Characterization of a porous transducer using a capillary bundle model: Permeability and streaming potential prediction

Cheng, Siyuan; Fu, Mengyin; Kulacki, F. A.

doi:10.1016/j.ijheatmasstransfer.2017.10.128

Cited by 17 publications

(11 citation statements)

References 25 publications

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“…In this work, the linking of emulsion properties with the equations to estimate the pressure gradient through porous beds (Φ), involves the Carmen-Kozeny and Burke-Plumber equations in conjunction with the analysis presented by Cheng et al [12]. Considering a solid tube with diameter D and length L, the following expressions are obtained:…”

Section: Mathematical Analysis Of the Emulsion Flow Through Porous Bedsmentioning

confidence: 99%

Water-In-Oil Emulsions through Porous Media and the Effect of Surfactants: Theoretical Approaches

et al. 2019

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The most complex components in heavy crude oils tend to form aggregates that constitute the dispersed phase in these fluids, showing the high viscosity values that characterize them. Water-in-oil (W/O) emulsions are affected by the presence and concentration of this phase in crude oil. In this paper, a theoretical study based on computational chemistry was carried out to determine the molecular interaction energies between paraffin-asphaltenes-water and four surfactant molecules to predict their effect in W/O emulsions and the theoretical influence on the pressure drop behavior for fluids that move through porous media. The mathematical model determined a typical behavior of the fluid when the parameters of the system are changed (pore size, particle size, dispersed phase fraction in the fluid, and stratified fluid) and the viscosity model determined that two of the surfactant molecules are suitable for applications in the destabilization of W/O emulsions. Therefore, an experimental study must be set to determine the feasibility of the methodology and mathematical model displayed in this work.

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Section: Mathematical Analysis Of the Emulsion Flow Through Porous Bedsmentioning

confidence: 99%

Water-In-Oil Emulsions through Porous Media and the Effect of Surfactants: Theoretical Approaches

et al. 2019

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“…The steady-state model of the molecular electronic system is presented by employing the capillary bundle model [34], in which the porous transducer is equivalent to a bundle of circular capillaries with the same tortuosity τc, as shown in Figure 4. The capillary radius distribution (CRD) can be calculated from PSD, and both are lognormal distributions, respectively presented by prefixln()dp∼N()μd,σd2 and prefixln()rc∼N()μc,σc2 [34]. The parameters of CRD can be derived from PSD [34], specifically as:μc=μd−prefixln(2Θ), σc=σd, where Θ=m2F2/3, m is the cementation index of the porous media, and F=ϕm presents the formation factor.…”

Section: Theoretical Analysis Of the Transient Model Of The Electrmentioning

confidence: 99%

“…The capillary radius distribution (CRD) can be calculated from PSD, and both are lognormal distributions, respectively presented by prefixln()dp∼N()μd,σd2 and prefixln()rc∼N()μc,σc2 [34]. The parameters of CRD can be derived from PSD [34], specifically as:μc=μd−prefixln(2Θ), σc=σd, where Θ=m2F2/3, m is the cementation index of the porous media, and F=ϕm presents the formation factor. ϕ means the porosity of porous media, calculated by [34]:ϕ=πτcAE()rc2. The steady-state permeability is derived based on the capillary bundle model [34], presented as, K0=Qμ<...>…”

Section: Theoretical Analysis Of the Transient Model Of The Electrmentioning

confidence: 99%

“…The parameters of CRD can be derived from PSD [34], specifically as:μc=μd−prefixln(2Θ), σc=σd, where Θ=m2F2/3, m is the cementation index of the porous media, and F=ϕm presents the formation factor. ϕ means the porosity of porous media, calculated by [34]:ϕ=πτcAE()rc2. The steady-state permeability is derived based on the capillary bundle model [34], presented as, K0=QμLAΛP=ϕ8τc2E()rc4E()rc2 where the expression of the original moment is:E()rcn=enμc+…”

Section: Theoretical Analysis Of the Transient Model Of The Electrmentioning

confidence: 99%

“…In this paper, we present a modified Packard’s model considering surface conductance, calculated by Revil’s model [16]. Combining the capillary bundle model of a porous transducer in LCAA [34], the modified Packard’s model is extended to the capillary bundle, and the dynamic model of streaming potential in porous media is established and employed to analyze the influence of structure parameters such as the particle size distribution (PSD), and solution properties like the zeta potential, surface conductance, pH, and solution conductivity on dynamic performance. In addition, experiments to measure steady-state permeability and SPC were actualized for seven types of porous transducers with different PSD.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Frequency-Dependent Streaming Potential in a Porous Transducer-Based Angular Accelerometer

Wang

2019

Sensors

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This paper presents a transient model of streaming potential generated when fluid flows through a porous transducer, which is sintered by glass microspheres and embedded in the circular tube of a liquid circular angular accelerometer (LCAA). The streaming potential coupling coefficient (SPC) is used to characterize this proposed transient model by combining a capillary bundle model of a porous transducer with a modified Packard’s model. The modified Packard’s model is developed with the consideration of surface conductance. The frequency-dependent streaming potential is investigated to analyze the effect of structure parameters of porous media and the properties of the fluid, including particle size distribution, zeta potential, surface conductance, pH, and solution conductivity. The results show that the diameter of microspheres not only affects bandwidth and transient response, but also influences the low-frequency gain. In addition, the properties of the fluid can influence the low-frequency gain. Experiments are actualized to measure the steady-state value of permeability and SPC for seven types of porous transducers. Experimental results possess high consistency, which verify that the proposed model can be utilized to optimize the transient and steady-state performance of the system effectively.

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Simplified method for estimating discharge of microporous ceramic emitters for drip irrigation

Liu

Zhang

2022

Biosystems Engineering

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Characterization of a porous transducer using a capillary bundle model: Permeability and streaming potential prediction

Cited by 17 publications

References 25 publications

Water-In-Oil Emulsions through Porous Media and the Effect of Surfactants: Theoretical Approaches

Water-In-Oil Emulsions through Porous Media and the Effect of Surfactants: Theoretical Approaches

Frequency-Dependent Streaming Potential in a Porous Transducer-Based Angular Accelerometer

Simplified method for estimating discharge of microporous ceramic emitters for drip irrigation

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