Characterization and simulation of microstructure and thermal properties of foamed concrete

She Wei, Chen Yiqiang, Zhang Yunsheng, M.R. Jones

    Research output: Contribution to journalArticle

    94 Citations (Scopus)

    Abstract

    Foamed concretes are composed of cement or mortar mixed with small size foams (0.1-1 mm). They exhibit good thermal insulation properties that are suitable for the insulating construction industry. To facilitate the design and development of this material, simulation of their thermal properties is essential. In this paper, foamed concretes with a large range of densities (300-1700 kg/m3) have been fabricated by the pre-forming method. The corresponding microstructures were characterized in 3D by the X-ray computerized tomography. A random generation method was introduced to efficiently model the 2D microstructures that retained the essential features of the experimental materials. Based on the reproduced 2D images, a resistor network analogy method was then introduced to numerically predict the effective thermal conductivity of this material. Finally the predictions were compared with the experimental data and other existing models. It is show that the 2D numerical predictions obtained for porosity less than 35% give very good agreement to the experimental data and the Hashin-Shtrikman upper model. The underestimation of the 2D numerical predictions mainly comes from the difference between the 2D image and the 3D structure of the real system. The radiation heat transfer is also a non-negligible factor for thermal transfer in foamed concretes for high porosity cases, and the radiation influence is diminishing as the porosity decreases.

    Original languageEnglish
    Pages (from-to)1278-1291
    Number of pages14
    JournalConstruction and Building Materials
    Volume47
    DOIs
    Publication statusPublished - Oct 2013

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    Keywords

    • Foamed concrete
    • Effective thermal conductivity
    • X-ray computerized tomography
    • Random generation method
    • Resistor network analogy method

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