Effective thermal conductivity of granular soils: a review of influencing factors and prediction models towards an investigation framework through multiscale characters

Abstract

The effective thermal conductivity of soil is important to geo-engineering applications, and it is controlled by factors across different length scales. Through a comprehensive review of these factors, we found that while other more traditional factors have been well studied, there is still a lack of characterisation of soil microscale and mesoscale structures and their influence on effective thermal conductivity. In addition, after reviewing the models available in the literature for soil effective thermal conductivity prediction, it was found that compared with empirical and theoretical models, machine learning models can account for the influence of multi-scale factors, however, research into them is scarce. To overcome the limitations of previous research, we proposed a framework that can investigate the factors influencing soil effective thermal conductivity at multiple scale. It includes the impact of soil structural factors at micro to mesoscale, and this impact is integrated with the influence from other factors for accurate thermal conductivity prediction.