scholarly journals A DEM/FFT approach to simulate the effective thermal conductivity of granular media

2022 ◽  
Vol 172 ◽  
pp. 107339
Author(s):  
Tristan Calvet ◽  
Jean-Mathieu Vanson ◽  
Renaud Masson
Author(s):  
Arkadiusz Grucelski

AbstractFlow thermomechanics in reactive porous media is of importance in industry including the thermal processing of fossil fuel (coking understood as a slow pyrolysis) involving devolatilisation. On the way to provide a detailed description of the process, a multi-scale approach was chosen to estimate effective transport coefficients. For this case the Lattice Boltzmann method (LBM) was used due to its advantages to accurately model multi-physics and chemistry in a random geometry of granular media. After account for earlier studies, the paper presents description of the model with improved boundary conditions and a benchmark case. Results from meso-scale LBM calculations are presented and discussed regarding the spatial resolution and the choice of relaxation parameter along its influence on the accuracy compared with empirical formulae. Regarding the estimation of effective thermal conductivity coefficient it is shown that occurrence of devolatilization has a crucial effect by reducing heat transfer. Some quantitative results characterise the propagation of thermal front; also presented is the evolution of effective thermal conductivity. The work is a step forward towards a physically sound simulation of thermal processing of fossil fuel.


2020 ◽  
Vol 4 (1) ◽  
pp. 32
Author(s):  
Chris R. Bowen ◽  
Kevin Robinson ◽  
Jianhui Tian ◽  
Meijie Zhang ◽  
Vincent A. Coveney ◽  
...  

The properties of thermal networks are examined to understand the effective thermal conductivity of heterogeneous two-phase composite materials and systems. At conditions of high contrast in thermal conductivity of the individual phases (k1 and k2), where k1 << k2 or k1 >> k2, the effective thermal conductivity of individual networks of the same composition was seen to be highly sensitive to the distribution of the phases and the presence of percolation paths across the network. However, when the contrast in thermal conductivities of the two phases was modest (k1/k2 ~ 10−2 to 102), the thermal networks were observed to exhibit an emergent response with a low variability in the effective thermal conductivity of mixtures of the same composition. A logarithmic mixing rule is presented to predict the network response in the low variability region. Excellent agreement between the model, mixing rule and experimental data is observed for a range two-phase porous and granular media. The modelling approach provides new insights into the design of multi-phase composites for thermal management applications and the interpretation or prediction of their heat transfer properties.


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