Implementation and validation of a 3D image-based prediction model for the thermal conductivity of cellular and granular porous building blocks

Walle, Wouter Van De; Claes, Steven; Janssen, Hans

doi:10.1016/j.conbuildmat.2018.06.105

Cited by 19 publications

(28 citation statements)

References 61 publications

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“…To validate the hygric property model, numerical simulations are compared to experimental results for a ROBU P100 sintered-glass filter. This material has been preferred over an actual building material, given that it only has coarse pores ranging from 2 to 130 micrometers, hence allowing a reliable characterization of its pore structure via X-ray CT [8]. To transform the obtained pore structure to a pore network model, the original maximal-ball (MB) network extraction [9] and its recently revised version [10] are used, illustrating the variability due to the network extraction.…”

Section: Validationmentioning

confidence: 99%

Validation of pore network model for hygric property calculation

et al. 2019

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Hygric properties can be estimated directly from pore structure information, represented by a network of regularly shaped pores, extracted from a pore structure image to conserve the real topology. On this network, pore-scale models of moisture behaviour determine the hygric properties of moisture storage and transport. The reliability of this approach is validated with a sintered-glass filter. Despite its more limited heterogeneity and pore size range relative to typical porous building materials, it provides a good basis for validating crucial pore-scale moisture processes. Measured storage data compare well to the estimated ad- and desorption moisture retention curves as well as to the saturated and capillary moisture content. Furthermore, the simulated whole-range moisture permeability curve agrees acceptably with measured data. The variation in modelling the pore space as a pore network model is also analysed by considering two distinct pore network extraction methods. The measured and simulated moisture contents agree well for the whole capillary range. Moreover, the resulting transport properties are generally accurate for the whole moisture content range. On the other hand, the estimated vapour permeabilities show notable variations between the two pore network models.

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Section: Validationmentioning

confidence: 99%

Validation of pore network model for hygric property calculation

et al. 2019

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“…The model framework has been validated using a sintered glass filter sample of 36 % porosity and a Reapor block of 89 % porosity with a mixed cellular-granular pore structure. For both materials, good agreement was achieved between numerical and experimental results, with deviations below 10 % [4].…”

Section: Model Frameworkmentioning

confidence: 56%

“…1. More details can be found in [4]. Thermal radiation is taken into account through an adapted version of Loeb's method: a radiative conductivity is calculated in every pore based on its size, shape and wall emissivity [5].…”

Section: Model Frameworkmentioning

confidence: 99%

Impact of pore scale parameters on the thermal conductivity of porous building blocks

Walle

Janssen

2019

MATEC Web Conf.

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Increasingly stringent energy requirements push for better performing building blocks with reduced thermal conductivity. A numerical framework to predict the heat transfer through porous materials is employed to investigate the effect of several microscale parameters on the macroscale thermal conductivity. Two different algorithms are used to generate a range of different cellular materials. Simulation results highlight the effect of the porosity, pore size distribution, matrix structure and matrix conductivity on the total thermal conductivity.

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“…Recently, the authors presented an image-based model to study the effect of the pore structure parameters on the ETC in macrocellular materials like cellular concrete or cellular glass (Van De Walle et al, 2018). Further thermal optimization of such materials could be achieved by reducing the pore size and/or the gas pressure as discussed earlier.…”

Section: Extension Of the Model Frameworkmentioning

confidence: 99%

“…This article discusses the extension of an existing 3D image-based thermal conductivity model (Van De Walle et al, 2018) to simulate porous materials containing nanosized pores or with low gas pressures. The model performs simulations on the 3D pore structure of the material, inherently incorporating the effect of the pore structure parameters.…”

Section: Introductionmentioning

confidence: 99%

A 3D model to predict the influence of nanoscale pores or reduced gas pressures on the effective thermal conductivity of cellular porous building materials

Walle

Janssen

2019

Journal of Building Physics

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Cellular porous materials are frequently applied in the construction industry, both for structural and insulation purposes. The progressively stringent energy regulations mandate the development of better performing insulation materials. Recently, novel porous materials with nanopores or reduced gas pressures have been shown to possess even lower thermal conductivities because of the Knudsen effect inside their pores. Further understanding of the relation between the pore structure and the effective thermal conductivity is needed to quantify the potential improvement and design new optimized materials. This article presents the extension of a 3D numerical framework simulating the heat transfer at the pore scale. A novel methodology to model the reduced gas-phase conductivity in nanopores or at low gas pressures is presented, accounting for the 3D pore geometry while remaining computationally efficient. Validation with experimental and numerical results from the literature indicates the accuracy of the methodology over the full range of pore sizes and gas pressures. Combined with an analytical model to account for thermal radiation, the framework is applied to predict the thermal conductivity of a nanocellular poly(methyl methacrylate) foam experimentally characterized in the literature. The simulation results show excellent agreement with less than 5% difference with the experimental results, validating the model’s performance. Furthermore, results also indicate the potential improvements when decreasing the pore size from the micrometre to the nanometre range, mounting up to 40% reduction for such high-porosity low-matrix-conductivity materials. Future application of the model could assist the design of advanced materials, properly accounting for the effect of reduced pore sizes and gas pressures.

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Implementation and validation of a 3D image-based prediction model for the thermal conductivity of cellular and granular porous building blocks

Cited by 19 publications

References 61 publications

Validation of pore network model for hygric property calculation

Validation of pore network model for hygric property calculation

Impact of pore scale parameters on the thermal conductivity of porous building blocks

A 3D model to predict the influence of nanoscale pores or reduced gas pressures on the effective thermal conductivity of cellular porous building materials

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