Lattice Boltzmann simulation of gas-solid heat transfer in random assemblies of spheres: The effect of solids volume fraction on the average Nusselt number for Re ≤ 100

Chen, Y.; Müller, Christoph R.

doi:10.1016/j.cej.2018.10.182

Cited by 32 publications

(7 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Nusselt numbers at different inlet temperatures roughly form the same line. This result is similar to Chen and Mueller's empirical correlation [43]. The error is within 2%.…”

Section: Nusselt Number In Packed Bedsupporting

confidence: 90%

See 1 more Smart Citation

CFD-DEM Modeling of Cryogenic Hydrogen Flow and Heat Transfer in Packed Bed

Quan,

Xia,

Zhang

2024

Sustainability

View full text Add to dashboard Cite

Hydrogen is an important component of renewable energy and is essential for sustainable development. The cryogenic energy storage system can solve the problem of hydrogen storage. A packed bed can be applied in a cryogenic energy storage system. It is crucial to understand the cryogenic energy discharging in a packed bed. In the present work, the CFD-DEM coupling method is used to investigate the pore-scale flow and heat transfer characteristics of cryogenic hydrogen flowing through the packed bed. To demonstrate the characteristics of the pore-scale heat transfer of the hydrogen flow in a packed bed, the local radial-averaged and axial-averaged temperatures and velocities are analyzed in detail, depending on the local porosity distribution. The pore-scale radial-averaged velocity distribution is proportional to the local radial porosity distribution, whereas the pore-scale radial-averaged temperature characteristics are inverse. Moreover, for the heat exchange of the cryogenic hydrogen flow in a packed bed, it can be found that the cryogenic hydrogen flow is fully heated at an axial distance of approximately 7 dp. Finally, considering that the thermo-physical properties of cryogenic hydrogen are sensitive to the temperature in a packed bed, the friction factor and Nusselt number in the packed bed are also analyzed under various operating parameters, which are in good agreement with certain classic empirical correlations.

show abstract

“…The Nusselt numbers at different inlet temperatures roughly form the same line. This result is similar to Chen and Mueller's empirical correlation [43]. The error is within 2%.…”

Section: Nusselt Number In Packed Bedsupporting

confidence: 90%

“…Fluid with a low velocity is present behind the particles, resulting in higher fluid temperatures compared to other areas. This phenomenon is the same as that observed in Guo's [43] study. This phenomenon is more pronounced at lower inlet velocities.…”

Section: Velocity and Temperature Contour Of Packed Bedsupporting

confidence: 89%

CFD-DEM Modeling of Cryogenic Hydrogen Flow and Heat Transfer in Packed Bed

Quan,

Xia,

Zhang

2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…While λ f and d p are usually known in ideal packed beds, Nu must be estimated using an appropriate correlation which commonly depends on the particle Reynolds number, Re , and the Prandtl number, Pr (see supporting information Table S1 for examples). Generally, such a correlation is empirically derived from laboratory experiments (Achenbach, 1995; Collier et al, 2004; Naghash et al, 2016; Nie et al, 2011; Shent et al, 1981; Wakao & Kaguei, 1982; Zanoni et al, 2017) or, more recently, by particle resolved direct numerical modeling (Chen & Müller, 2019; Singhal et al, 2017b; Sun et al, 2015; Tavassoli et al, 2015; Zhu et al, 2019). As natural porous aquifers are typified by Re < 50 and a porosity (fluid volume fraction) n < 0.5, the correlations established by previous studies are covering much broader ranges.…”

Section: Methodsmentioning

confidence: 99%

On the Limitations and Implications of Modeling Heat Transport in Porous Aquifers by Assuming Local Thermal Equilibrium

Gossler

Bayer

Rau

et al. 2020

Water Resources Research

View full text Add to dashboard Cite

Heat transport in natural porous media, such as aquifers or streambeds, is generally modeled assuming local thermal equilibrium (LTE) between the fluid and solid phases. Yet, the mathematical and hydrogeological conditions and implications of this simplification have not been fully established for natural porous media. To quantify the occurrence and effects of local thermal disequilibrium during heat transport, we systematically compared thermal breakthrough curves from a LTE with those calculated using a local thermal nonequilibrium (LTNE) model, explicitly allowing for different temperatures in the fluid and solid phases. For the LTNE model, we developed a new correlation for the heat transfer coefficient representative of the conditions in natural porous aquifers using six published experimental results. By conducting an extensive parameter study (>50,000 simulations), we show that LTNE effects do not occur for grain sizes smaller than 7 mm or for groundwater flow velocities that are slower than 1.6 m day −1. The limits of LTE are likely exceeded in gravel aquifers or in the vicinity of pumped bores. For such aquifers, the use of a LTE model can lead to an underestimation of the effective thermal dispersion by a factor of up to 30 or higher, while the advective thermal velocity remains unaffected for most conditions. Based on a regression analysis of the simulation results, we provide a criterion which can be used to determine if LTNE effects are expected for particular conditions.

show abstract

“…However, since the upscaling framework is not properly defined, this leads to some indeterminacies in defining the appropriate boundary conditions, how to calculate the Nusselt number, or how the Nusselt number is consistent with the macroscopic two-temperature model [22]. As pointed out by Chen et al [27], the adopted boundary conditions can have an impact on the numerically derived correlations. Moreover, as stated by Sun et al [22], the Nusselt number is usually calculated for the mixing-cup temperature 𝑇 = 𝑢 𝑇 /𝑢 but is used in the macroscopic two-temperature model with the average temperature 𝑇 .…”

Section: Introductionmentioning

confidence: 99%

New Framework for Upscaling Gas-Solid Heat Transfer in Dense Packing

Noël¹,

Teixeira²

2021

SSRN Journal

View full text Add to dashboard Cite

Lattice Boltzmann simulation of gas-solid heat transfer in random assemblies of spheres: The effect of solids volume fraction on the average Nusselt number for Re ≤ 100

Cited by 32 publications

References 31 publications

CFD-DEM Modeling of Cryogenic Hydrogen Flow and Heat Transfer in Packed Bed

CFD-DEM Modeling of Cryogenic Hydrogen Flow and Heat Transfer in Packed Bed

On the Limitations and Implications of Modeling Heat Transport in Porous Aquifers by Assuming Local Thermal Equilibrium

New Framework for Upscaling Gas-Solid Heat Transfer in Dense Packing

Contact Info

Product

Resources

About

Lattice Boltzmann simulation of gas-solid heat transfer in random assemblies of spheres: The effect of solids volume fraction on the average Nusselt number for Re ≤ 100

Cited by 32 publications

References 31 publications

CFD-DEM Modeling of Cryogenic Hydrogen Flow and Heat Transfer in Packed Bed

CFD-DEM Modeling of Cryogenic Hydrogen Flow and Heat Transfer in Packed Bed

On the Limitations and Implications of Modeling Heat Transport in Porous Aquifers by Assuming Local Thermal Equilibrium

New Framework for Upscaling Gas-Solid Heat Transfer in Dense Packing

Contact Info

Product

Resources

About

Lattice Boltzmann simulation of gas-solid heat transfer in random assemblies of spheres: The effect of solids volume fraction on the average Nusselt number for Re ≤ 100