Theoretical and computational modeling of thermal properties of lightweight concrete

There is an increasing interest in developing and utilizing lightweight concrete (LWC) due to its environmental, structural, and economic benefits. In addition, replacing natural sand with lightweight particles has a direct positive impact on the thermal properties of the concrete mix. While there are many experimental studies available on the thermal properties of LWC, limited predictive capabilities exist. In this work, we examine a number of analytical models and assess their capabilities of predicting the effective thermal conductivity (ETC) of LWC mixtures. Six different mixtures were prepared by replacing 0%, 20%, 40%, 60%, 80%, and 100% of natural sand by volume with expanded perlite (EP) aggregate. Experimental measurements were conducted to evaluate their thermal conductivities (TC), thermal diffusivities, and volumetric heat capacities. In addition, X-ray computed tomography (CT) images coupled with numerical simulations were employed to perform microstructure analysis and numerical simulations of the ETC. This paper presents a comparison between the experimental and analytical results, and it discusses the predictive capabilities of the analytical models. Experimentally, the use of EP reduced the ETC from 1.81 W. m^-1. K^-1 at 0% EP to 0.688 W. m^-1. K^-1 at 100% EP. Among the analytical models, the Woodside & Messmer model exhibited the best prediction of the experimental data with a maximum error of 18.7%. The numerical simulations provided predictions of the ETC at 0%, 60%, and 100% EP with an error up to 10.5%. Based on the concerned application, the incorporated EP percentage can be optimized emanate on the relationship between ETC and the unit weight of LWC. The analytical Woodside & Messmer model and the numerical simulations using of X-ray CT images model can be used in the design of LWC mixtures with desired thermal properties.

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Published in: Case Studies in Thermal Engineering
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.csite.2021.101683