Explicit modeling of pebble temperature in the porous-media model for pebble-bed reactors

Zou, Ling; Hu, Guojun; O’Grady, Daniel; Hu, Rui

doi:10.1016/j.pnucene.2022.104175

Cited by 15 publications

(9 citation statements)

References 12 publications

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“…SAM provides some code capability when modeling multi-dimensional flow including both Navier-Stoke flow model [4] and porous-medium flow model [5]. In terms of multi-dimensional flow model, a unique feature to SAM is the full integration of the 1D and 3D flow models via special flow junction component and the integrated 1D/3D system is solved in a fully coupled manner attributable to the Newton's method inherited from the MOOSE system.…”

Section: D/3d Flow Model Couplingmentioning

confidence: 99%

Enabling Parallel Execution of System-level Simulations in SAM

Zou

O’Grady

2022

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Section: D/3d Flow Model Couplingmentioning

confidence: 99%

Enabling Parallel Execution of System-level Simulations in SAM

Zou

O’Grady

2022

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“…Previous efforts have been made to model the extremely complex geometry of pebble bed systems, which are typically accompanied by computationally difficult random and repeated unit cell simulations. − Most studies have gathered temperature profiles and thermal conductivities across the entire sample range into a lumped thermal result. However, variations in the thermal conductivity at geometric boundaries are inevitable. − The packing and porosity of the pebbles largely dictate the rate of heat conduction .…”

Section: Introductionmentioning

confidence: 99%

Analysis of Near-Wall Pebble Bed Thermal Conductivity for Energy Applications

Wada,

Eixenberger,

Stout

et al. 2023

ACS Omega

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Pebble beds have been employed in thermal storage and energy systems, where they are typically used to promote heat exchange in high-temperature environments. Understanding the heat conduction of the entire pebble bed could aid in the material selection of the pebbles themselves and structural components, system design, and safety monitoring. However, the thermal conductivity of pebble beds can change significantly near geometric boundaries. Using a complex multilayer analytical model in conjunction with a line source probe, we found a substantial increase in the thermal conductivity of a sintered bauxite pebble bed in the near-wall region (7.6 W m −1 K −1 ) compared to the bulk (0.59 W m −1 K −1 ). We investigated this difference by comparing porosity results, acquired with micro-CT, of 33.18 and 33.31% at approximately one pebble width surrounding the probe (near-wall) and the bulk of the pebble bed, suggesting that the thermal conductivity is largely altered by thermal contact resistance in the nearwall regime.

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“…Banerjee and Paul (Banerjee and Paul, 2021) examined the most recent research and advancements concerning PMM combustion applications. For pebble-bed devices, Zou et al (Zou et al, 2022) designed an explicit system of stone heat in the PMM. PMM substantiation using stress drip dimensions was suggested by Lee et al (Lee et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Quadratic regression estimation of hybridized nanoliquid flow using Galerkin finite element technique considering shape of nano solid particles

Rahman

Jamshed

et al. 2022

Front. Energy Res.

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Because of its multivariate particle suspension approach, the developing class of fluid has a better level of stability as well as increased heat transfer. In this regard, hybrid nanofluid outperforms ordinary fluid and even well-known nanofluid. In a slick environment, we investigate its fluidity and heat transfer qualities. Nano-leveled particle morphologies, porousness materials, variable thermal conductivity, slippage velocity, and thermal radiative effects are all being studied. The Galerkin finite element method is a numerical methodology for numerically solving the governing equations (G-FEM). For this analysis, a Powell-Eyring hybrid nanofluid (PEHNF) flowing via a permeable stretchable surface is used, which comprises two types of nanoparticles (NP), copper (Cu), and titanium alloy (Ti6Al4V) dispersed in sodium alginate (C6H9NaO7). The heat transfer ratio of PEHNF (Ti6Al4V-Cu/C6H9NaO7) remained much greater than that of conventional nanofluids (Cu-C6H9NaO7), with a range of 43%–54%. When lamina particles are present, the thermal conductivity of the boundary layer increases dramatically, while spherical nanoparticles have the lowest thermal conductivity. As nanoparticles are added under their fractional sizes, radiative heat conductance, and flexible heat conductance, the system’s entropy increases. The flow system’s ability to transport mass decreases when molecule diffusivity decreases dramatically. This is theoretically related to a rise in Schmidt number against molecular diffusivity.

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Explicit modeling of pebble temperature in the porous-media model for pebble-bed reactors

Cited by 15 publications

References 12 publications

Enabling Parallel Execution of System-level Simulations in SAM

Enabling Parallel Execution of System-level Simulations in SAM

Analysis of Near-Wall Pebble Bed Thermal Conductivity for Energy Applications

Quadratic regression estimation of hybridized nanoliquid flow using Galerkin finite element technique considering shape of nano solid particles

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