based estimation of local parameters for flow and transport in heterogeneous porous media

Stöhr

Roth

2005

Water Resources Research

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[1] We present the application of the gradient-based total least squares (TLS) method to the local estimation of parameters for flow and transport in porous media. The concept is based on the evaluation of partial derivatives of spatially and temporally resolved data using TLS as a maximum likelihood estimator. While ordinary inverse modeling approaches are often complicated by the spatially varying properties of porous media, the present approach can directly localize the estimation to an arbitrary range in space and time. The estimation of the local parameters can be achieved without requiring any explicit solution of the respective transport equation. First the basic ideas and the formalism of TLS are introduced with a simple example of a straight line fit. Then the ideas of the gradient-based approach and its application to the parameter estimation for a large class of dynamic processes are presented. We further discuss relevant computational issues such as the calculation of the derivatives, choice of the local neighborhood and the determination of a measure of confidence. The performance of the method is then exemplified by the estimation of local velocities and dispersion coefficients from numerical solutions of the convection-dispersion equation.

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Eulerian network modeling of longitudinal dispersion

Mehmani

Balhoff

2015

Water Resources Research

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A novel Eulerian network model that incorporates “shear dispersion,” the stretching of solute due to nonuniform velocity profiles within pore throats is developed. The superposing transport method (STM) is nonlocal in time (i.e., uses information from several previous time steps) and is equivalent to performing network‐wide time convolutions of elementary throat response functions. Predicted macroscopic longitudinal dispersion coefficients for disordered sphere packs are in good agreement with published experimental data. We further investigate the impact of mixing assumptions within pores on macroscopic longitudinal dispersion and find the dependence to be weak for disordered sphere packs. Limitations of Eulerian network models as a whole are also discussed, and their inappropriateness for ordered porous media concluded.

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Measurement of 3D pore-scale flow in index-matched porous media

Cited by 79 publications

References 9 publications

A review of solid–fluid selection options for optical-based measurements in single-phase liquid, two-phase liquid–liquid and multiphase solid–liquid flows

A review of solid–fluid selection options for optical-based measurements in single-phase liquid, two-phase liquid–liquid and multiphase solid–liquid flows

Gradient‐based estimation of local parameters for flow and transport in heterogeneous porous media

Eulerian network modeling of longitudinal dispersion

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